(Book Slides) - UCRvahid/pubs/sdes_slides.pdf · Transistors, resistors, capacitors Gates,...
216
UC Irvine Copyright (c) 1994 Daniel D. Gajski, Frank Vahid, Sanjiv Narayan, and Jie Gong 1 of 214 SPECIFICATION AND DESIGN OF EMBEDDED SYSTEMS by Daniel D. Gajski Frank Vahid Sanjiv Narayan Jie Gong University of California at Irvine Department of Computer Science Irvine, CA 92715-3425
Transcript of (Book Slides) - UCRvahid/pubs/sdes_slides.pdf · Transistors, resistors, capacitors Gates,...
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
g1
of21
4
SP
EC
IFIC
AT
ION
AN
DD
ES
IGN
OF
EM
BE
DD
ED
SY
ST
EM
S
by
Dan
ielD
.Gaj
ski
Fra
nkV
ahid
San
jivN
aray
anJi
eG
ong
Uni
vers
ityof
Cal
iforn
iaat
Irvi
neD
epar
tmen
tofC
ompu
ter
Sci
ence
Irvi
ne,C
A92
715-
3425
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gIn
trod
uctio
n2
of21
4
Des
ign
repr
esen
tatio
ns
� Beh
avio
ral
Rep
rese
nts
func
tiona
lity
butn
otim
plem
enta
tion
� Str
uctu
ral
Rep
rese
nts
conn
ectiv
itybu
tnot
dim
ensi
onal
ity
� Phy
sica
lR
epre
sent
sdi
men
sion
ality
butn
otfu
nctio
nalit
y
UC
Irvi
neC
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ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gIn
trod
uctio
n3
of21
4
Leve
lsof
abst
ract
ion
Tra
nsis
tor
Gat
e
Reg
iste
r
Pro
cess
or
Beh
avio
ral
fo
rms
Str
uctu
ral
com
pone
nts
Phy
sica
l o
bjec
tsLe
vels
PC
Bs,
MC
Ms
Diff
eren
tial e
q.,
curr
ent−
volta
ge
dia
gram
s
Boo
lean
equ
atio
ns,
finite
−st
ate
mac
hine
s
Exe
cuta
ble
spec
.,
pro
gram
sP
roce
ssor
s, c
ontr
olle
rs,
m
emor
ies,
AS
ICs
Add
ers,
com
para
tors
, r
egis
ters
, cou
nter
s, r
egis
ter
files
, que
ues
Gat
es,
flip−
flops
Tra
nsis
tors
, r
esis
tors
, c
apac
itors
Ana
log
and
dig
ital c
ells
Mod
ules
,
units
Mic
roch
ips,
A
SIC
s
Alg
orith
ms,
flo
wch
arts
, in
stru
ctio
n se
ts,
gene
raliz
ed F
SM
UC
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neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gIn
trod
uctio
n4
of21
4
Des
ign
met
hodo
logi
es
� Cap
ture
-and
-sim
ulat
eS
chem
atic
capt
ure
Sim
ulat
ion
� Des
crib
e-an
d-sy
nthe
size
Har
dwar
ede
scrip
tion
lang
uage
Beh
avio
rals
ynth
esis
Logi
csy
nthe
sis
� Spe
cify
-exp
lore
-re�
neE
xecu
tabl
esp
eci�c
atio
nS
oftw
are
and
hard
war
epa
rtiti
onin
gE
stim
atio
nan
dex
plor
atio
nS
peci
�cat
ion
re�n
emen
t
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gIn
trod
uctio
n5
of21
4
Mot
ivat
ion
if (
x =
0)
then
y
= a
* b
/ 2
Pro
cess
orM
emor
y
AS
ICI/O
Exe
cuta
ble
spec
ifica
tion
S
yste
mim
plem
enta
tion
Mod
els
Lang
uage
s
Par
titio
ning
Est
imat
ion
Ref
inem
ent
V
ideo
acce
lera
tor
Beh
avio
ral s
ynth
esis
Logi
c sy
nthe
sis
Sof
twar
e co
mpi
latio
nP
hysi
cal d
esig
nT
est g
ener
atio
nM
anuf
actu
ring
UC
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ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gO
utlin
e6
of21
4
Out
line
� Intr
oduc
tion
� Des
ign
mod
els
and
arch
itect
ures
� Sys
tem
-des
ign
lang
uage
s
� An
exam
ple
� Tran
slat
ion
� Par
titio
ning
� Est
imat
ion
� Re�
nem
ent
� Met
hodo
logy
and
envi
ronm
ents
UC
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neC
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ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es7
of21
4
Mod
els
and
arch
itect
ures
Impl
emen
tatio
n
Des
ign
proc
ess
Mod
els
are
conc
eptu
al v
iew
s of
the
syst
em’s
func
tiona
lity
Mod
els
Arc
hite
ctur
es
Spe
cific
atio
n +
Con
stra
ints
Arc
hite
ctur
es a
re a
bstr
act v
iew
s of
the
syst
em’s
impl
emen
tatio
n
(Spe
cific
atio
n)
(Im
plem
enta
tion)
UC
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ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es8
of21
4
Mod
els
and
arch
itect
ures
� Mod
el:
ase
toff
unct
iona
lobj
ects
and
rule
sfo
rco
mpo
sing
thes
eob
ject
s
� Arc
hite
ctur
e:a
seto
fim
plem
enta
tion
com
pone
nts
and
thei
rco
nnec
tions
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es9
of21
4
Mod
els
ofan
elev
ator
cont
rolle
r
then
the
elev
ator
rem
ains
idle
.lo
op
if
(req
_flo
or =
cur
r_flo
or)
then
dire
ctio
n :=
idle
;
el
sif (
req_
floor
< c
urr_
floor
) th
en
di
rect
ion
:= d
own;
elsi
f (r
eq_f
loor
> c
urr_
floor
) th
en
di
rect
ion
:= u
p;
en
d if;
end
loop
;
then
low
er th
e el
evat
or to
the
requ
este
d flo
or.
"If t
he e
leva
tor
is s
tatio
nary
and
the
floor
r
eque
sted
is
equa
l to
the
curr
ent f
loor
,
If th
e el
evat
or is
sta
tiona
ry a
nd th
e flo
or
requ
este
d is
less
than
the
curr
ent f
loor
,
If th
e el
evat
or is
sta
tiona
ry a
nd th
e flo
or
requ
este
d is
gre
ater
than
the
curr
ent f
loor
, th
en r
aise
the
elev
ator
to th
e re
ques
ted
floor
."
(req
_flo
or <
cur
r_flo
or)
/ di
rect
ion
:= d
own
�
(req
_flo
or =
cur
r_flo
or)
/ di
rect
ion
:= id
le
�(r
eq_f
loor
> c
urr_
floor
)/
dire
ctio
n :=
up
�(r
eq_f
loor
= c
urr_
floor
)/
dire
ctio
n :=
idle
�
(req
_flo
or =
cur
r_flo
or)
/ di
rect
ion
:= id
le
�(r
eq_f
loor
> c
urr_
floor
)/
dire
ctio
n :=
up
�
(req
_flo
or <
cur
r_flo
or)
/ di
rect
ion
:= d
own
�
(req
_flo
or <
cur
r_flo
or)
/ di
rect
ion
:= d
own
�
(req
_flo
or <
cur
r_flo
or)
/ di
rect
ion
:= u
p
�U
pId
leD
own
(a)
Eng
lish
desc
riptio
n(b
) A
lgor
ithm
ic m
odel
(c)
Sta
te−m
achi
ne m
odel
UC
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ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es10
of21
4
Arc
hite
ctur
esfo
rim
plem
entin
gth
eel
evat
orco
ntro
ller
Sta
te r
egis
ter
dire
ctio
nCombinational logic
req_
floor
curr
_flo
or
In/o
ut p
orts
Mem
ory
Pro
cess
orB
us
req_
floor
curr
_flo
ordi
rect
ion
(b)
Sys
tem
leve
l(a
) R
egis
ter
leve
l
UC
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ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es11
of21
4
Mod
els
� Sta
te-o
rient
edm
odel
sF
inite
-sta
tem
achi
ne(F
SM
),P
etri
net,
Hie
rarc
hica
lcon
curr
entF
SM
� Act
ivity
-orie
nted
mod
els
Dat
a ow
grap
h,F
low
char
t
� Str
uctu
re-o
rient
edm
odel
sB
lock
diag
ram
,RT
netli
st,G
ate
netli
st
� Dat
a-or
ient
edm
odel
sE
ntity
-rel
atio
nshi
pdi
agra
m,J
acks
on’s
diag
ram
� Het
erog
eneo
usm
odel
sC
ontr
ol/d
ata
owgr
aph,
Str
uctu
rech
art,
Pro
gram
min
gla
ngua
gepa
radi
gm,
Obj
ect-
orie
nted
para
digm
,Pro
gram
-sta
tem
achi
ne,Q
ueue
ing
mod
el
UC
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ight
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4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es12
of21
4
Sta
teor
ient
ed:
Fin
ite-s
tate
mac
hine
(Mea
lym
odel
)
S 1S
2
S 3
star
tr2
/u1
r1/d
1
r3/u2
r1/d2r2/d1
r3/u1
r2/n
r3/n
r1/n
S =
{ s
1, s
2, s
3}I =
{r1
, r2,
r3}
O =
{d2
, d1,
n, u
1, u
2}f:
S x
I −
> S
h: S
x I
−>
O
UC
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neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es13
of21
4
Sta
teor
ient
ed:
Fin
ite-s
tate
mac
hine
(Moo
rem
odel
)
S 12
SS 11 13
S S21 S 22 23
S S S
31 3332
star
t/d
2� /d1� /n�
/d1� /n� /u1�
/n� /u1� /u2�
r1r1r1
r2
r1
r1
r1
r2r2
r1
r1r1r2
r2
r3
r3r2r2
r3
r3 r3r2
r3r2
r3 r3 r3
UC
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neC
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ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es14
of21
4
Sta
teor
ient
ed:
Fin
ite-s
tate
mac
hine
with
data
path
S 1
(cur
r_flo
or !=
req
_flo
or)
/ out
put :
= r
eq_f
loor
− c
urr_
floor
; cu
rr_f
loor
:= r
eq_f
loor
�(c
urr_
floor
= r
eq_f
loor
)/ o
utpu
t :=
0
�
star
t
UC
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neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es15
of21
4
Fin
ite-s
tate
mac
hine
s
� Mer
its:
repr
esen
tsys
tem
’ste
mpo
ralb
ehav
ior
expl
icitl
ysu
itabl
efo
rco
ntro
l-dom
inat
edsy
stem
� Dem
erits
:la
ckof
hier
arch
yan
dco
ncur
renc
yre
sulti
ngin
stat
eor
arc
expl
osio
nw
hen
repr
esen
ting
com
plex
syst
ems
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es16
of21
4
Sta
teor
ient
ed:
Pet
rine
ts
Net
= (
P, T
, I, O
, u)
P =
{p1
, p2,
p3,
p4,
p5}
T =
{t1
, t2,
t3, t
4}
I(t1
) =
{p1
}I(
t2)
= {
p2,p
3,p5
}I(
t3)
= {
p3}
I(t4
) =
{p4
}
p1p5
p2 p3
p4t4 t3
t2t1
I:O
:u:
u(p1
) =
1u(
p2)
= 1
u(p3
) =
2u(
p4)
= 0
u(p5
) =
1
O(t
1) =
{p5
}O
(t2)
= {
p3,p
5}O
(t3)
= {
p4}
O(t
4) =
{p2
,p3}
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es17
of21
4
Pet
rine
ts
t2t1
t1t2
t1
t1t2
t1t2
t3t4
(a)
Seq
uenc
e(b
) B
ranc
h(c
) S
ynch
roni
zatio
n
(d)
Res
ourc
e co
nten
tion
(e)
Con
curr
ency
UC
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ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es18
of21
4
Pet
rine
ts
� Mer
its:
good
atm
odel
ing
and
anal
yzin
gco
ncur
rent
syst
ems
� Dem
erits
:‘ a
t’mod
elth
atis
inco
mpr
ehen
sibl
ew
hen
syst
emco
mpl
exity
incr
ease
s
UC
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ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es19
of21
4
Sta
teor
ient
ed:
Hie
rarc
hica
lco
ncur
rent
FS
M
Y A
B C
D
E
F
G
b
u
r
as
a(P
)/c
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es20
of21
4
Hie
rarc
hica
lco
ncur
rent
FS
Ms
� Mer
its:
supp
ortb
oth
hier
arch
yan
dco
ncur
renc
ygo
odfo
rre
pres
entin
gco
mpl
exsy
stem
s
� Dem
erits
:co
ncen
trat
eon
lyon
mod
elin
gco
ntro
lasp
ects
and
notd
ata
and
activ
ities
UC
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neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es21
of21
4
Act
ivity
orie
nted
:D
ata
owgr
aphs
(DF
G)
A 1
A 2
X
Y
VV
’
Z
W
Y
W
Z
V’
A 2.
1A
2.2
A 2.
3
File
+X
YW
*Z
Inpu
t
Out
put
Out
put
(a)
Act
ivity
leve
l(b
) O
pera
tion
leve
l
UC
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ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es22
of21
4
Dat
a ow
grap
hs
� Mer
its:
supp
orth
iera
rchy
suita
ble
for
spec
ifyin
gco
mpl
extr
ansf
orm
atio
nals
yste
ms
repr
esen
tpro
blem
-inhe
rent
data
depe
nden
cies
� Dem
erits
:do
note
xpre
sste
mpo
ralb
ehav
iors
orco
ntro
lseq
uenc
ing
wea
kfo
rm
odel
ing
embe
dded
syst
ems
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es23
of21
4
Act
ivity
orie
nted
:F
low
char
t(C
FG
)
MA
X =
ME
M(J
)
J =
1M
AX
= 0
J =
J+
1
J >
NM
EM
(J)
> M
AX
star
t
No
Yes
Yes
No
end
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es24
of21
4Flo
wch
arts
� Mer
its:
usef
ulto
repr
esen
ttas
ksgo
vern
edby
cont
rol
owca
nim
pose
aor
der
tosu
pers
ede
natu
rald
ata
depe
nden
cies
� Cha
ract
eris
tics:
used
only
whe
nth
esy
stem
’sco
mpu
tatio
nis
wel
lkno
wn
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es25
of21
4
Str
uctu
reor
ient
ed:
Com
pone
nt-c
onn
ectiv
ity
diag
ram
s
Reg
iste
r fil
e
ALU
LIR
RIR
Rig
htbu
sLe
ftbu
sA
B
Pro
cess
or
Pro
gram
mem
ory
Dat
am
emor
y
I/Oco
proc
esso
rA
pplic
atio
n
spec
ific
har
dwar
eSys
tem
bus
(a)
Blo
ck d
iagr
am(b
) R
T n
etlis
t(c
) G
ate
netli
st
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es26
of21
4
Com
pone
nt-c
onne
ctiv
itydi
agra
ms
� Mer
its:
good
atre
pres
entin
gsy
stem
’sst
ruct
ure
� Cha
ract
eris
tics:
ofte
nus
edin
the
late
rph
ases
ofde
sign
proc
ess
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es27
of21
4
Dat
aor
ient
ed:
Ent
ity-r
elat
ions
hip
diag
ram
Ord
erC
usto
mer
Pro
duct
Sup
plie
r
Ava
ilabi
lity
P
.O.
inst
ance
Req
uest
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es28
of21
4
Ent
ity-r
elat
ions
hip
diag
ram
s
� Mer
its:
prov
ide
ago
odvi
ewof
the
data
inth
esy
stem
,als
osu
itabl
efo
rex
pres
sing
com
plex
rela
tions
amon
gva
rious
kind
sof
data
� Dem
erits
:do
notd
escr
ibe
any
func
tiona
lor
tem
pora
lbeh
avio
rof
the
syst
em.
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es29
of21
4
Dat
aor
ient
ed:
Jack
son’
sdi
agra
m
Rec
tang
le
Dra
win
g
Col
or
Circ
le
Wid
thH
eigh
t
Nam
e
*
AN
D
OR
AN
D
Sha
pe
Rad
ius
Use
rs
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es30
of21
4
Jack
son’
sdi
agra
ms
� Mer
its:
suita
ble
for
repr
esen
ting
data
havi
nga
com
plex
com
posi
test
ruct
ure.
� Dem
erits
:do
notd
escr
ibe
any
func
tiona
lor
tem
pora
lbeh
avio
rof
the
syst
em.
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es31
of21
4
Het
erog
eneo
us:
Con
trol
/dat
a ow
grap
h
Con
trol
A2
A3
A 1
enab
le
0S 1S 2S
star
t
disa
ble
enab
le
disa
ble di
sabl
een
able
,ena
ble
/ dis
able
�
A 1A
3
/ ena
ble
�
enab
le
,A 1
A2
/ disable � stopdisable , A2A3
star
tst
op
W =
10
X
W
Y
Z
W =
10
(a)
Act
ivity
leve
l(b
) O
pera
tion
leve
l
+
12
E
+
+
+
Rea
d X
Rea
d W
Writ
e A
Con
st 3
Rea
d X
Writ
e A
Rea
d X
Con
st 2 C
onst
5
Writ
e X
Writ
e A
A :=
X +
WA
:= X
+ 3
X :=
X +
2A
:= X
+ 5
Dat
a flo
w g
raph
s
Con
trol
flow
gra
ph
C
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es32
of21
4
Con
trol
/dat
a ow
grap
hs
� Mer
its:
corr
ectt
hein
abili
tyof
DF
Gin
repr
esen
ting
the
cont
rolo
fasy
stem
corr
ectt
hein
abili
tyof
CF
Gto
repr
esen
tdat
ade
pend
enci
es
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es33
of21
4
Het
erog
eneo
us:
Str
uctu
rech
art
Get
Tra
nsfo
rm
Get
_AG
et_B
Cha
nge_
AC
hang
e_B
Do_
Loop
1D
o_Lo
op2
Com
pute
Mai
n
Out
_C
Dat
aco
ntro
l
AB
A,B
A,B
A’,B
’
A
A’
B’
B
A’,B
’C
,D
C
Bra
nch
Itera
tion
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es34
of21
4
Str
uctu
rech
arts
� Mer
its:
repr
esen
tbot
hda
taan
dco
ntro
l
� Cha
ract
eris
tics:
used
inth
epr
elim
inar
yst
ages
ofpr
ogra
mde
sign
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es35
of21
4
Het
erog
eneo
us:
Pro
gram
min
gla
ngua
ges
� Impe
rativ
evs
decl
arat
ive
prog
ram
min
gla
ngua
ges:
C,P
asca
l,A
da,C
++
,etc
.LI
SP,
PR
OLO
G,e
tc.
� Seq
uent
ialv
sco
ncur
rent
prog
ram
min
gla
ngua
ges:
Pas
cal,
C,e
tc.
CS
P,A
DA
,VH
DL,
etc.
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es36
of21
4
Pro
gram
min
gla
ngua
ges
� Mer
its:
mod
elda
ta,a
ctiv
ity,a
ndco
ntro
l
� Dem
erits
:do
note
xplic
itly
mod
elth
esy
stem
’sst
ates
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es37
of21
4
Het
erog
eneo
us:
Obj
ect-
orie
nted
para
digm
Dat
a
Ope
ratio
ns
Obj
ect
Dat
a
Ope
ratio
ns
Obj
ect
Dat
a
Ope
ratio
ns
Obj
ect
Tra
nsfo
rmat
ion
f
unct
ion
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es38
of21
4
Obj
ect-
orie
nted
para
digm
s
� Mer
its:
supp
orti
nfor
mat
ion
hidi
ng,i
nher
itanc
e,na
tura
lcon
curr
ency
� Dem
erits
:no
tsui
tabl
efo
rsy
stem
sw
ithco
mpl
icat
edtr
ansf
orm
atio
nfu
nctio
ns
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es39
of21
4
Het
erog
eneo
us:
Pro
gram
-sta
tem
achi
ne
e2
e3
Y A
B C
D
e1
varia
ble
A: a
rray
[1..2
0] o
f int
eger
varia
ble
i, m
ax: i
nteg
er ;
max
= 0
;fo
r i
= 1
to 2
0 do
if (
A[i]
> m
ax )
then
m
ax =
A[i]
;
en
d if;
end
for
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es40
of21
4
Pro
gram
-sta
tem
achi
nes
� Mer
its:
repr
esen
tsys
tem
’sst
ates
,dat
a,co
ntro
land
activ
ities
ina
sing
lem
odel
over
com
eth
elim
itatio
nsof
prog
ram
min
gla
ngua
ges
and
HC
FS
Mm
odel
s
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es41
of21
4
Het
erog
eneo
us:
Que
uein
gm
odel
Que
ueS
erve
rA
rriv
ing
requ
ests
Arr
ivin
gre
ques
ts
(a)
One
ser
ver
(b)
Mul
tiple
ser
vers
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es42
of21
4
Que
uein
gm
odel
� Cha
ract
eris
tics:
used
for
anal
yzin
gsy
stem
’spe
rfor
man
ce,a
ndca
n�n
dut
iliza
tion,
queu
eing
leng
th,t
hrou
ghpu
t
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es43
of21
4Arc
hite
ctur
es
� App
licat
ion-
spec
i�car
chite
ctur
esC
ontr
olle
rar
chite
ctur
e,D
atap
ath
arch
itect
ure,
Fin
ite-s
tate
mac
hine
with
data
path
(FS
MD
).
� Gen
eral
-pur
pose
proc
esso
rsC
ompl
exin
stru
ctio
nse
tcom
pute
r(C
ISC
)R
educ
edin
stru
ctio
nse
tcom
pute
r(R
ISC
)V
ecto
rm
achi
neV
ery
long
inst
ruct
ion
wor
dco
mpu
ter
(VLI
W)
� Par
alle
lpro
cess
ors
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es44
of21
4
Con
trol
ler
arch
itect
ure
Nex
t−st
ate
func
tion
Out
put
func
tion
Out
puts
Inpu
ts
Sta
te r
egis
ter
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es45
of21
4
Dat
apat
har
chite
ctur
e
x(i)
b(0)
x(i−
1)b(
1)x(
i−2)
b(2)
b(3)
x(i−
3)
y(i)
++
x(i)
b(0)
x(i−
1)b(
1)x(
i−2)
b(2)
b(3)
x(i−
3)
y(i)
Pip
elin
e st
ages
Pip
elin
e st
ages
+
*
+
++
**
**
**
*
(a)
Thr
ee s
tage
pip
elin
e
(b)
Fou
r st
age
pipe
line
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es46
of21
4
FS
MD
Nex
t−st
ate
func
tion
Out
put
func
tion
Dat
apat
h
Sta
tus
Dat
apat
h in
puts
Dat
apat
h ou
tput
s
Con
trol
uni
tSta
te r
egis
ter
Con
trol
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es47
of21
4
CIS
Car
chite
ctur
e Sta
tus
Con
trol
uni
tIn
stru
ctio
n re
g.
Dat
apat
h
Mem
ory
+1
Mic
ropr
ogra
m
mem
ory
Add
ress
sele
ctio
n
logi
c
PC
Mic
roP
C
Con
trol
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es48
of21
4
RIS
Car
chite
ctur
e
Sta
tus
Con
trol
uni
t
Inst
ruct
ion
reg.
Har
dwire
dou
tput
and
next
−st
ate
l
ogic
Mem
ory
Reg
iste
rfil
e
ALU
Inst
r.ca
che
Dat
aca
che
Dat
apat
h
Sta
te r
egis
ter
Con
trol
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es49
of21
4
Vec
tor
mac
hine
s
Inte
rleav
ed m
emor
y
Vec
tor
regi
ster
s S
cala
rre
gist
ers
Mem
ory
pip
esM
emor
y p
ipes
Vec
tor
func
tiona
l
uni
t
Sca
lar
func
tiona
l
uni
t
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es50
of21
4
VLI
War
chite
ctur
e
+
Mem
ory
+*
*
Reg
iste
r fil
e
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es51
of21
4
Par
alle
lpr
oces
sors
:S
IMD
/MIM
D
Con
trol
un
it
Pro
c. 0
Mem
. 0
Pro
c. 1
Mem
. 1
Pro
c. N
−1
Mem
. N−
1
Inte
rcon
nect
ion
netw
ork
PE
0P
EP
E1
N−
1
(a)
Mes
sage
pas
sing
Pro
c. 0
Mem
. 0
Pro
c. 1
Mem
. 1
Pro
c. N
−1
Mem
. N−
1
Inte
rcon
nect
ion
netw
ork
(b)
Sha
red
mem
ory
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
odel
s&
Arc
hite
ctur
es52
of21
4Con
clus
ion
� Diff
eren
tmod
els
focu
son
diffe
rent
aspe
cts
� Pro
per
mod
elne
eds
tore
pres
ents
yste
m’s
feat
ures
� Mod
els
are
impl
emen
ted
inar
chite
ctur
es
� Sm
ooth
tran
sfor
mat
ion
ofm
odel
sto
arch
itect
ures
incr
ease
spr
oduc
tivity
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
g53
of21
4
Sys
tem
spec
i�cat
ion
� For
ever
yde
sign
,the
reex
ists
aco
ncep
tual
view
� Con
cept
ualv
iew
depe
nds
onap
plic
atio
nC
ompu
tatio
n:
conc
eptu
aliz
edas
apr
ogra
mC
ontr
olle
r:
conc
eptu
aliz
edas
ast
ate-
mac
hine
� Goa
lof
spec
i�cat
ion
lang
uage
Cap
ture
conc
eptu
alvi
eww
ithm
inim
umde
sign
eref
fort
� Idea
llan
guag
e1-
to-1
map
ping
betw
een
conc
eptu
alm
odel
&la
ngua
geco
nstr
ucts
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n54
of21
4
Out
line
� Cha
ract
eris
tics
ofco
mm
only
used
conc
eptu
alm
odel
s:C
oncu
rren
cy,
hier
arch
y,sy
nchr
oniz
atio
n
� Req
uire
men
tsfo
rem
bedd
edsy
stem
spec
i�cat
ion
� Eva
luat
eH
DLs
with
resp
ectt
oem
bedd
edsy
stem
sV
HD
L,V
erilo
g,E
ster
el,C
SP,
Sta
tech
arts
,SD
L,S
pecC
hart
s
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n55
of21
4
Con
curr
ency
� Beh
avio
r:a
chun
kof
syst
emfu
nctio
nalit
ye.
g.pr
oces
s,pr
oced
ure,
stat
e-m
achi
ne
� Sys
tem
ofte
nco
ncep
tual
ized
asse
tofc
oncu
rren
tbeh
avio
rs
� Con
curr
ency
can
exis
tatd
iffer
enta
bstr
actio
nle
vels
:Jo
b-le
vel
Task
-leve
lS
tate
men
t-le
vel
Ope
ratio
n-le
vel
Bit-
leve
l
� Two
type
sof
conc
urre
ncy
with
ina
beha
vior
Dat
a-dr
iven
,Con
trol
-driv
en
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n56
of21
4
Dat
a-dr
iven
conc
urre
ncy
� Ope
ratio
nsex
ecut
ew
hen
inpu
tdat
ais
avai
labl
e
� Exe
cutio
nor
der
dete
rmin
edby
data
depe
nden
cies
1: Q
= A
+ B
2:
Y =
X +
P3:
P =
(C
− D
) *
Qm
ultip
ly
AB
add
CD
subt
ract
X
add
YP
Q
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n57
of21
4
Con
trol
-driv
enco
ncur
renc
y
� Con
trol
thre
ad:
seto
fope
ratio
nsex
ecut
edse
quen
tially
� Con
curr
ency
repr
esen
ted
bym
ultip
leco
ntro
lthr
eads
For
k-jo
inst
atem
ent
Pro
cess
stat
emen
tA
BC
Q R
AC
B
sequ
entia
l be
havi
or X
be
gin
Q
();
f
ork
A()
; B
(); C
();
join
;
R()
;en
d be
havi
or X
;
conc
urre
nt b
ehav
ior
X
begi
n
pro
cess
A()
;
pro
cess
B()
;
pro
cess
C()
;en
d be
havi
or X
;
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n58
of21
4Sta
te-t
rans
ition
s
� Sys
tem
sof
ten
are
stat
e-ba
sed,
e.g.
cont
rolle
rs
� Sta
tem
ayre
pres
ent
mod
eor
stag
eof
bein
gco
mpu
tatio
n
� Dif�
cultt
oca
ptur
eus
ing
prog
ram
min
gco
nstr
ucts
v
w
x
P
QR
S
star
t
u
y
finis
hT
z
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n59
of21
4
Hie
rarc
hy
� Req
uire
dfo
rm
anag
ing
syst
emco
mpl
exity
Allo
ws
syst
emm
odel
erto
focu
son
one
subs
yste
mat
atim
eE
nhan
ces
com
preh
ensi
onof
syst
emfu
nctio
nalit
yS
copi
ngm
echa
nism
for
obje
cts
like
type
san
dva
riabl
es
� Two
type
sof
hier
arch
yS
truc
tura
lhie
rarc
hyB
ehav
iora
lhie
rarc
hy
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n60
of21
4
Str
uctu
ral
hier
arch
y
� Sys
tem
repr
esen
ted
asse
tofi
nter
conn
ecte
dco
mpo
nent
s
� Inte
rcon
nect
ions
betw
een
com
pone
nts
repr
esen
twire
s
� Sev
eral
leve
ls:
syst
ems,
chip
s,R
T-co
mpo
nent
s,ga
tes
Mem
ory
Pro
cess
or
Con
trol
Log
icD
atap
ath
data
bus
cont
rol
lin
es
Sys
tem
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n61
of21
4
Beh
avio
ral
hier
arch
y
� Abi
lity
tosu
cces
sive
lyde
com
pose
beha
vior
into
sub-
beha
vior
s
� Con
curr
entd
ecom
posi
tion
For
k-jo
inP
roce
ss
� Seq
uent
iald
ecom
posi
tion
Pro
cedu
reS
tate
-mac
hine
e1
e3
P
QR
R1
R2
Q1
Q3
Q2
e2
e4 e6e5 e7
e8
beha
vior
P
var
iabl
e x,
y;
begi
n
Q(x
) ;
R
(y)
;en
d b
ehav
ior
P;
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n62
of21
4
Pro
gram
min
gco
nstr
ucts
� Som
ebe
havi
ors
easi
lyco
ncep
tual
ized
asse
quen
tiala
lgor
ithm
s
� Wid
eva
riety
ofco
nstr
ucts
avai
labl
eA
ssig
nmen
t,br
anch
ing,
itera
tion,
subp
rogr
ams,
recu
rsio
n,co
mpl
exda
taty
pes
(rec
ords
,lis
ts)
type
buf
fer_
type
is
arra
y (1
to 1
0) o
f int
eger
;va
riabl
e b
uf :
buffe
r_ty
pe;
varia
ble
i, j
: int
eger
;
for
i = 1
to 1
0
for
j =
i to
i
if (
buf(
i) >
buf
(j))
then
S
WA
P(b
uf(i)
, buf
(j));
e
nd if
;
end
for;
end
for;
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n63
of21
4
Beh
avio
ral
com
plet
ion
� Beh
avio
rco
mpl
etes
whe
nal
lcom
puta
tions
perf
orm
ed
� Adv
anta
ges
Beh
avio
rca
nbe
view
edw
ithou
tint
er-le
velt
rans
ition
sA
llow
sna
tura
ldec
ompo
sitio
nin
tose
quen
tials
ubbe
havi
ors
XY
e1
e2
e3
e4
B e5Y
1
Y2
X3
X1
X2
q 0
q 1 q 2
q 3
star
tfin
al
stat
e
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n64
of21
4Com
mun
icat
ion
� Con
curr
entb
ehav
iors
exch
ange
data
� Sha
red-
mem
ory
mod
elS
ende
rup
date
sco
mm
onm
ediu
mP
ersi
sten
t,N
on-p
ersi
sten
t
� Mes
sage
-pas
sing
mod
elD
ata
sent
over
abst
ract
chan
nels
Uni
dire
ctio
nal/
bidi
rect
iona
lP
oint
-to-
poin
t/m
ultiw
ayB
lock
ing
/non
-blo
ckin
g
shar
ed m
emor
y proc
ess
Qpr
oces
s P
proc
ess
P
begi
n
var
iabl
e x
..
..
sen
d (x
);
....
end
proc
ess
Q
begi
n
var
iabl
e y
.
...
rec
eive
(y)
;
....
end
chan
nel
C
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n65
of21
4Syn
chro
niza
tion
� Con
curr
entb
ehav
iors
exec
ute
atdi
ffere
ntsp
eeds
� Syn
chro
niza
tion
requ
ired
whe
nD
ata
exch
ange
dbe
twee
nbe
havi
ors
Diff
eren
tact
iviti
esm
ustb
epe
rfor
med
sim
ulta
neou
sly
� Two
type
sof
sync
hron
izat
ion
mec
hani
sms
Con
trol
-dep
ende
ntD
ata-
depe
nden
t
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n66
of21
4
Con
trol
-dep
end
ent
sync
hron
izat
ion
� Syn
chro
niza
tion
base
don
cont
rols
truc
ture
ofbe
havi
or
For
k-jo
in
Res
et
beha
vior
X
begi
n
Q()
;
for
k A
();
B()
; C()
; jo
in;
R
();
end
beha
vior
X;
sync
hron
izat
ion
poi
nt
Q R
AC
B
AB
C
AB
C
e
A2
A1
AB
AB
B1
B2
e
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n67
of21
4
Dat
a-de
pend
ent
sync
hron
izat
ion
� Syn
chro
niza
tion
base
don
com
mun
icat
ion
ofda
tabe
twee
nbe
havi
ors
A2
ente
red
A2
A1
AB
AB
e
B1 B2
(x=
1)
A
x:=
0A
1
x:=
1A
2
B1
B2
B
eAB
Syn
chro
niza
tion
by
sta
tus
dete
ctio
nS
ynch
roni
zatio
n by
com
mon
eve
ntS
ynch
roni
zatio
n by
c
omm
on v
aria
ble
A2
B2
B1
AB
ee
A1AB
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n68
of21
4
Exc
eptio
nha
ndlin
g
� Occ
urre
nce
ofev
entt
erm
inat
escu
rren
tcom
puta
tion
� Con
trol
tran
sfer
red
toap
prop
riate
next
mod
e
� Exa
mpl
eof
exce
ptio
ns:
inte
rrup
ts,r
eset
s
eP
1
P2
PQ
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n69
of21
4
Tim
ing
� Req
uire
dto
repr
esen
trea
lwor
ldim
plem
enta
tions
� Fun
ctio
nal
timin
g:
affe
cts
sim
ulat
ion
ofsy
stem
spec
i�cat
ion
wai
tfor
200
ns;
A<
=A
+1
afte
r10
0ns
;
� Tim
ing
cons
trai
nts
:gu
ide
synt
hesi
san
dve
ri�ca
tion
tool
s
time
max
10
ms
IN
OU
T
chan
nel C
(m
ax 1
0 M
b/s)
min
50
ns
beha
vior
B
beha
vior
Q
beha
vior
P
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n70
of21
4
Em
bedd
edsy
stem
spec
i�cat
ion
� Em
bedd
edsy
stem
:be
havi
orde
�ned
byin
tera
ctio
nw
ithen
viro
nmen
t
� Ess
entia
lcha
ract
eris
tics
Sta
te-t
rans
ition
sE
xcep
tions
Beh
avio
ralh
iera
rchy
Con
curr
ency
Pro
gram
min
gco
nstr
ucts
Beh
avio
ralc
ompl
etio
n
u
v w
x
star
t
P
Q
R
e
Q
P
P2
P1
fork
SP
QR
join�
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n71
of21
4
VH
DL
� IEE
Est
anda
rd,i
nten
ded
for
docu
men
tatio
nan
dex
chan
geof
desi
gns
[IEE
88]
� Cha
ract
eris
tics
supp
orte
dB
ehav
iora
lhie
rarc
hy:
sing
lele
velo
fpro
cess
esS
truc
tura
lhie
rarc
hy:
nest
edbl
ocks
and
com
pone
ntin
stan
tiatio
nsC
oncu
rren
cy:
task
-leve
l(pr
oces
s),s
tate
men
t-le
vel(
sign
alas
sign
men
t)P
rogr
amm
ing
cons
truc
tsC
omm
unic
atio
n:
shar
ed-m
emor
yus
ing
glob
alsi
gnal
sS
ynch
roni
zatio
n:
wai
ton
and
wai
tunt
ilst
atem
ents
Tim
ing
:w
aitf
orst
atem
ent,
afte
rcl
ause
inas
sign
men
ts
� Cha
ract
eris
tics
not
supp
orte
dE
xcep
tions
:pa
rtia
llysu
ppor
ted
bygu
arde
dsi
gnal
assi
gnm
ents
Sta
tetr
ansi
tions
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n72
of21
4
Ver
ilog
and
Est
erel
� Ver
ilog
[TM
91]d
evel
oped
aspr
oprie
tary
lang
uage
for
spec
i�cat
ion,
sim
ulat
ion
� Est
erel
[Hal
93]d
evel
oped
for
spec
i�cat
iono
frea
ctiv
esy
stem
s
� Cha
ract
eris
tics
supp
orte
d:B
ehav
iora
lhie
rarc
hy:
fork
-join
Str
uctu
ralh
iera
rchy
:hi
erar
chy
ofin
terc
onne
cted
mod
ules
Pro
gram
min
gco
nstr
ucts
Com
mun
icat
ion
:sh
ared
regi
ster
s(V
erilo
g)an
dbr
oadc
astin
g(E
ster
el)
Syn
chro
niza
tion
:w
aitf
oran
even
ton
asi
gnal
Tim
ing
:m
odel
ing
ofga
te,n
et,a
ssig
nmen
tdel
ays
inV
erilo
gE
xcep
tions
:di
sabl
e(V
erilo
g),w
atch
ing,
do-u
pto,
trap
stat
emen
ts(E
ster
el)
� Cha
ract
eris
tics
not
supp
orte
d:S
tate
tran
sitio
ns
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n73
of21
4
SD
L(S
peci
�cat
ion
and
Des
crip
tion
lang
uage
)
� CC
ITT
stan
dard
inte
leco
mm
unic
atio
nfo
rpr
otoc
olsp
eci�c
atio
n[B
HS
91]
� Cha
ract
eris
tics
supp
orte
dB
ehav
iora
lhie
rarc
hy:
nest
edda
ta o
wS
truc
tura
lhie
rarc
hy:
nest
edbl
ocks
Sta
tetr
ansi
tions
:st
ate
mac
hine
inpr
oces
ses
Com
mun
icat
ion
:m
essa
gepa
ssin
gTi
min
g:
timeo
uts
gene
rate
dby
timer
obje
ct
� Cha
ract
eris
tics
not
supp
orte
dE
xcep
tions
Pro
gram
min
gco
nstr
ucts
syst
em bloc
k
bloc
k
proc
ess
proc
ess
sign
al r
oute
chan
nel
chan
nel
chan
nel
sign
al r
oute
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n74
of21
4
CS
P(C
omm
unic
atin
gS
eque
ntia
lP
roce
sses
)
� Inte
nded
tosp
ecify
prog
ram
sru
nnin
gon
mul
tipro
cess
orm
achi
nes
[Hoa
78]
� Cha
ract
eris
tics
supp
orte
dB
ehav
iora
lhie
rarc
hy:
fork
-join
usin
gpa
ralle
lcom
man
dP
rogr
amm
ing
cons
truc
tsC
omm
unic
atio
n:
mes
sage
pass
ing
usin
gin
put,
outp
utco
mm
ands
Syn
chro
niza
tion
:bl
ocki
ngm
essa
gepa
ssin
g
� Cha
ract
eris
tics
not
supp
orte
dE
xcep
tions
Sta
tetr
ansi
tions
Str
uctu
ralh
iera
rchy
Tim
ing
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n75
of21
4
Spe
cCha
rts
� Dev
elop
edfo
rem
bedd
edsy
stem
spec
i�cat
ion
[NV
G92
]
� PS
M(p
rogr
am-s
tate
mac
hine
)m
odel
+V
HD
L
� Cha
ract
eris
tics
supp
orte
dB
ehav
iora
lhie
rarc
hy:
sequ
entia
l/con
curr
ent
beha
vior
sS
tate
tran
sitio
ns:
TO
C(t
rans
ition
onco
mpl
etio
n)ar
csC
omm
unic
atio
n:
shar
edm
emor
y,m
essa
gepa
ssin
gE
xcep
tions
:T
I(tr
ansi
tion
imm
edia
tely
)ar
cs
� Cha
ract
eris
tics
sim
ilar
toV
HD
LP
rogr
amm
ing
cons
truc
tsS
truc
tura
lhie
rarc
hyS
ynch
roni
zatio
nan
dTi
min
g
XY
X2
e1
X1
e2
e3
Bport
P, Q
: in
inte
ger;
E
type
IN
TA
RR
AY
is
arr
ay
(na
tura
l ra
nge
<>
) o
f int
eger
;si
gnal
A :
IN
TA
RR
Y (
15 d
ownt
o 0)
;
varia
ble
MA
X :
inte
ger
;
MA
X :
= 0
;fo
r J
in
0 to
15
loop
if
( A
(J)
> M
AX
) th
en
m
ax :
= A
(J)
;
end
if;en
d lo
op
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n76
of21
4
Spe
cCha
rts
:st
ate
tran
sitio
ns
� Sta
tetr
ansi
tions
repr
esen
ted
byT
OC
and
TIa
rcs
betw
een
beha
vior
s
u
v w
x
star
t
P
Q
R
typ
e se
quen
tial s
ubbe
havi
ors
is
P
: (
TO
C, u
, Q)
;
Q :
(T
OC
, v, P
), (
TO
C, w
, R);
R
: (
TO
C, x
, Q);
beha
vior
MA
INbe
gin
b
ehav
ior
P ..
...
beh
avio
r Q
.....
b
ehav
ior
R ..
...
end
MA
IN;
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n77
of21
4
Spe
cCha
rts
:be
havi
oral
hier
arch
y
� Hie
rarc
hyre
pres
ente
dby
nest
edbe
havi
ors
� Beh
avio
rde
com
pose
din
tose
quen
tialo
rco
ncur
rent
subb
ehav
iors
fork
SP
QR
join
beha
vior
MA
IN
begi
n
b
ehav
ior
P ..
...
b
ehav
ior
Q_R
beg
in
b
ehav
ior
Q
b
ehav
ior
R
e
nd Q
_R;
b
ehav
ior
Sen
d M
AIN
;
ty
pe s
eque
ntia
l sub
beha
vior
s is
P
: (
TO
C, t
rue,
Q_R
);
Q_R
: (
TO
C, t
rue,
S);
S
: ;
.....
type
con
curr
ent s
ubbe
havi
or is
Q
: (T
OC
, tru
e, h
alt)
;
R :
(TO
C, t
rue,
hal
t);
.....
.....
.....
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n78
of21
4
Spe
cCha
rts
:ex
cept
ions
� Exc
eptio
nsre
pres
ente
dby
TI(
tran
sitio
nim
med
iate
ly)
arcs
e
Q
P
P2
P1
ty
pe s
eque
ntia
l sub
beha
vior
s is
P
: (
TI,
e, Q
);
Q :
;
......
.
...
....
......
beha
vior
MA
IN
begi
n
b
ehav
ior
P
be
havi
or P
1
be
havi
or P
2
b
ehav
ior
Q
end
MA
IN;
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
msp
eci�c
atio
n79
of21
4
Sum
mar
y
Con
curr
ency
Beh
avio
ral
Com
plet
ion
Exc
eptio
ns
VH
DL
Ver
ilog
CS
P
Sta
tech
arts
SD
L
Est
erel
Spe
cCha
rts
Beh
avio
ral
Hie
rarc
hy
S
tate
Tra
nsiti
ons
Pro
gram
Con
stru
cts
Em
bedd
ed S
yste
m F
eatu
res
Lang
uage
Fea
ture
fu
llysu
ppor
ted
Fea
ture
par
tially
supp
orte
d F
eatu
re n
otsu
ppor
ted
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
g80
of21
4
Spe
ci�c
atio
nex
ampl
e
� An
exec
utab
lesp
eci�c
atio
n-la
ngua
geen
able
s:E
arly
veri�
catio
nP
reci
sion
Aut
omat
ion
Doc
umen
tatio
n
� Ago
odla
ngua
ge/m
odel
mat
chre
duce
s:C
aptu
retim
eC
ompr
ehen
sion
time
Fun
ctio
nale
rror
s
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
peci
�cat
ion
exam
ple
81of
214
Out
line
� Cap
ture
anex
ampl
e’s
mod
elin
apa
rtic
ular
lang
uage
PS
Mm
odel
inth
eS
pecC
hart
sla
ngua
ge
� Poi
ntou
tthe
bene
�tsof
ago
odla
ngua
ge/m
odel
mat
ch
� Hig
hlig
htex
perim
ents
that
dem
onst
rate
thos
ebe
ne�ts
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
peci
�cat
ion
exam
ple
82of
214
Ans
wer
ing
mac
hine
cont
rolle
r’s
envi
ronm
ent
Con
trol
ler
Li
neci
rcui
try
rec
ann
hear
ann
mem
o
stop
rew
play
fwd
pla
ym
sgs
micA
nnou
ncem
ent
uni
tT
ape
unit
light
tolls
aver
hangup
offhook
beep
ring
tone
pow
er
on/o
ff
ann_done
ann_play
ann_rec
tape_fwd
tape_play
tape_rec
tape_rew
phon
e lin
e
mes
sage
s
tape_cnt
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
peci
�cat
ion
exam
ple
83of
214
Hig
hest
-leve
lvi
ewof
the
cont
rolle
r
Sys
tem
Off
Sys
tem
On
Con
trol
ler
pow
er=
’0’
pow
er=
’1’
Con
trol
ler
Li
neci
rcui
try
rec
ann
hear
ann
mem
o
stop
rew
play
fwd
pla
ym
sgs
micA
nnou
ncem
ent
uni
tT
ape
unit
light
tolls
aver
hangup
offhook
beep
ring
tone
pow
er
on/o
ff
ann_done
ann_play
ann_rec
tape_fwd
tape_play
tape_rec
tape_rew
phon
e lin
e
mes
sage
s
tape_cnt
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
peci
�cat
ion
exam
ple
84of
214
The
Sys
tem
On
beha
vior
Sys
tem
usua
llyre
spon
dsto
the
line
Pre
ssin
gan
ym
achi
nebu
tton
gets
imm
edia
tere
spon
se
Sys
tem
On
Res
pond
ToL
ine
Res
pond
ToM
achi
neB
utto
n
risin
g(an
y_bu
tton_
push
ed)
Con
trol
ler
Li
neci
rcui
try
rec
ann
hear
ann
mem
o
stop
rew
play
fwd
pla
ym
sgs
micA
nnou
ncem
ent
uni
tT
ape
unit
light
tolls
aver
hangup
offhook
beep
ring
tone
pow
er
on/o
ff
ann_done
ann_play
ann_rec
tape_fwd
tape_play
tape_rec
tape_rew
phon
e lin
e
mes
sage
s
tape_cnt
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
peci
�cat
ion
exam
ple
85of
214
The
Res
pond
ToM
achi
neB
utt
onbe
havi
or
Con
trol
ler
Li
neci
rcui
try
rec
ann
hear
ann
mem
o
stop
rew
play
fwd
pla
ym
sgs
micA
nnou
ncem
ent
uni
tT
ape
unit
light
tolls
aver�
hangup
offhook
beep
ring
tone
pow
er
on/o
ff
ann_done
ann_play
ann_rec
tape_fwd
tape_play
tape_rec
tape_rew
phon
e lin
e
mes
sage
s
tape_cnt
(a)
(b)
beha
vior
Res
pond
ToM
achi
neB
utto
n
type
cod
e is
begi
n
if (
play
=’1
’) th
en
H
andl
ePla
y;
els
if (f
wd=
’1’)
then
Han
dleF
wd;
e
lsif
(rew
=’1
’) th
en
H
andl
eRew
;
els
if (m
emo=
’1’)
then
Han
dleM
emo;
e
lsif
(sto
p=’1
’) th
en
H
andl
eSto
p;
els
if (h
ear_
ann=
’1’)
then
Han
dleH
earA
nn;
e
lsif
(rec
_ann
=’1
’) th
en
H
andl
eRec
Ann
;
els
if (p
lay_
msg
s=’1
’) th
en
H
andl
ePla
yMsg
s;
end
if;
end;
Res
pond
ToM
achi
neB
utto
n
Han
dleP
lay
Han
dleF
wd
Han
dleR
ew
Han
dleM
emo
Han
dleS
top
Han
dleH
earA
nn
Han
dleR
ecA
nn
Han
dleP
layM
sgs
play
=’1
’
fwd=
’1’
rew
=’1
’
mem
o=’1
’
stop
=’1
’
hear
_ann
=’1
’
rec_
ann=
’1’
play
_msg
s=’1
’
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
peci
�cat
ion
exam
ple
86of
214
The
Res
pond
ToL
ine
beha
vior
Mon
itors
line
for
rings
Ans
wer
slin
e
Res
pond
sto
exce
ptio
nsH
angu
pM
achi
netu
rned
off
Con
trol
ler
Li
neci
rcui
try
rec
ann
hear
ann
mem
o
stop
rew
play
fwd
pla
ym
sgs
micA
nnou
ncem
ent
uni
tT
ape
unit
light
tolls
aver
hangup
offhook
beep
ring
tone
pow
er
on/o
ff
ann_done
ann_play
ann_rec
tape_fwd
tape_play
tape_rec
tape_rew
phon
e lin
e
mes
sage
s
tape_cnt
risin
g(ha
ngup
)
Res
pond
ToL
ine
Mon
itor
Ans
wer
falli
ng(m
achi
ne_o
n)
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
peci
�cat
ion
exam
ple
87of
214
The
Mon
itor
beha
vior
Cou
nts
for
requ
ired
rings
Req
uire
men
tsm
aych
ange
Con
trol
ler
Li
neci
rcui
try
rec
ann
hear
ann
mem
o
stop
rew
play
fwd
pla
ym
sgs
micA
nnou
ncem
ent
uni
tT
ape
unit
light
tolls
aver
hangup
offhook
beep
ring
tone
pow
er
on/o
ff
ann_done
ann_play
ann_rec
tape_fwd
tape_play
tape_rec
tape_rew
phon
e lin
e
mes
sage
s
tape_cnt
Mon
itor
Mai
ntai
nRin
gsT
oWai
tC
ount
Rin
gs
sign
al r
ings
_to_
wai
t : in
tege
r ra
nge
1 to
20
:= 4
;
loop
rin
gs_t
o_w
ait <
= D
eter
min
eRin
gsT
oWai
t;
wai
t on
tolls
aver
, mac
hine
_on;
end
loop
;func
tion
Det
erm
ineR
ings
ToW
ait r
etur
n in
tege
r is
beg
in
if (
(num
_msg
s >
0)
and
(tol
lsav
er=
’1’)
and
(m
achi
ne_o
n=’1
’)) th
en
r
etur
n(2)
;
els
if (m
achi
ne_o
n=’1
’) th
en
ret
urn(
4);
e
lse
r
etur
n(15
);
end
if;
end;
varia
ble
I : in
tege
r ra
nge
0 to
20;
i :=
0;
whi
le (
i < r
ings
_to_
wai
t) lo
op
wai
t on
rings
_to_
wai
t, rin
g;
if (r
isin
g(rin
g))
then
i :=
i +
1;
en
d if;
end
loop
;
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
peci
�cat
ion
exam
ple
88of
214
The
Ans
wer
beha
vior
Ans
wer P
layA
nnou
ncem
ent
Rec
ordM
sgH
angu
p
Rem
oteO
pera
tion
risin
g(ha
ngup
)
butto
n="0
001"
butto
n="0
001"
beha
vior
Pla
yAnn
ounc
emen
t ty
pe c
ode
isbe
gin
a
nn_p
lay
<=
’1’;
w
ait u
ntil
ann_
done
= ’1
’;
ann
_pla
y <
= ’0
’;en
d;
beha
vior
Rec
ordM
sg t
ype
code
isbe
gin
P
rodu
ceB
eep(
1 s)
;
if (
hang
up =
’0’)
then
tap
e_re
c <
= ’1
’;
w
ait u
ntil
hang
up=
’1’
for
100
s;
P
rodu
ceB
eep(
1 s)
;
n
um_m
sgs
<=
num
_msg
s +
1;
tap
e_re
c <
= ’0
’;
end
if;
end;
(a)
(b)
(c)
Con
trol
ler
Li
neci
rcui
try
rec
ann
hear
ann
mem
o
stop
rew
play
fwd
pla
ym
sgs
micA
nnou
ncem
ent
uni
tT
ape
unit
light
tolls
aver
hangup
offhook
beep
ring
tone �
pow
er
on/o
ff
ann_done
ann_play
ann_rec
tape_fwd �
tape_play �
tape_rec � tape_rew �
phon
e lin
e
mes
sage
s
tape_cnt �
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
peci
�cat
ion
exam
ple
89of
214
The
Rem
oteO
pera
tion
beha
vior
Ow
ner
can
oper
ate
mac
hine
rem
otel
yby
phon
e
Ow
ner
iden
ti�es
him
self
byfo
urbu
tton
ID
Rem
oteO
pera
tion
code
_ok=
’1’
code
_ok=
’0’
hang
up=
’1’
Res
pond
ToC
mds
Che
ckC
ode
(a)
(b)
beha
vior
Che
ckU
serC
ode
type
cod
e is
begi
n
code
_ok
<=
true
;
for
(i in
1 to
4)
loop
wai
t unt
il to
ne /=
"11
11"
and
tone
’eve
nt;
if (t
one
/= u
ser_
code
(i))
then
c
ode_
ok <
= fa
lse;
end
if;
end
loop
;en
d;
Con
trol
ler
Li
neci
rcui
try
rec
ann
hear
ann
mem
o
stop
rew
play
fwd
pla
ym
sgs
micA
nnou
ncem
ent
uni
tT
ape
unit
light
tolls
aver
hangup
offhook
beep
ring
tone
pow
er
on/o
ff
ann_done
ann_play
ann_rec
tape_fwd
tape_play
tape_rec
tape_rew
phon
e lin
e
mes
sage
s
tape_cnt
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
peci
�cat
ion
exam
ple
90of
214
The
answ
erin
gm
achi
neco
ntro
ller
spec
i�cat
ion
Con
trol
ler
Li
neci
rcui
try
rec
ann
hear
ann
mem
o
stop
rew
play
fwd
pla
ym
sgs
micA
nnou
ncem
ent
uni
tT
ape
unit
light
tolls
aver
hangup
offhook
beep
ring
tone
pow
er
on/o
ff
ann_done
ann_play
ann_rec
tape_fwd
tape_play
tape_rec
tape_rew
phon
e lin
e
mes
sage
s
tape_cnt
Hea
rMsg
sCm
dsM
iscC
mds
Res
etT
ape
tone
="0
010"
hang
up=
’1’
othe
r
Res
pond
ToC
mds
code
_ok
not c
ode_
ok
hang
up=
’1’
Rem
oteO
pera
tion
Pla
yAnn
ounc
emen
tR
ecor
dMsg
Han
gup
tone
="0
001"
risin
g(ha
ngup
)A
nsw
er
Mon
itor
risin
g(ha
ngup
)
falli
ng(m
achi
ne_o
n)
Res
pond
ToL
ine
Initi
aliz
eSys
tem
Res
pond
ToM
achi
neB
utto
nS
yste
mO
n
Sys
tem
Off
Con
trol
ler
Che
ckU
serC
oderis
ing(
any_
butto
n_pu
shed
)
pow
er=
’1’
pow
er=
’0’
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
peci
�cat
ion
exam
ple
91of
214
Exe
cuta
ble
spec
i�cat
ion
use
Pre
cisi
onR
eada
bilit
y/pr
ecis
ion
com
pete
ina
natu
rall
angu
age
Exe
cuta
ble
spec
i�cat
ion
enco
urag
espr
ecis
ion
Des
igne
ras
ksqu
estio
ns,s
peci
�cat
ion
answ
ers
them
Lang
uage
/mod
elm
atch
(Spe
cCha
rts/
PS
M):
Hie
rarc
hyS
tate
-tra
nsiti
ons
Pro
gram
min
gco
nstr
ucts
Con
curr
ency
Exc
eptio
nsC
ompl
etio
nE
quiv
alen
ceof
stat
esan
dpr
ogra
ms
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
peci
�cat
ion
exam
ple
92of
214
Spe
ci�c
atio
nca
ptur
eex
perim
ent
VH
DL
Spe
cCha
rts
Num
ber
of m
odel
ers
40 3 2 1
16
0 03
Num
ber
of in
corr
ect s
peci
ficat
ions
sec
ond
time
Ave
rage
spe
cific
atio
n−tim
e in
min
utes
Num
ber
of in
corr
ect s
peci
ficat
ions
firs
t tim
e
VH
DL
mod
eler
sre
quire
d2.
5tim
eslo
nger
Two
VH
DL
spec
i�cat
ions
poss
esse
dco
ntro
lerr
ors
Spe
cCha
rts
wer
eef
fect
ive
for
stat
e-tr
ansi
tions
and
exce
ptio
ns
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
peci
�cat
ion
exam
ple
93of
214
Com
paris
onof
Spe
cCha
rts,
VH
DL
and
Sta
tech
arts
Ans
wer
ing
mac
hine
exam
ple
Specification attributes Shortcomings
Pro
gram
−st
ates
Arc
s
Con
trol
sig
nals
Line
s/le
af
Line
s
Wor
ds
No
sequ
entia
lpr
ogra
m c
onst
ruct
s
No
stat
e−tr
ansi
tion
cons
truc
ts
Con
cept
ual
m
odel
Spe
cCha
rts
V
HD
L(h
iera
rch.
)S
tate
char
ts
42 40 −−
−−
−−
−−
80
135 0
−−
−−
−−
42 40
0 7
446
1733
42 40 84 27
1592
6740
32
152 1
29
963
8088
X
X X X X
X X X
No
hier
arch
y
No
exce
ptio
nco
nstr
ucts
No
hier
arch
ical
ev
ents
VH
DL
(fla
t)
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
peci
�cat
ion
exam
ple
94of
214
Des
ign
qual
ityex
perim
ent
Des
ign
attr
ibut
e
3130
2277
5407
38
2630
2251
4881 38
Des
igne
d fr
om
E
nglis
hD
esig
ned
from
S
pecC
hart
s
Con
trol
tran
sist
ors
Dat
apat
h tr
ansi
stor
s
Tot
al tr
ansi
stor
s
Tot
al p
ins
� No
loss
inde
sign
qual
ityw
ithan
exec
utab
lela
ngua
ge
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
peci
�cat
ion
exam
ple
95of
214
Sum
mar
y
� Exe
cuta
ble
lang
uage
sen
cour
age
prec
isio
nan
dau
tom
atio
n
� The
lang
uage
shou
ldsu
ppor
tan
appr
opria
tem
odel
Mak
essp
eci�c
atio
nea
sy
� Str
ongl
ypa
ralle
lspr
ogra
mm
ing
lang
uage
sS
truc
ture
dvs
.ass
embl
yla
ngua
ges
Obj
ect-
orie
nted
mod
elan
dC
++
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
g96
of21
4
Tran
slat
ion
� Mod
elof
ten
unsu
ppor
ted
bya
stan
dard
lang
uage
(1)
Use
ast
anda
rdla
ngua
gean
yway
Man
yto
ols
avai
labl
eB
ut,c
aptu
res
mod
elun
natu
rally
(2)
Use
anap
plic
atio
n-sp
eci�c
lang
uage
Cap
ture
sm
odel
natu
rally
But
,not
man
yto
ols
avai
labl
e
(3)
Use
afr
ont-
end
lang
uage
Cap
ture
sm
odel
natu
rally
Man
yto
ols
avai
labl
eaf
ter
tran
slat
ing
toa
stan
dard
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gTr
ansl
atio
n97
of21
4
Out
line
� Fro
nt-e
ndla
ngua
gein
VH
DL
envi
ronm
ent
� Sta
tem
achi
netr
ansl
atio
n
� For
k-jo
intr
ansl
atio
n
� Exc
eptio
ntr
ansl
atio
n
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gTr
ansl
atio
n98
of21
4
Afr
ont-
end
lang
uage
ina
VH
DL
envi
ronm
ent
Too
l out
put
VH
DL
Spe
cCha
rts
Tra
nsla
tor
VH
DL
Sim
ulat
orD
ebug
erT
est−
gene
rato
rS
ynth
esis
to
ol
VH
DL
envi
ronm
ent
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gTr
ansl
atio
n99
of21
4
Sta
tem
achi
netr
ansl
atio
n
(a)
(b)
type
sta
te_t
ype
is (
P, Q
, R);
varia
ble
stat
e : s
tate
_typ
e :=
P;
loop
c
ase
(sta
te)
is
whe
n P
=>
<ac
tions
for
P>
if
(u)
then
sta
te :=
Q;
el
se if
(no
t u)
then
sta
te :=
R;
en
d if;
w
hen
Q =
>
<ac
tions
for
Q>
st
ate
:= P
;
whe
n R
=>
<
actio
ns fo
r R
>
stat
e :=
Q;
e
nd c
ase;
end
loop
;
P
Q
star
t
u
R
not u
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gTr
ansl
atio
n10
0of
214
For
k-jo
intr
ansl
atio
n
(a)
(b)
sign
al fo
rk, P
1_do
ne, P
2_do
ne :
bool
ean;
Mai
n: p
roce
ss
begi
n
s
tate
men
t1;
p
aral
lel
{
P1;
P2;
}
s
tate
men
t2;
..
.
Mai
n : p
roce
ssbe
gin
s
tate
men
t1;
fo
rk <
= tr
ue;
w
ait u
ntil
P1_
done
an
d P
2_do
ne;
s
tate
men
t2;
..
.
P1_
proc
ess
: pro
cess
begi
n
w
ait u
ntil
fork
;
P
1;
P
1_do
ne <
= tr
ue;
w
ait u
ntil
not f
ork;
P
1_do
ne <
= fa
lse;
end;
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gTr
ansl
atio
n10
1of
214
Exc
eptio
ntr
ansl
atio
n
even
t e :
T −
−>
S;
S_s
tart
:
(a)
(b)
(c)
T :
s
tate
men
t1;
s
tate
men
t2;
s
tate
men
t3;
S :
s
tate
men
t4;
s
tate
men
t5;
−−
Sst
atem
ent4
;st
atem
ent5
;
−−
Tst
atem
ent1
;if
(e)
g
oto
S_s
tart
;st
atem
ent2
;if
(e)
g
oto
S_s
tart
;st
atem
ent3
;
−−
TT
_loo
p : l
oop
s
tate
men
t;
if (
e)
exi
t T_l
oop;
sta
tem
ent2
;
if (
e)
exi
t T_l
oop;
s
tate
men
t3;
e
xit T
_loo
p;en
d lo
op;
−−
Sst
atem
ent4
;st
atem
ent5
;
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gTr
ansl
atio
n10
2of
214
Sum
mar
y
� The
perf
ects
tand
ard
lang
uage
may
neve
rex
ist
� No
stan
dard
lang
uage
supp
orts
allm
odel
s
� Usi
nga
fron
t-en
dla
ngua
geso
lves
the
prob
lem
Nat
ural
capt
ure
Larg
eba
seof
tool
san
dex
pert
ise
� Tran
slat
ors
are
sim
ple
Map
sch
arac
teris
tics
toex
istin
gco
nstr
ucts
Gen
erat
esw
ell-s
truc
ture
dan
dco
nsis
tent
outp
ut
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
g10
3of
214
Sys
tem
part
ition
ing
� Sys
tem
func
tiona
lity
isim
plem
ente
don
syst
emco
mpo
nent
sA
SIC
s,pr
oces
sors
,mem
orie
s,bu
ses
� Two
desi
gnta
sks:
Allo
cate
syst
emco
mpo
nent
sor
AS
ICco
nstr
aint
sP
artit
ion
func
tiona
lity
amon
gco
mpo
nent
s
� Con
stra
ints
Cos
t,pe
rfor
man
ce,s
ize,
pow
er
� Par
titio
ning
isa
cent
rals
yste
mde
sign
task
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g10
4of
214
Out
line
� Str
uctu
ralv
s.fu
nctio
nalp
artit
ioni
ng
� Nat
ural
vs.e
xecu
tabl
ela
ngua
gesp
eci�c
atio
ns
� Bas
icpa
rtiti
onin
gis
sues
and
algo
rithm
s
� Fun
ctio
nalp
artit
ioni
ngte
chni
ques
for
hard
war
e
� Har
dwar
e/so
ftwar
epa
rtiti
onin
g
� Fun
ctio
nalp
artit
ioni
ngte
chni
ques
for
softw
are
� Exp
lorin
gtr
adeo
ffsw
ithfu
nctio
nalp
artit
ioni
ng
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g10
5of
214
Str
uctu
ral
vs.
func
tiona
lpa
rtiti
onin
g
� Str
uctu
ral:
Impl
emen
tstr
uctu
re,t
hen
part
ition
� Fun
ctio
nal:
Par
titio
nfu
nctio
n,th
enim
plem
ent
Ena
bles
bette
rsi
ze/p
erfo
rman
cetr
adeo
ffsU
ses
few
erob
ject
s,be
tter
for
algo
rithm
s/hu
man
sP
erm
itsha
rdw
are/
softw
are
solu
tions
But
,it’s
hard
erth
angr
aph
part
ition
ing
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g10
6of
214
Nat
ural
vs.
exec
utab
lela
ngua
gesp
eci�c
atio
ns
� Alte
rnat
ive
met
hods
for
spec
ifyin
gfu
nctio
nalit
y
� Nat
ural
lang
uage
sco
mm
onin
prac
tice
� Exe
cuta
ble
lang
uage
sbe
com
ing
popu
lar
Aut
omat
edes
timat
ion/
part
ition
ing
expl
ores
solu
tions
Ear
lyve
ri�ca
tion
redu
ces
cost
lyla
tech
ange
sP
reci
sion
ease
sin
tegr
atio
n
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g10
7of
214
Bas
icpa
rtiti
onin
gis
sues
Gra
nula
rity
Out
put
Par
titio
ning
alg
orith
ms
Spe
cific
atio
n ab
stra
ctio
n−le
vel
Met
rics
and
estim
atio
ns
Obj
ectiv
e an
d cl
osen
ess
func
tions
Sys
tem
−co
mpo
nent
allo
catio
n
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g10
8of
214
Bas
icpa
rtiti
onin
gis
sues
(con
t.)
� Spe
ci�c
atio
n-ab
stra
ctio
nle
vel:
inpu
tde�
nitio
nJu
stin
dica
ting
the
lang
uage
isin
suf�c
ient
Abs
trac
tion-
leve
lind
icat
esam
ount
ofde
sign
alre
ady
done
e.g.
task
DF
G,t
asks
,CD
FG
,FS
MD
� Gra
nula
rity:
spec
i�cat
ions
ize
inea
chob
ject
Fin
egr
anul
arity
yiel
dsm
ore
poss
ible
desi
gns
Coa
rse
gran
ular
itybe
tter
for
com
puta
tion,
desi
gner
inte
ract
ion
e.g.
task
s,pr
oced
ures
,sta
tem
entb
lock
s,st
atem
ents
� Com
pone
ntal
loca
tion:
type
san
dnu
mbe
rse.
g.A
SIC
s,pr
oces
sors
,mem
orie
s,bu
ses
� Out
put:
form
atan
dus
ese.
g.ne
wsp
eci�c
atio
n,hi
nts
tosy
nthe
sis
tool
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g10
9of
214
Bas
icpa
rtiti
onin
gis
sues
(con
t.)
� Met
rics
and
estim
atio
ns:
"goo
d"pa
rtiti
onat
trib
utes
e.g.
cost
,spe
ed,p
ower
,si
ze,p
ins,
test
abili
ty,r
elia
bilit
yE
stim
ates
deriv
edfr
omqu
ick,
roug
him
plem
enta
tion
Spe
edan
dac
cura
cyar
eco
mpe
ting
goal
sof
estim
atio
n
� Obj
ectiv
ean
dcl
osen
ess
func
tions
Com
bine
sm
ultip
lem
etric
valu
esC
lose
ness
used
for
grou
ping
befo
reco
mpl
ete
part
ition
Wei
ghte
dsu
mco
mm
one.
g.
� 1
����������� �� 2
�� � ����� ��� �� 3
���� !�� ���
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g11
0of
214
Bas
icpa
rtiti
onin
gis
sues
(con
t.)
� Alg
orith
ms:
cont
rols
trat
egie
sse
ekin
gbe
stpa
rtiti
onC
onst
ruct
ive
crea
tes
part
ition
Itera
tive
impr
oves
part
ition
Key
isto
esca
pelo
calm
inim
umN
umbe
r of
mov
es
A
BC
ost
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g11
1of
214
Typi
cal
part
ition
ing-
sys
tem
con�
gura
tion
Inpu
tM
odel
Out
put
Est
imat
ors
Use
r in
terf
ace
Alg
orith
ms
Obj
ectiv
efu
nctio
n
Des
ign
feed
back
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g11
2of
214
Bas
icpa
rtiti
onin
gal
gorit
hms
� Clu
ster
ing
and
mul
ti-st
age
clus
terin
g[J
oh67
,LT
91]
� Gro
upm
igra
tion
(a.k
.a.m
in-c
utor
Ker
nigh
an/L
in)
[KL7
0,F
M82
]
� Rat
iocu
t[K
C91
]
� Sim
ulat
edan
neal
ing
[KG
V83
]
� Gen
etic
evol
utio
n
� Inte
ger
linea
rpr
ogra
mm
ing
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g11
3of
214
Hie
rarc
hica
lcl
uste
ring
� Con
stru
ctiv
eal
gorit
hmus
ing
clos
enes
sm
etric
s
� Ove
rvie
wG
roup
scl
oses
tobj
ects
Rec
ompu
tes
clos
enes
ses
Rep
eats
until
term
inat
ion
cond
ition
met
� Clu
ster
tree
mai
ntai
nshi
stor
yof
mer
ges
Cut
line
acro
ssth
etr
eede
�nes
apa
rtiti
on
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g11
4of
214
Hie
rarc
hica
lcl
uste
ring
algo
rithm
/*In
itial
ize
each
obje
ctas
agr
oup
*/fo
rea
ch
" # loop
$ #%" # & %& ' $ #
end
loop
/*C
ompu
tecl
osen
esse
sbe
twee
nob
ject
s*/
for
each
$ # loopfo
rea
ch
$ ( loop
) #+*(%
Com
pute
Clo
sene
ss(
$ #-,$ ( )en
dlo
open
dlo
op
/*M
erge
clos
esto
bjec
tsan
dre
com
pute
clos
enes
ses
*/w
hile
notT
erm
inat
e(
& )lo
op
$ # ,$ (% Find
Clo
sest
Obj
ects
(
& ,. )
& %&0/$ #/$ (' $ #(
for
each
$ 1 loop
) #( *1% Com
pute
Clo
sene
ss(
$ #( ,$ 1 )en
dlo
open
dlo
op
retu
rn
&
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g11
5of
214
Hie
rarc
hica
lcl
uste
ring
exam
ple
1
23
410
o
o
o
o
12
34
12
34
12
34
23
4
(a)
(b)
(c)
(d)
1o
oo
oo
oo
oo
oo
oo
oo
o
Avg
(10,
10)
= 1
0A
vg(1
5,25
) =
20
10
4
3025
1510
10
2o
3o
o
1o
10
20
1
3
4
102
o
o
o
o4
2o
3o
o
1o
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g11
6of
214
Sim
ulat
edan
neal
ing
� Itera
tive
algo
rithm
mod
eled
afte
rph
ysic
alan
neal
ing
proc
ess
� Ove
rvie
wS
tart
sw
ithin
itial
part
ition
and
tem
pera
ture
Slo
wly
decr
ease
ste
mpe
ratu
reF
orea
chte
mpe
ratu
re,g
ener
ates
rand
omm
oves
Acc
epts
any
mov
eth
atim
prov
esco
stA
ccep
tsso
me
bad
mov
es,l
ess
likel
yat
low
tem
pera
ture
s
� Res
ults
and
com
plex
ityde
pend
onte
mpe
ratu
rede
crea
sera
te
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g11
7of
214
Sim
ulat
edan
neal
ing
algo
rithm
243567 initi
alte
mpe
ratu
re
89:27 Ob
jfct(
; )w
hile
notF
roze
nlo
opw
hile
notE
quili
briu
mlo
op
; 243<24=2>@?3 7
Mov
e(
; )
89:2243<2 =2>@?37 Ob
jfct(
; 243<24=2> ?3 )
89:2789:2243<24=2>@?3 A89:2
if(A
ccep
t(
89:2CB24356
)
D Ran
dom
(0B 1))
then
; 7; 243<24=2>@?3
89:2789:2243<24=2>@?3
end
ifen
dlo
op
243567 Dec
reas
eTem
p(24356
)en
dlo
op
whe
re:
E 88362F 89:2CB2 356G75><F 1B3HIJKL L MNOG
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g11
8of
214
Fun
ctio
nal
part
ition
ing
for
hard
war
e:B
UD
� Goa
l:in
corp
orat
ear
ea/ti
me
into
synt
hesi
s[M
K90
]
� Clu
ster
sC
DF
Gop
erat
ions
into
data
path
mod
ules
� Clo
sene
ssm
etric
s:In
terc
onne
ctin
gw
ires
Con
curr
ency
Sha
red
hard
war
e
� Eac
hcl
uste
ring
corr
espo
nds
toan
allo
catio
n/sc
hedu
ling
� Sel
ects
clus
terin
gw
ithbe
star
ea/ti
me
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g11
9of
214
BU
Dex
ampl
e
+
=
−
<
−.38
.24
.7.2 0
0
(a)
(b)
(c)
x :=
a +
b;
if (a
= b
)
c :=
((x
− y
) <
z);
(bit−
wid
ths
= 4
)
+=
<−
ab
xy
z c
01
xco
nd
cond
star
t
finis
h
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g12
0of
214
BU
Dex
ampl
e(c
ont.)
=<
+−
.2
−.19
.12
+=
<−
AV
G(−
.19,
.12)
=
.035
+−
=<
+−
=<
+=
<−
+=
<−
17.5
3663
015
.826
411
16.4
2642
613
.826
359
(bes
t)
3 cl
uste
rs
Chi
p ar
ea A
Exp
ecte
d cy
cle
time
TO
bjfc
t = A
xT
(a)
(b)
(c)
Avg(−
.38,
0) =
Avg(0
,.24)
=
Chi
p Con
trol
ler
+−
<=
+−
=<
+−
, =
<+
−,
=,
<+
, −
, =
, <
Clu
ster
s
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g12
1of
214
Fun
ctio
nal
part
ition
ing
for
hard
war
e:A
part
y
� Ext
ends
BU
Dcl
uste
ring
tom
ultip
lest
ages
[LT
91]
Diff
eren
tclo
sene
ssm
etric
sfo
rea
chst
age
� Clo
sene
ssm
etric
s:C
ontr
oltr
ansf
erre
duct
ion
Dat
atr
ansf
erre
duct
ion
Har
dwar
esh
arin
g
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g12
2of
214A
part
yex
ampl
e
1
3
4 (a)
123
4
23
17
214
(b)
(c)
2o
o
o
o
oo
oo
23
41
oo
oo
34
12o
oo
12o
3o
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g12
3of
214
Har
dwar
e/so
ftwar
epa
rtiti
onin
g
� Com
bine
dha
rdw
are/
softw
are
syst
ems
are
com
mon
� Sof
twar
eis
chea
p,m
odi�a
ble,
and
quic
kto
desi
gn
� Har
dwar
eis
fast
� Spe
cial
algo
rithm
sar
ene
eded
tofa
vor
softw
are
� Pro
pose
dal
gorit
hms
Gre
edy
[GD
92]
Hill
clim
bing
[EH
B94
]B
inar
y-co
nstr
aint
sear
chw
ithhi
llcl
imbi
ng[V
GG
93]
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g12
4of
214
Fun
ctio
nal
part
ition
ing
for
syst
ems:
Vul
can,
Cos
yma
� Vul
can
[GD
90]I
Par
titio
nsC
DF
Gop
erat
ions
amon
gha
rdw
are
only
Gro
upm
igra
tion
and
sim
ulat
edan
neal
ing
algo
rithm
s
� Vul
can
II[G
D93
]P
artit
ions
oper
atio
nsam
ong
hard
war
e/so
ftwar
eA
rchi
tect
ure:
proc
esso
r,ha
rdw
are,
mem
ory,
bus
All
com
mun
icat
ion
thro
ugh
mem
ory
Use
sgr
eedy
algo
rithm
,ext
ract
sbe
havi
ors
from
hard
war
e
� Cos
yma
[EH
B94
]P
artit
ions
stat
emen
tblo
cks
amon
gha
rdw
are/
softw
are
Arc
hite
ctur
e:pr
oces
sor,
hard
war
e,m
emor
y,bu
sS
imul
ated
anne
alin
g,ex
trac
tsbe
havi
ors
from
softw
are
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g12
5of
214
Fun
ctio
nal
part
ition
ing
for
syst
ems:
Spe
cSyn
� Sol
ves
thre
epa
rtiti
onin
gpr
oble
ms
Beh
avio
rsto
proc
esso
rs/A
SIC
sV
aria
bles
tom
emor
ies
Com
mun
icat
ion
chan
nels
tobu
ses
� Use
sfa
stin
crem
enta
l-upd
ate
estim
ator
s
� Cov
ers
both
hard
war
ean
dha
rdw
are/
softw
are
part
ition
ing
[GV
N94
,VG
92]
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g12
6of
214
Exp
lorin
gtr
adeo
ffsw
ithfu
nctio
nal
part
ition
ing
� Eac
hlin
ere
pres
ents
adi
ffere
ntve
ndor
’sch
ipse
t
� Eac
hpo
intr
epre
sent
san
allo
catio
nan
dpa
rtiti
on
� Man
yde
sign
squ
ickl
yex
amin
ed
0.0
20.0P 40
.0P 60.0P 80
.0P 100.
0P 120.
0P 140.
0P
cost
(do
llars
)Q
200.
0
400.
0
600.
0
800.
0
1000
.0
1200
.0
performance (microseconds)
chip
set1
chip
set2
chip
set3
AB
C
D
AB
C
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g12
7of
214
Sum
mar
y
� Par
titio
ning
heav
ilyin
uen
cesd
esig
nqu
ality
� Fun
ctio
nalp
artit
ioni
ngis
nece
ssar
y
� Exe
cuta
ble
spec
i�cat
ion
enab
les:
Aut
omat
ion
Exp
lora
tion
Doc
umen
tatio
n
� Var
iety
ofal
gorit
hms
exis
t
� Var
iety
ofte
chni
ques
exis
tfor
diffe
rent
appl
icat
ions
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gS
yste
mpa
rtiti
onin
g12
8of
214Fut
ure
dire
ctio
ns
� Met
rics
from
real
desi
gnto
guid
epa
rtiti
onin
g
� Com
paris
onof
func
tiona
lpar
titio
ning
algo
rithm
s
� Impa
ctof
met
ricse
lect
ions
and
orde
rings
� Impa
ctof
ofgr
anul
arity
onpa
rtiti
onqu
ality
� Exp
loita
tion
ofre
gula
rity
inpa
rtiti
onin
g
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
g12
9of
214
Est
imat
ion
� Est
imat
esal
low
Eva
luat
ion
ofde
sign
qual
ityD
esig
nsp
ace
expl
orat
ion
� Des
ign
mod
elR
epre
sent
sde
gree
ofde
sign
deta
ilco
mpu
ted
Sim
ple
vs.
com
plex
mod
els
� Issu
esfo
res
timat
ion
Acc
urac
yS
peed
Fid
elity
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n13
0of
214
Out
line
� Acc
urac
yve
rsus
spee
d
� Fid
elity
� Qua
lity
met
rics
Per
form
ance
met
rics
Har
dwar
ean
dso
ftwar
eco
stm
etric
s
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n13
1of
214
Acc
urac
yvs
.S
peed
� Acc
urac
y:di
ffere
nce
betw
een
estim
ated
and
actu
alva
lue
R S
1
TU V� W�TX
� W�U
X� W�
� Spe
ed:
com
puta
tion
time
for
obta
inin
ges
timat
e
Act
ual D
esig
n
Com
puta
tion
Tim
e
Sim
ple
Mod
el
Est
imat
ion
Err
or
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n13
2of
214
Fid
elity
� Est
imat
esm
ustp
redi
ctqu
ality
met
rics
for
diffe
rent
desi
gnal
tern
ativ
es
� Fid
elity
:%
ofco
rrec
tpre
dict
ions
for
pairs
ofde
sign
impl
emen
tatio
ns
� Hig
her
�del
ity
YZ
corr
ectd
ecis
ions
base
don
estim
ates
AB
C
estim
ate
Des
ign
poin
ts
Met
ricE
(A)
> E
(B),
M(A
) <
M(B
)
E(B
) <
E(C
), M
(B)
> M
(C)
E(A
) <
E(C
), M
(A)
< M
(C)
(A, B
) =
(B, C
) =
(A, C
) =
= 3
3 %
Fid
elity
mea
sure
d
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n13
3of
214
Qua
lity
met
rics
� Per
form
ance
Met
rics
Clo
ckcy
cle,
cont
rols
teps
,exe
cutio
ntim
e,co
mm
unic
atio
nra
tes
� Cos
tMet
rics
Har
dwar
e:
man
ufac
turin
gco
st(a
rea)
,pac
kagi
ngco
st(p
in)
Sof
twar
e:
prog
ram
size
,dat
am
emor
ysi
ze
� Oth
erm
etric
sP
ower
,tes
tabi
lity,
desi
gntim
e,tim
eto
mar
ket
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n13
4of
214
Har
dwar
ede
sign
mod
el
RF
Con
trol
L
ogic
Mem
ory
Mux
es
Reg
iste
rs/
Reg
iste
r F
iles
Mux
es
Fun
ctio
nal
Uni
tsF
U
Dat
apat
hC
ontr
ol U
nit
Sta
tus
bits
Con
trol
Reg
iste
r
Sta
tus
Reg
iste
r
Sta
te R
eg.
AR
DR
R1
R2
n 1 n6
n5
n2
n3
n 4
p 3
p 2
p 1
Nex
t−S
tate
Log
ic
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n13
5of
214
Clo
ckcy
cle
estim
atio
n
� Clo
ckcy
cle
dete
rmin
es:
Res
ourc
es,e
xecu
tion
time
� Det
erm
inin
gcl
ock
cycl
eD
esig
ner
spec
i�ed
[PK
89,M
K90
]M
axim
umde
lay
ofan
yfu
nctio
nalu
nit[
PP
M86
,JM
P88
]C
lock
utili
zatio
n[N
G92
]
Clo
ck C
ycle
Exe
c. T
ime
Res
ourc
es
: 380
ns
: 380
ns
+
+
+
+
150
150
80
8080
80
Clo
ck C
ycle
Exe
c.
Tim
e R
esou
rces
: 150
ns
: 600
ns
+15
0
150
80 +80
+80 +
80
Clo
ck C
ycle
Exe
c.
Tim
e R
esou
rces
: 80
ns: 4
00 n
s
+15
0
150
80 +80
+80 +
80x
xxx x
x
: 2 x
, 4 +
: 1 x
, 1 +
: 1 x
, 1 +
i1i2
i3i4
i5i6
i1i2
i3i4
i5i6
i1i2
i3i4
i5i6
o2o1
o1
o2o1
o2
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n13
6of
214
Clo
cksl
ack
and
utili
zatio
n
[ Sla
ck:
port
ion
ofcl
ock
cycl
efo
rw
hich
FU
isid
le
\]�^_`a _]`cbd0ef Sag h�i]�^ja d eflk_]`m+n _]`fTh i
] ^ja d0ef
[ Ave
rage
slac
k:
FU
slac
kav
erag
edov
eral
lope
ratio
ns
^oi\] ^_`a _]`fSprq es�t__
uva d0ef n\] ^_`a _]`cbd efw
p q et__uva d0ef
[ Clo
ckut
iliza
tion
:%
ofcl
ock
cycl
eut
ilize
dfo
rco
mpu
tatio
ns
udx] xzy^dx t{a _]`fS 1
T^oi\] ^_`a _]`f
_]`
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n13
7of
214
Clo
ckut
iliza
tion
1 x
CLK
2 x
CLK
3 x
CLK
5010
015
0tim
e (n
s)
Sla
ck
occu
r(x)
=6
occu
r(−
)=2
occu
r(+
)=2
Fun
ctio
nal u
nit d
elay
num
ber
of
oper
atio
ns
Clo
ck =
65
ns
=+
+x
−+
6x32
2x9
2 x
17
=24
.4 n
sav
e_sl
ack(
65 n
s)6
+
2
+
2
utili
zatio
n(65
ns)
=
1 −
(24
.4 /
65.
0) =
62
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n13
8of
214S
lack
min
imiz
atio
nal
gorit
hm
Clo
ckS
lack
Min
imiz
atio
n[N
G92
]C
ompu
tera
nge
:
|}~@��� ,|}~ �e��
Com
pute
occu
rren
ces
:
�||��� ����
�����e} e����e ��� 0/*
Exa
min
eea
chcl
ock
cycl
ein
rang
e*/
for
|}~ �e��� |}~�
|}~@��� loo
p
for
allo
pera
tion
type
s
����p lo
opC
ompu
tesl
ack
�} �|~� |}~������
end
loop
Com
pute
aver
age
slac
k:
����} �|~�|}~�
Com
pute
utili
zatio
n:
��e} e����e ��� |}~�
/*If
high
estu
tiliz
atio
n*/
if��e} e����e ��� |}~�4������e} e����e ��
then
�����e} e����e �����e} e����e ��� |}~�
�����e} e����e ��|}~ �|}~
end
ifen
dlo
op |}~� � �� ������e} e����e��|}~
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n13
9of
214
Exe
cutio
ntim
evs
.cl
ock
utili
zatio
nS
econ
dor
der
diffe
rent
iale
quat
ion
exam
ple
� Clo
ckw
ithhi
ghes
tutil
izat
ion
resu
ltsin
bette
rex
ecut
ion
times
Clo
ckcy
cle
vs.
Util
izat
ion
Exe
cutio
ntim
evs
.ut
iliza
tion
0.0
20.0�
40.0�
60.0�
80.0�
100.
0�
Util
izat
ion
(%)
0.0
20.0
40.0
60.0
80.0
100.
0
120.
0
140.
0
160.
0
Clock cycle (ns) �
56 n
s
92%
0.0
20.0�
40.0�
60.0�
80.0�
100.
0�
Util
izat
ion
(%)
400.
0
600.
0
800.
0
1000
.0
1200
.0
Execution time (ns) �
92%
560
ns
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n14
0of
214
Con
trol
step
ses
timat
ion
� Ope
ratio
nsin
the
spec
i�cat
iona
ssig
ned
toco
ntro
lste
p
� Num
ber
ofco
ntro
lst
eps
dete
rmin
es:
Exe
cutio
ntim
eof
desi
gnC
ompl
exity
ofco
ntro
luni
t
� Sch
edul
ing
Gra
nula
rity
isop
erat
ions
ina
data
ow
grap
hC
ompu
tatio
nally
expe
nsiv
e
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n14
1of
214
Ope
rato
r-us
em
etho
d
� Gra
nula
rity
isst
atem
ents
insp
eci�c
atio
n
� Fas
ter
than
sche
dulin
g,av
erag
eer
ror
13%
u6 :=
u −
u4
u :=
u6
− u
5
add:
(1/
1)*1
= 1
add:
(1/
1)*1
= 1
mul
t: (4
/2)*
4= 8
mul
t: (2
/2)*
4= 4
max
imum
mac
ro−
node
cont
rol s
teps
add
mul
tsu
b
1 2 1
1 4 1
cloc
ks(t
) inu
m(t
) it i u1
:= u
x d
x ;
u2 :=
5 x
w ;
u3 :=
3 x
y ;
y1 :=
i x
dx
;w
:=
w +
dx
;u4
:= u
1 x
u2 ;
u5 :=
dx
x u3
;y
:=
y +
y1
;u6
:= u
− u
4 ;
u :
= u
6 −
u5
;
u1 :=
u x
dx
u2 :=
5 x
w
u3 :=
3 x
yy1
:= i
x d
x w
:=
w +
dx
u4 :=
u1
x u2
u5 :=
dx
x u3
y :=
y +
y1
max
(1
, 8)
= 8
max
(1
, 4)
= 4
sub:
(1/
1)*1
= 1
max
(1
) =
1
Est
imat
ed t
otal
con
trol
ste
ps
= 1
4
sub:
(1/
1)*1
= 1
max
(1
) =
1y
:= y
+ y
1
u6 :=
u −
u4
u :=
u6
−u5
w :=
w +
dx
u1 :=
u x
dx
u2 :=
5 x
w
u3 :=
3 x
y
y1 :=
i x
dx
u4 :=
u1
x u2
u5 :=
dx
x u3
n 1 n2
n3
n4
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n14
2of
214
Bra
nchi
ngin
beha
vior
s
� Con
trol
step
sm
aybe
shar
edac
ross
excl
usiv
ebr
anch
essh
arin
gsc
hedu
le:
few
erst
ates
,sta
tus
regi
ster
non-
shar
ing
sche
dule
:m
ore
stat
es,n
ost
atus
regi
ster
s
o 1 o 2
o 3o 6 o 7
o 8
o 4 o 5
B 1
BB
B 4
23
o 1 o 2
o 3 o 4 o 5
o 6 o 7
o 8
s 1 s 2 s 3 s 4 s 5 s 6
o 1 o 2
o 3 o 4 o 5
o 6 o 7
o 8
s 1 s 2 s 3 s 4 s 5
s 6 s 7
s 8
(a)
(b)
(c)
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n14
3of
214
Exe
cutio
ntim
ees
timat
ion
� Ave
rage
star
tto
�nis
htim
eof
beha
vior
� Str
aigh
t-lin
eco
debe
havi
ors
���_�xz �¡ ¢£ ¤_¥� �¦¥¡ ¢£+§ _¨©
� Beh
avio
rw
ithbr
anch
ing
Est
imat
eex
ecut
ion
time
for
each
basi
cbl
ock
Cre
ate
cont
rol
owgr
aph
from
basi
cbl
ocks
Det
erm
ine
bran
chin
gpr
obab
ilitie
sF
orm
ulat
eeq
uatio
nsfo
rno
defr
eque
ncie
sS
olve
seto
fequ
atio
ns
���_�xz �¡ ¢£ ¤q ª¬«����_�xz �¡ ®°¯£ §± v�²¡ ® ¯£
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n14
4of
214Pro
babi
lity-
base
d o
wan
alys
is
A :=
A +
1;
for
I in
1 to
10
loop
B :=
B +
1;
C :=
C −
A;
if (
D >
A )
then
D
:= D
+ 2
;
el
se
D :=
D +
3;
end
if
E :=
D *
2;
end
loop
;
B :=
B *
A;
C :=
3
A :=
A +
1;
(I =
< 1
0)(I
> 1
0)
D>
AD
<=
A
D :=
D +
2;
B :=
B +
1 ;
C :=
C −
A;
E :=
D *
2 ;
B: =
B *
A;
C :=
3;
D :=
D +
3;
V1
V2
V3
V4
V5
V6
e 52
e 56
e 35e 45
e 12
24e
0.5
0.5
0.9
0.1
e 23
S
B B
B
B B
B
1 2
34
5 6
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n14
5of
214Pro
babi
lity-
base
d o
wan
alys
is
� Flo
weq
uatio
ns:
±�³�²¡ ´£¤ 1µ
0
±�³�²¡�¶ 1
£ ¤
1
µ 0§± ³�²¡ ´£
±�³�²¡�¶ 2
£ ¤
1
µ 0§± ³�²¡�¶ 1
£¸·0
µ 9§±�³�²¡�¶ 5
£
±�³�²¡�¶ 3
£ ¤
0
µ 5§± ³�²¡�¶ 2
£
±�³�²¡�¶ 4
£ ¤
0
µ 5§± ³�²¡�¶ 2£
±�³�²¡�¶ 5
£ ¤
1
µ 0§± ³�²¡�¶ 3£¸·
1
µ 0§±�³�²¡�¶ 4
£
±�³�²¡�¶ 6
£ ¤
0
µ 1§± ³�²¡�¶ 5
£
� Nod
eex
ecut
ion
freq
uenc
ies:
±�³�²¡�¶ 1
£ ¤1µ 0
±�³�²¡�¶ 2
£ ¤
10
µ 0
±�³�²¡�¶ 3
£ ¤5
µ 0
±�³�²¡�¶ 4
£ ¤
5
µ 0
±�³�²¡�¶ 5£ ¤
10
µ 0
±�³�²¡�¶ 6
£ ¤
1
µ 0
� Can
beus
edto
estim
ate
num
ber
ofac
cess
esto
varia
bles
,cha
nnel
sor
proc
edur
es
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n14
6of
214
Com
mun
icat
ion
rate
s
time
(ns)
8 8
8 8
8 8
8
200
400
600
800
1000
bits
sen
t ove
r ch
anne
l C
� Ave
rage
chan
nel
rate
rate
ofda
tatr
ansf
erov
erlif
etim
eof
beha
vior
¹¶�³¹� �¡ º£ ¤
56
ª ¯ � �
1000
��¤ 56
»®¼¥
� Pea
kch
anne
lra
tera
teof
data
tran
sfer
ofsi
ngle
mes
sage
¦�¹© ³¹� �¡ º£ ¤
8
ª ¯ � �
100��
¤ 80
»®¼¥
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
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stim
atio
n14
7of
214Com
mun
icat
ion
rate
estim
atio
n
� Tota
lbeh
avio
rex
ecut
ion
time
cons
ists
ofC
ompu
tatio
ntim
e,_½ ¦�¾z �¡ ¿£ ,o
btai
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ow
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e,_½ �¾z �¡ ¿ÁÀº£¤¹__�¥¥¡ ¿ÁÀº£ §Â �¨ ¹Ã¡ º£
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sfer
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l,
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nnel
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age
rate
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UC
Irvi
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199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n14
8of
214
Are
aes
timat
ion
� Two
task
s:D
eter
min
ing
num
ber
and
type
ofco
mpo
nent
sre
quire
dE
stim
atin
gco
mpo
nent
size
for
asp
eci�c
tech
nolo
gy(F
SM
D,g
ate
arra
yset
c.)
� Beh
avio
rim
plem
ente
das
aF
SM
D(�
nite
stat
em
achi
new
ithda
tapa
th)
Dat
apat
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mpo
nent
s:re
gist
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func
tiona
luni
ts,m
ultip
lexe
rs/b
uses
Con
trol
unit:
stat
ere
gist
er,c
ontr
ollo
gic,
next
-sta
telo
gic
� We
will
disc
uss
Dat
apat
hco
mpo
nent
estim
atio
nC
ontr
olun
ites
timat
ion
Layo
utar
eafo
ra
cust
omim
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enta
tion
UC
Irvi
neC
opyr
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(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
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9of
214
Cliq
ue-p
artit
ion
ing
� Com
mon
lyus
edfo
rde
term
inin
gda
tapa
thco
mpo
nent
s
� Let
ÄÆÅÇ ÈÊÉËÌ be
agr
aph,
È
and
Ë are
seto
fver
tices
and
edge
s
� Cliq
ueis
aco
mpl
ete
subg
raph
of
Ä
� Cliq
ue-p
artit
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ngdi
vide
sth
eve
rtic
esin
toa
min
imal
num
ber
ofcl
ique
sea
chve
rtex
inex
actly
one
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ue
� One
heur
istic
:m
axim
umnu
mbe
rof
com
mon
neig
hbor
s[C
S86
]Tw
ono
des
with
max
imum
num
ber
ofco
mm
onne
ighb
ors
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mer
ged
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two
node
sre
plac
edby
edge
sto
mer
ged
node
Pro
cess
repe
ated
tilln
om
ore
node
sca
nbe
mer
ged
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n15
0of
214
Cliq
ue-p
artit
ion
ing
Cliq
ues:
{v ,
v ,
v
}1
34
{v ,
v
}2
5
= =
v 1
v 3v 4
v 5
v 2
s13
4
s25
s13
4s
25
v 1
v 3v 4
v 5
v 2
s1
s2
s3
s4
s5
1 0
0
0
1
1
e’ 1,3
e’ 2,5
e’ 4,5
e’ 3,4
e’ 1,4
e’ 2,3
Com
mon
n
eigh
bors
Edg
e
v 1
v 3v 4
v 5
v 2
s13
4
s5
s2
0
e’ 2,5
Com
mon
n
eigh
bors
Edg
e
v 1
v 3v 4
v 5
v 2
s4
s5
s2
s13
e’ 4,5
0
e’ 2,5
0
e’ 13,4
0
Com
mon
n
eigh
bors
Edg
e
UC
Irvi
neC
opyr
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(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n15
1of
214
Sto
rage
-uni
tes
timat
ion
� Var
iabl
esno
tuse
dco
ncur
rent
lym
aybe
map
ped
sam
est
orag
e-un
it
� Tous
ecl
ique
-par
titio
ning
,co
nstr
ucta
grap
hw
here
Eac
hva
riabl
ere
pres
ente
dby
ave
rtex
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iabl
esw
ithno
n-ov
erla
ppin
glif
etim
esha
vean
edge
betw
een]
thei
rve
rtic
es
v
v
v
vv
v
vv
v
vv
10
8
1
92
7
113
5
46
= = = = =
1 3 4 5
R
2R R R R
10
{v ,
v }
{v ,
v ,
v
}9
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v
}4
576
8
11{v
,
v }
1{v
}23
Cliq
ues
Sto
rage
uni
t
v 1v 2
v 3v 4
v 5v 6
v 7v 8
v 9v 10
v 11
s 1 s 2 s 3 s 4s 0 s 5
UC
Irvi
neC
opyr
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(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n15
2of
214
Fun
ctio
nal-u
nit
and
inte
rcon
nect
-uni
tes
timat
ion
� Cliq
ue-p
artit
ioni
ngca
nbe
appl
ied
� For
dete
rmin
ing
the
num
ber
ofF
U’s
requ
ired,
cons
truc
tagr
aph
whe
reE
ach
oper
atio
nin
beha
vior
repr
esen
ted
bya
vert
exE
dge
conn
ects
two
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ices
ifC
orre
spon
ding
oper
atio
nsas
sign
eddi
ffere
ntco
ntro
lste
psT
here
exis
tsan
FU
that
can
impl
emen
tbot
hop
erat
ions
� For
dete
rmin
ing
the
num
ber
ofin
terc
onne
ctun
its,c
onst
ruct
agr
aph
whe
reE
ach
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ectio
nbe
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oun
itsis
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esen
ted
bya
vert
exE
dge
conn
ects
two
vert
ices
ifco
rres
pond
ing
conn
ectio
nsno
tuse
din
sam
eco
ntro
lste
p
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n15
3of
214
Com
putin
gda
tapa
thar
ea
� Bit-
slic
edda
tapa
th
Í ª ¯ �¤Î§� ³¡ Ï¿£
Ð ��¤����
����Ñ��� ��|~§
Ò
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B
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Bit
slic
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outin
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l
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t
rtD
atap
ath
com
pone
nts
Con
trol
li
nes
UC
Irvi
neC
opyr
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(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n15
4of
214
Pin
estim
atio
n
� Num
ber
ofw
ires
atbe
havi
or’s
boun
dary
depe
nds
onG
loba
ldat
aP
orta
cces
sed
Com
mun
icat
ion
chan
nels
used
Pro
cedu
reca
lls
chan
nel c
h2
chan
nel c
h1
proc
ess
Fac
toria
l (
ch1,
ch2
)
i
n c
hann
el c
h1 ;
out
cha
nnel
ch2
;{
rec
eive
(ch
1, M
);
/*
com
pute
fact
oria
l */
.
......
......
...
sen
d (c
h2, r
esul
t);
}
port
F
port
G
proc
ess
Mai
n (
ch1
, ch2
)
o
ut c
hann
el c
h1 ;
in
cha
nnel
ch2
;{
sen
d (c
h1,
N);
p
ortF
<=
por
tG +
4;
..
......
....
r
ecei
ve (
ch2,
Res
ult)
;}
varia
ble
N :
inte
ger;
varia
ble
X :
bit_
vect
or(1
5 do
wnt
o 0)
;
proc
edur
e S
UM
(A, B
, OU
T)
isbe
gin
...
.en
d S
UM
;
UC
Irvi
neC
opyr
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(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n15
5of
214
Sof
twar
ees
timat
ion
mod
els
Spe
cific
atio
n
Com
pile
toge
neric
inst
ruct
ions
G
ener
icin
stru
ctio
ns
Est
imat
or
Sof
twar
e M
etric
s
8086
inst
ruct
ion
timin
g &
siz
ein
form
atio
n
MIP
Sin
stru
ctio
ntim
ing
& s
ize
info
rmat
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6
8000
inst
ruct
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timin
g &
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ein
form
atio
n
te
chno
logy
fil
es fo
r ta
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pro
cess
ors
Spe
cific
atio
n
Com
pile
to
808
6 C
ompi
le
to 6
8000
Com
pile
to
MIP
S
8
086
inst
ruct
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6
8000
in
stru
ctio
ns
MIP
S
inst
ruct
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680
00E
stim
ator
80
86E
stim
ator
M
IPS
Est
imat
or
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twar
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etric
s
8086
inst
ruct
ion
timin
g &
siz
ein
form
atio
n
MIP
Sin
stru
ctio
ntim
ing
& s
ize
info
rmat
ion
6
8000
inst
ruct
ion
timin
g &
siz
ein
form
atio
n
Pro
cess
or s
peci
fic m
odel
Gen
eric
m
odel
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n15
6of
214
Der
ivin
gpr
oces
sor
tech
nolo
gy�le
s
Ge
ne
ric
inst
ruct
ion
tech
no
log
y fil
e fo
r 6
80
20
tech
no
log
y fil
e fo
r 8
08
6
68
02
0 in
stru
ctio
ns
80
86
in
stru
ctio
ns
cloc
ksby
tes
byte
scl
ocks
dm
em
3
=
dm
em
1 +
dm
em
2
size
ge
ne
ric
inst
ruct
ion
...
...
exe
cutio
n
tim
e
dm
em
3 =
dm
em
1 +
dm
em
23
5 c
lock
s 1
0
byt
es
ge
ne
ric
inst
ruct
ion
...
...
exe
cutio
n
tim
esi
ze
dm
em
3
= d
me
m1
+
dm
em
22
2 c
lock
s
6b
yte
s
mo
v a
x, w
ord
ptr
[bp
+o
ffse
t1]
(10
)
3 a
dd
ax,
wo
rd p
tr[b
p+
off
set2
]
(9
+ E
A1
)
4 m
ov
wo
rd p
tr[b
p+
off
set3
], a
x
(1
0)
3
inst
ruct
ion
inst
ruct
ion
mo
v a
6@
(off
set1
), d
0
(
7)
2 a
dd
a6
@(o
ffse
t2),
d0
(2
+ E
A2
)
2 m
ov
d0
, a
6@
(off
set3
)
(5
)
2
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n15
7of
214
Sof
twar
ees
timat
ion
Õ Pro
gram
exec
utio
ntim
eC
reat
eba
sic
bloc
ksan
dco
mpi
lein
toge
neric
inst
ruct
ions
Est
imat
eex
ecut
ion
time
ofba
sic
bloc
ksP
erfo
rmpr
obab
ility
-bas
ed o
wan
alys
isC
ompu
teex
ecut
ion
time
ofth
een
tire
beha
vior
:
Ö×ÖØÙÚzÛÖÜ ÝÞàßá�âÜ ã ä¬åæ
çÖ×ÖØÙÚzÛÖÜ èÆéÞ âê�ëÖìÜ è éÞÞ
á acco
unts
for
com
pile
rop
timiz
atio
ns
Õ Pro
gram
mem
ory
size
íëîïðÚzñÖÜ ÝÞ ßã òæ
óÚzôðÙ ëðÚzñÖÜïÞ
Õ Dat
am
emor
ysi
ze
õ�öÙ öðÚzñÖÜ ÝÞ ßã ÷ æ
øõ�öÙ öðÚzñÖÜ õÞ
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gE
stim
atio
n15
8of
214Sum
mar
yan
dfu
ture
dire
ctio
ns
Õ We
desc
ribed
met
hods
for
estim
atin
g:P
erfo
rman
cem
etric
s:cl
ock,
cont
rols
teps
,exe
cutio
ntim
e,co
mm
unic
atio
nra
tes
Cos
tmet
rics:
desi
gnar
ea,p
ins,
prog
ram
and
data
mem
ory
size
Õ Fut
ure
dire
ctio
ns:
Inco
rpor
atin
gsy
nthe
sis/
com
pila
tion
optim
izat
ions
New
met
rics
for
test
abili
ty,p
ower
,in
tegr
atio
nco
st,e
tc.
New
arch
itect
ural
feat
ures
for
the
estim
atio
nm
odel
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
g15
9of
214
Re�
nem
ent
Õ Fun
ctio
nalo
bjec
tsar
egr
oupe
dan
dm
appe
dto
syst
emco
mpo
nent
sF
unct
iona
lobj
ects
:va
riabl
es,b
ehav
iors
,and
chan
nels
Sys
tem
com
pone
nts:
mem
orie
s,ch
ips
orpr
oces
sors
,and
buse
s
Õ Re�
nem
ent
isup
date
ofsp
eci�c
atio
nto
re e
ctm
appi
ng
Õ Nee
dfo
rre
�nem
ent
Mak
essp
eci�c
atio
nco
nsis
tent
Ena
bles
sim
ulat
ion
ofsp
eci�c
atio
nG
ener
ate
inpu
tfor
synt
hesi
s,co
mpi
latio
nan
dve
ri�ca
tion
tool
s
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t16
0of
214
Out
line
Õ Re�
ning
varia
ble
grou
ps
Õ Cha
nnel
re�n
emen
t
Õ Res
olvi
ngac
cess
con
icts
Õ Re�
ning
inco
mpa
tible
inte
rfac
es
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t16
1of
214
Re�
ning
varia
ble
grou
ps
Õ Gro
upof
varia
bles
map
ped
toa
mem
ory
Õ Var
iabl
efo
ldin
g:Im
plem
entin
gea
chva
riabl
ein
am
emor
yw
itha
�xed
wor
dsi
ze
Õ Mem
ory
addr
ess
tran
slat
ion
Ass
ignm
ento
fadd
ress
esto
each
varia
ble
ingr
oup
Upd
ate
refe
renc
esto
varia
ble
byac
cess
esto
mem
ory
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t16
2of
214
Var
iabl
efo
ldin
g
varia
ble
A :
bit_
vect
or(
3 d
ownt
o 0)
;va
riabl
e B
: b
it_ve
ctor
(15
dow
nto
0) ;
varia
ble
C :
bit_
vect
or(1
1 do
wnt
o 0)
;va
riabl
e D
: b
it_ve
ctor
(11
dow
nto
0) ;
70
C(1
1 do
wnt
o 8)
D(1
1 do
wnt
o 6)
B(1
5 do
wnt
o 8)
C(
7 d
ownt
o 0)
D(
5 d
ownt
o 0)
B(
7 d
ownt
o 0)
A(
3 d
ownt
o 0)
... ...
8−bi
t M
emor
y
...
118
70
7..4
4x1
3..0
to v
aria
ble
C in
mem
ory
116
50
6x1
5..0
to v
aria
ble
D in
mem
ory
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
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men
t16
3of
214M
emor
yad
dres
str
ansl
atio
n
varia
ble
J :
inte
ger
:= 1
00;
varia
ble
K :
inte
ger
:= 0
;va
riabl
e M
EM
: In
tArr
ay (
255
dow
nto
0);
....
ME
M(K
+ 1
00)
:= 3
;X
:= M
EM
(136
);M
EM
(J)
:= X
;...
.fo
r J
in
100
to 1
63 lo
op
SU
M :=
SU
M +
ME
M(J
);en
d lo
op;
....
varia
ble
J, K
: in
tege
r :=
0;
varia
ble
V :
IntA
rray
(63
dow
nto
0);
....
V(K
) :=
3;
X :=
V(3
6);
V(J
) :=
X;
....
for
J i
n 0
to 6
3 lo
op
SU
M :=
SU
M +
V(J
);en
d lo
op;
....
varia
ble
J, K
: in
tege
r :=
0;
varia
ble
ME
M :
IntA
rray
(25
5 do
wnt
o 0)
;...
.M
EM
(K +
100)
:= 3
;X
:= M
EM
(136
);M
EM
(J+
100)
:= X
;...
.fo
r J
in 0
to 6
3 lo
op
SU
M :=
SU
M +
ME
M(J
+10
0);
end
loop
;...
.
V (
63 d
ownt
o 0)
ME
M(1
63 d
ownt
o 10
0)
Orig
inal
spe
cific
atio
nA
ssig
ning
add
ress
es to
V
Ref
ined
spe
cific
atio
n
R
efin
ed s
peci
ficat
ion
with
out o
ffset
s fo
r in
dex
J
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t16
4of
214
Re�
ning
chan
nel
grou
ps
Õ Cha
nnel
sar
evi
rtua
lent
ities
over
whi
chm
essa
ges
are
tran
sfer
red
Õ Bus
isa
phys
ical
med
ium
that
impl
emen
tsgr
oups
ofch
anne
ls
Õ Bus
cons
ists
of:
wire
sre
pres
entin
gda
taan
dco
ntro
llin
espr
otoc
olde
�nin
gse
quen
ceof
assi
gnm
ents
toda
taan
dco
ntro
llin
es
Õ Two
re�n
emen
ttask
sB
usge
nera
tion:
dete
rmin
ing
busw
idth
i.e.
num
ber
ofda
talin
esP
roto
colg
ener
atio
n:sp
ecify
ing
mec
hani
smof
tran
sfer
over
bus
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t16
5of
214
Cha
ract
eriz
ing
com
mun
icat
ion
chan
nels
Õ For
agi
ven
beha
vior
ù that
send
sda
taov
erch
anne
lú ,
Mes
sage
size
,è Ú Ù ðÜ ûÞ
:nu
mbe
rof
bits
inea
chm
essa
geA
cces
ses
,
öØØÖððÖðÜ üÁýûÞ
:nu
mbe
rof
times
ü tran
sfer
sda
taov
er
û
Ave
rage
rate
,öþÖëöÙ ÖÜ ûÞ :
rate
ofda
tatr
ansf
erof
û over
lifet
ime
ofbe
havi
orP
eak
rate
,
íÖöÿ ëöÙ ÖÜ ûÞ :
rate
oftr
ansf
erof
sing
lem
essa
ge
t=0
88
chan
nel
X
X1
X2
8 X3
100
200
300
400
time
(ns)
è Ú Ù ðÜ ûÞ ß
8bi
ts
öþÖëöÙ ÖÜ ûÞ ß
24
ä é � �
400
��ß
60
�è Ú Ù ð� ð
íÖöÿ ëöÙ ÖÜ ûÞ ß
8
ä é � �
100
��ß
80
�è Ú Ù ð� ð
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t16
6of
214
Cha
ract
eriz
ing
buse
s
Õ For
agi
ven
bus
� ,B
usw
idth
,è��ð�Úõ ÙÜ ÝÞ :
num
ber
ofda
talin
esin
ÝP
roto
col
dela
y,
íëîÙõ Ö ö�Ü ÝÞ
:de
lay
for
sing
lem
essa
getr
ansf
erov
erbu
sA
vera
gera
te,öþ
ÖëöÙ ÖÜ ÝÞ :
rate
ofda
tatr
ansf
erov
er
Ý over
lifet
ime
ofsy
stem
Pea
kra
te,
íÖöÿ ëöÙ ÖÜ ÝÞ :
max
imum
rate
oftr
ansf
erof
data
onbu
s
íÖöÿ ëöÙ ÖÜ ûÞ ß
è��ð�Úõ ÙÜ ÝÞ
íëîÙõ Ö ö�Ü ÝÞ
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t16
7of
214
Det
erm
inin
gbu
sra
tes
Õ Idle
slot
sof
ach
anne
luse
dfo
rm
essa
ges
ofot
her
chan
nels
Õ Toen
sure
that
chan
nela
vera
gera
tes
are
unaf
fect
edby
bus
öþÖëöÙ ÖÜ ÝÞ �ã æ
çöþÖëöÙ ÖÜ ûÞ
Õ Goa
l:to
synt
hesi
zea
bus
that
cons
tant
lytr
ansf
ers
data
i.e.
íÖöÿ ëöÙ ÖÜ ÝÞàßöþÖëöÙ ÖÜ ûÞ
t=0
1s2s
3s4s
88
88
1616
16 1616
16
(3x1
6 bi
ts)
/ 4s
=
12
bits
/s
(4 +
12
bits
/s)
=
16
bits
/s
time(2
x8 b
its)
/ 4s
=
4 b
its/s
chan
nel
X
chan
nel
Y
X1
X2
X1
X2
Y1
Y1
Y2
Y3
Y3
Y2
bus
B
Ave
rage
rat
e
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t16
8of
214
Con
stra
ints
for
bus
gene
ratio
n
Õ Bus
wid
th:
affe
cts
num
ber
ofpi
nson
chip
boun
darie
s
Õ Cha
nnel
aver
age
rate
s:
affe
cts
exec
utio
ntim
eof
beha
vior
s
Õ Cha
nnel
peak
rate
s:
affe
cts
time
requ
ired
for
sing
lem
essa
getr
ansf
er
t=0
1s2s
3s4s
81616
time
88
8
1616
X1
X1
X1
X2
X2
X2
aver
ate(
B)
= 8
bits
/spe
akra
te(B
) =
8 bi
ts/s
aver
ate(
X)
= 8
bits
/s
peak
rate
(B)
= 1
6 bi
ts/s
aver
ate(
B)
= 8
bits
/s
chan
nel X
bus
B
bus
B
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t16
9of
214Bus
gene
ratio
nal
gorit
hm[N
G94
]
/*D
eter
min
era
nge
ofbu
swid
ths
*/
�é ��é÷ ����
1,
����é÷ �� �
Max
� ä é � �� ��
�é ����� �� ,
�é ����� �é÷ �� ��
for
�����é÷ �� in
�é ��é÷ ��
to
����é÷ ��
loop
/*co
mpu
tebu
spe
akra
te*/
���� ��� �� ç� ������é÷ �� �����÷ � �!� ç�
/*co
mpu
tesu
mof
chan
nela
vera
gera
tes
*/
�"���� ���� =0
;fo
ral
lcha
nnel
s
æç lo
op
�"���� �� � �������� #%$ �'&ä é � �� �
������� #� ( ������� #�
�"���� ���� =�"���� ���� +�"���� �� � ;
end
loop
if(
���� ��� �� ç�*)�"���� ���� )th
en/*
feas
ible
solu
tion,
dete
rmin
em
inim
alco
st*/
��������� C
ompu
teC
ost(
�����é÷ �� )
if(����
����+�é ����� )
then
�é ����� ���������
,
�é ����� �é÷ �� ������é÷ ��
end
ifen
dif
end
loop
retu
rn(
�é ����� �é÷ ��
)
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t17
0of
214
Bus
gene
ratio
nal
gorit
hm
Õ Com
pute
busw
idth
rang
e:
,-/.0-
1 2354
1,
,670
-1 23 4
Max
8 9 -2;:8 ú<<
Õ For
,-/.0-
1 23 =>?@@0-
1 23 =
,670
-1 23 lo
opC
ompu
tebu
spe
akra
te:
íÖöÿ ëöÙ ÖÜ ÝÞ ßØ�ëë�Úõ ÙBAíëîÙõ Ö ö�Ü ÝÞ
Com
pute
chan
nel
aver
age
rate
s
ØîÛÛÙÚzÛÖÜ üÞ ßöØØÖððÜ üÁýûÞ â
CDä é � �� �
�����é÷ ��E âíëîFõ�G ö�H IJK
öþGëöF GH ûJML
öNNGðð
H üÁýûJ âè O F ðH ûJ
NîPíFOPGH ü
JRQ NîPPFOPGH ü
J
if
íGöÿ ëöF GH IJ �ã æ
çöþGëöF GH ûJ th
en
if
è GðF NîðF Sû îPí�F Gû îðFH N�ëë�Oõ FJ
then
è GðF NîðF Lû îPí�F Gû îðFH N�ëë�Oõ FJ
è GðF �Oõ F LN�ëë�Oõ F
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t17
1of
214
Bus
gene
ratio
nex
ampl
e
T 2be
havi
orac
cess
ing
16bi
tdat
aov
ertw
och
anne
ls
T Con
stra
ints
spec
i�ed
for
chan
nelp
eak
rate
s
0.0
4.0
8.0
12.0U
16.0V
20.0W
24.0X
Bus
wid
th
-100
0.0
0.0
1000
.020
00.0
3000
.040
00.0
5000
.0
6000
.070
00.0
8000
.090
00.0
Cost Function Value Y
sele
cted
bus
wid
thin
feas
ible
impl
emen
tatio
ns
feas
ible
impl
emen
tatio
ns
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t17
2of
214
Per
form
ance
vs.
busw
idth
trad
eoffs
T Allo
ws
abu
swid
thto
bese
lect
ed,g
iven
perf
orm
ance
cons
trai
nts
e.g.
beha
vior
ü 1ha
spe
rfor
man
ceco
nstr
aint
of25
00cl
ocks
.bu
swid
ths
of4
orgr
eate
rm
ustb
ese
lect
ed
0.0
4.0
8.0
12.0Z
16.0[
20.0\
24.0]
Bus
wid
th (
pins
)
^
0.0
1000
.0
2000
.0
3000
.0
4000
.0
5000
.0
6000
.0
7000
.0
Behavior execution time (clocks) _
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t17
3of
214
Pro
toco
lge
nera
tion
T Bus
cons
ists
ofse
vera
lset
sof
wire
s:D
ata
lines
,use
dfo
rtr
ansf
errin
gm
essa
gebi
tsC
ontr
ollin
es,u
sed
for
sync
hron
izat
ion
betw
een
beha
vior
sID
lines
,use
dfo
rid
entif
ying
the
chan
nela
ctiv
eon
the
bus
T All
chan
nels
map
ped
tobu
ssh
are
thes
elin
es
T Num
ber
ofda
talin
esde
term
ined
bybu
sge
nera
tion
algo
rithm
T Pro
toco
lgen
erat
ion
cons
ists
ofsi
xst
eps
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t17
4of
214
Pro
toco
lge
nera
tion
1.P
roto
col
sele
ctio
n:
full
hand
shak
e,ha
lf-ha
ndsh
ake
etc.
2.ID
assi
gnm
ent
:
` chan
nels
requ
ire
acbd
2
8`< ID
lines
bus
B
CH
0
CH
1
CH
2
CH
3
beha
vior
P
var
iabl
e A
D;
begi
n
....
.
X <
= 3
2 ;
.
....
M
EM
(AD
) :=
X +
7;
.
....
end
;
beha
vior
Q
var
iabl
e C
OU
NT
;be
gin
.
....
M
EM
(60)
:= C
OU
NT
;
....
.en
d ;
varia
ble
X :
bit_
vect
or(1
5 do
wnt
o 0)
;
varia
ble
ME
M :
bit_
vect
or
(63
dow
nto
0, 1
5 do
wnt
o 0)
;
"00"
"00"
"00"
"00"
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t17
5of
214
Pro
toco
lge
nera
tion
3.B
usst
ruct
ure
de�n
ition
4.B
uspr
otoc
olde
�niti
on
f
or J
in 1
to 2
loop
w
ait
until
(B
.ST
AR
T =
’1’)
and
(B.ID
= "
00")
;
rxd
ata
(8*J
−1
dow
nto
8*(J
−1)
) <
= B
.DA
TA
;
B.D
ON
E <
= ’1
’ ;
wai
t unt
il (
B.S
TA
RT
= ’0
’) ;
B
.DO
NE
<=
’0’ ;
e
nd lo
op;
b
us B
.ID <
= "
00"
;
for
J in
1 to
2 lo
op
B.d
ata
<=
txd
ata(
8*J−
1 d
ownt
o 8
*(J−
1))
;
B.S
TA
RT
<=
’1’ ;
w
ait u
ntil
(B
.DO
NE
= ’1
’) ;
B
.ST
AR
T <
= ’0
’ ;
wai
t unt
il (
B.D
ON
E =
’0’)
;
end
loop
;
type
Han
dSha
keB
us is
rec
ord
end
reco
rd ;
sign
al B
: H
andS
hake
Bus
;
proc
edur
e R
ecei
veC
H0(
rxd
ata
: out
bit_
vect
or)
isbe
gin
end
Rec
eive
CH
0;
proc
edur
e S
endC
H0(
txda
ta :
in b
it_ve
ctor
) is
begi
n
end
Sen
dCH
0;
S
TA
RT
, DO
NE
: bi
t ;
ID :
bit_
vect
or(1
dow
nto
0) ;
D
AT
A :
bit_
vect
or(7
dow
nto
0) ;
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t17
6of
214
Pro
toco
lge
nera
tion
5.U
pdat
eva
riabl
ere
fere
nces
6.G
ener
ate
beha
vior
sfo
rva
riabl
es
8
proc
ess
Q
var
iabl
e C
OU
NT
;be
gin
.
....
S
endC
H3(
60, C
OU
NT
);
....
.en
d ;
bus
B
proc
ess
Xpr
oc
var
iabl
e X
; be
gin
w
ait
on B
.ID;
if (B
.ID=
"00"
) th
en
rec
eive
CH
0(X
);
el
sif (
B.ID
="0
1" )
then
s
endC
H1(
X);
end
if;en
d;
proc
ess
ME
Mpr
oc v
aria
ble
ME
M: a
rray
(0 to
63)
; be
gin
w
ait
on B
.ID;
if (B
.ID=
"10"
) th
en
rec
eive
CH
2(M
EM
);
el
sif (
B.ID
="1
1" )
then
r
ecei
veC
H3(
ME
M);
end
if;en
d;
proc
ess
P
va
riabl
e A
D X
tem
p;be
gin
.
....
S
endC
H0(
32)
;
....
.
Rec
eive
CH
1(X
tem
p);
S
endC
H2(
AD
, Xte
mp+
7);
.
....
end
;
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t17
7of
214
Res
olvi
ngac
cess
con
icts
e Sys
tem
part
ition
ing
may
resu
ltin
conc
urre
ntac
cess
esto
are
sour
ceC
hann
els
map
ped
toa
bus
may
atte
mpt
data
tran
sfer
sim
ulta
neou
sly
Var
iabl
esm
appe
dto
am
emor
ym
aybe
acce
ssed
bybe
havi
ors
sim
ulta
neou
sly
e Arb
iter
need
sto
bege
nera
ted
tore
solv
esu
chac
cess
con
icts
e Thr
eeta
sks
Arb
itrat
ion
mod
else
lect
ion
Arb
itrat
ion
sche
me
sele
ctio
nA
rbite
rge
nera
tion
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t17
8of
214
Arb
itrat
ion
mod
els
Sta
tic
Dyn
amic
addr
/ da
ta
addr
/ da
ta
port
1po
rt2
port
2po
rt1
mem
ory
ME
M
mem
ory
ME
MM
emA
rbite
r
Mem
Arb
iter
addr
/ da
taaddr
/ da
ta
req,
gran
tre
q,gr
ant
req,
gran
t
beha
vior
Pbe
havi
or Q
beha
vior
R
beha
vior
Pbe
havi
or Q
beha
vior
R
req,
gran
tre
q,gr
ant
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t17
9of
214
Arb
iter
gene
ratio
n
e Exa
mpl
eof
bus
arbi
trat
ion
Two
beha
vior
sac
cess
ing
asi
ngle
reso
urce
,bus
fB
ehav
ior
g assi
gned
high
erpr
iorit
yth
an
h
Fix
edpr
iorit
yim
plem
ente
dw
ithtw
oha
ndsh
ake
sign
als
ikjl
and
m�nopq
bus
B 8
Req
_P <
= ’1
’;
w
ait u
ntil
(G
rant
_P =
’1’);
Req
_P <
= ’0
’;
pr
oces
s P
varia
ble
AD
Xte
mp;
begi
n
....
.
S
endC
H0(
32)
;
.
....
end
proc
ess
;
R
eq_Q
<=
’1’;
w
ait u
ntil
(G
rant
_Q =
’1’);
R
eq_Q
<=
’0’;
proc
ess
Q
var
iabl
e C
OU
NT
;be
gin
.
....
S
endC
H3(
60, C
OU
NT
);
.
....
end
pro
cess
;
Req
_PG
rant
_P
Req
_QG
rant
_Q
begi
n
wai
t un
til (
Req
_P=
’1’)
or (
Req
_Q =
’1’);
i
f (R
eq_P
= ’1
’) th
en
Gra
nt_P
= ’1
’;
wai
t uni
tl (R
eq_P
= ’0
’);
Gra
nt_P
= ’0
";
els
if (
Req
_Q =
’1’)
then
G
rant
_Q <
= ’1
’;
wai
t unt
il (R
eq_Q
= ’0
’);
Gra
nt_Q
<=
’0’;
e
nd if
;en
d pr
oces
s;
proc
ess
B_a
rbite
r
proc
ess
ME
Mpr
oc
varia
ble
ME
M: a
rray
(0 to
63)
; be
gin
w
ait
on B
.ID;
if (B
.ID=
"10"
) th
en
rec
eive
CH
2(M
EM
);
el
sif (
B.ID
="1
1" )
then
r
ecei
veC
H3(
ME
M);
end
if;en
d pr
oces
s;
proc
ess
Xpr
oc
varia
ble
X ;
begi
n
wai
t on
B.ID
;
if
(B.ID
="0
0")
then
r
ecei
veC
H0(
X);
elsi
f (B
.ID=
"01"
) th
en
sen
dCH
1(X
);
en
d if;
end
proc
ess;
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t18
0of
214Effe
ctof
bind
ing
onin
terf
aces
Sta
ndar
d
Sta
ndar
dS
tand
ard
Cus
tom
Cus
tom
beha
vior
B
beha
vior
B
beha
vior
B
beha
vior
X
beha
vior
A
beha
vior
A
Pa
Pb
Pb
PaPa
Pb
prot
ocol
prot
ocol
Cha
nnel
X
Cha
nnel
X
Cus
tom
Inte
rfac
e P
roce
ss
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t18
1of
214
Pro
toco
lop
erat
ions
e Pro
toco
lsus
ually
cons
isto
f�ve
atom
icop
erat
ions
wai
ting
for
anev
ento
nin
putc
ontr
ollin
eas
sign
ing
valu
eto
outp
utco
ntro
llin
ere
adin
gva
lue
from
inpu
tdat
apo
rtas
sign
ing
valu
eto
outp
utda
tapo
rtw
aitin
gfo
r�x
edtim
ein
terv
al
e Pro
toco
lope
ratio
nsm
aybe
spec
i�ed
inon
eof
thre
ew
ays
Fin
itest
ate
mac
hine
s(F
SM
s)Ti
min
gdi
agra
ms
Har
dwar
ede
scrip
tion
lang
uage
s(H
DLs
)
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t18
2of
214Pro
toco
lsp
eci�c
atio
n:
FS
Ms
e Pro
toco
lope
ratio
nsor
dere
dby
sequ
enci
ngbe
twee
nst
ates
e Con
stra
ints
betw
een
even
tsm
aybe
spec
i�ed
usin
gtim
ing
arcs
e Con
ditio
nal&
repe
titiv
eev
ents
eque
nces
requ
ireex
tra
stat
es,t
rans
ition
s
Pro
toco
l Pa
Pro
toco
l Pb
a1 a2 a3star
t
AD
DR
p <
= A
ddrV
ar(7
dow
nto
0);
AR
DY
p <
= ’1
’;(A
RC
Vp
= ’1
’ )
AD
DR
p <
= A
ddrV
ar(1
5 do
wnt
o 8)
;A
RE
Qp
<=
’1’;
(DR
DY
p =
’1’ )
Dat
aVar
<=
DA
TA
p
star
t
b1 b2 b3
(RD
p =
’1’)
MA
ddrV
ar :=
MA
DD
Rp
(100
ns)
MD
AT
Ap
<=
M
emV
ar (
MA
ddrV
ar)
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t18
3of
214
Pro
toco
lsp
eci�c
atio
n:
Tim
ing
diag
ram
s
e Adv
anta
ges:
Eas
eof
com
preh
ensi
on,r
epre
sent
atio
nof
timin
gco
nstr
aint
s
e Dis
adva
ntag
es:
Lack
ofac
tion
lang
uage
,not
sim
ulat
able
Dif�
cultt
osp
ecify
cond
ition
alan
dre
petit
ive
even
tseq
uenc
es
7..0
15..8
15..0
AR
DY
p
AD
DR
p
AR
CV
p
DR
EQ
p
DR
DY
p
DA
TA
p
15..0
15..0
100n
s
MA
DD
Rp
RD
p
MD
AT
Ap
Pro
toco
l Pa
Pro
toco
l Pb
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t18
4of
214Pro
toco
lsp
eci�c
atio
n:
HD
Ls
e Adv
anta
ges:
Fun
ctio
nalit
yca
nbe
veri�
edby
sim
ulat
ion
Eas
yto
spec
ifyco
nditi
onal
and
repe
titiv
eev
ents
eque
nces
e Dis
adva
ntag
es:
Cum
bers
ome
tore
pres
entt
imin
gco
nstr
aint
sbe
twee
nev
ents
MA
DD
Rp
MD
AT
Ap
RD
p
16
16
8
16
port
AD
DR
p : o
ut
b
it_ve
ctor
(7 d
ownt
o 0)
;po
rt D
AT
Ap
: in
bit_
vect
or(1
5 do
wnt
o 0)
;po
rt A
RD
Yp
: out
bit;
port
AR
CV
p : i
n b
it;po
rt D
RE
Qp
: out
bit;
port
DR
DY
p : i
n bi
t;
AD
DR
p <
= A
ddrV
ar(7
dow
nto
0);
AR
DY
p <
= ’1
’;w
ait u
ntil
(AR
CV
p =
’1’ )
;A
DD
Rp
<=
Add
rVar
(15
dow
nto
8);
DR
EQ
p <
= ’1
’;w
ait
until
(D
RD
Yp
= ’1
’);D
ataV
ar <
= D
AT
Ap;
AD
DR
pD
AT
Ap
AR
DY
p
AR
CV
p
DR
EQ
pD
RD
Yp
port
MA
DD
Rp
: in
b
it_ve
ctor
(15
dow
nto
0);
port
MD
AT
Ap
: out
bit_
vect
or(1
5 do
wnt
o 0)
;po
rt R
Dp
: in
bit;
wai
t unt
il (
RD
p =
’1’);
MA
ddrV
ar :=
MA
DD
Rp
;w
ait
for
100
ns;
MD
AT
Ap
<=
Mem
Var
(M
Add
rVar
);
Pro
toco
l Pa
Pro
toco
l Pb
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t18
5of
214In
terf
ace
proc
ess
gene
ratio
n
e Inpu
t:H
DL
desc
riptio
nof
two
�xed
,but
inco
mpa
tible
prot
ocol
s
e Out
put:
HD
Lpr
oces
sth
attr
ansl
ates
one
prot
ocol
toth
eot
her
i.e.
resp
onds
toth
eir
cont
rols
igna
lsan
dse
quen
ceth
eir
data
tran
sfer
s
e Fou
rst
eps
requ
ired
for
gene
ratin
gin
terf
ace
proc
ess
(IP
):C
reat
ing
rela
tions
Par
titio
ning
rela
tions
into
grou
psG
ener
atin
gin
terf
ace
proc
ess
stat
emen
tsin
terc
onne
ctop
timiz
atio
n
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t18
6of
214
IPge
nera
tion:
crea
ting
rela
tions
e Pro
toco
lrep
rese
nted
asan
orde
red
seto
frel
atio
ns
e Rel
atio
nsar
ese
quen
ces
ofev
ents
/act
ions
AD
DR
p <
= A
ddrV
ar(7
dow
nto
0);
AR
DY
p <
= ’1
’;w
ait u
ntil
(AR
CV
p =
’1’ )
;A
DD
Rp
<=
Add
rVar
(15
dow
nto
8);
DR
EQ
p <
= ’1
’;w
ait
until
(D
RD
Yp
= ’1
’);D
ataV
ar <
= D
AT
Ap;
A1
A2
A3
[ (D
RD
Yp
= ’1
’) :
Dat
aVar
<=
DA
TA
p ]
[ (A
RC
Vp
= ’1
’) :
AD
DR
p <
= A
ddrV
ar(1
5 do
wnt
o 8)
DR
EQ
p <
= ’1
’ ]
[ (tr
ue)
:
A
DD
Rp
<=
Add
rVar
(7 d
ownt
o 0)
AR
DY
p <
= ’1
’ ]
Pro
toco
l P
aR
elat
ions
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t18
7of
214
IPge
nera
tion:
part
ition
ing
rela
tions
r Par
titio
nth
ese
tofr
elat
ions
from
both
prot
ocol
sin
togr
oups
.
r Gro
upre
pres
ents
aun
itof
data
tran
sfer
B2
(16
bits
out
)
G1
G2
Pro
toco
l P
aP
roto
col
Pb
A1
(8 b
its o
ut)
A2
(8 b
its o
ut)
B1
(16
bits
in)
A3
(16
bits
in)
s1
tu v1v
2
w 1
xs
2
tuw 1v
3
x
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t18
8of
214
IPge
nera
tion:
inve
rtin
gpr
otoc
olop
erat
ions
r For
each
oper
atio
nin
agr
oup,
add
itsdu
alto
inte
rfac
epr
oces
s
r Dua
lofa
nop
erat
ion
repr
esen
tsth
eco
mpl
emen
tary
oper
atio
n
r Tem
pora
ryva
riabl
em
aybe
requ
ired
toho
ldda
tava
lues
AD
DR
p
DA
TA
p
AR
DY
p
AR
CV
p
DR
EQ
pD
RD
Yp
MA
DD
Rp
MD
AT
Ap
RD
p
816
1616
Inte
rfac
e P
roce
ss
/*
(gr
oup
G1)
’ */
w
ait u
ntil
(A
RD
Yp
= ’1
’);T
empV
ar1(
7 do
wnt
o 0)
:= A
DD
Rp
;A
RC
Vp
<=
’1’ ;
wai
t unt
il (
DR
EQ
p =
’1’);
Tem
pVar
1(15
dow
nto
8) :=
AD
DR
p ;
RD
p <
= ’1
’ ;M
AD
DR
p <
= T
empV
ar1;
/* (
grou
p G
2)’
*/w
ait f
or 1
00 n
s;T
empV
ar2
:= M
DA
TA
p ;
DR
DY
p <
= ’1
’ ;D
AT
Ap
<=
Tem
pVar
2 ;
wai
t for
100
ns
wai
t for
100
ns
Dua
l op
erat
ion
Cp
<=
’1’
var
<=
Dp
Dp
<=
var
Tem
pVar
:= D
p
Dp
<=
Tem
pVar
Cp
<=
’1’
wai
t unt
il (C
p =
’1’)
wai
t unt
il (C
p =
’1’)
Ato
mic
ope
ratio
n
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t18
9of
214
IPge
nera
tion:
inte
rcon
nect
optim
izat
ion
r Cer
tain
port
sof
both
prot
ocol
sm
aybe
dire
ctly
conn
ecte
d
r Adv
anta
ges:
Byp
assi
ngin
terf
ace
proc
ess
redu
ces
inte
rcon
nect
cost
Ope
ratio
nsre
late
dto
thes
epo
rts
can
beel
imin
ated
from
inte
rfac
epr
oces
s
AD
DR
p
DA
TA
p
AR
DY
p
AR
CV
p
DR
DY
p
MA
DD
Rp
MD
AT
Ap
8
16
16
Inte
rfac
e P
roce
ss
BA
wai
t unt
il (
AR
DY
p =
’1’);
Tem
pVar
1(7
dow
nto
0) :=
AD
DR
p ;
AR
CV
p <
= ’1
’ ;w
ait u
ntil
(D
RE
Qp
= ’1
’);T
empV
ar1(
15 d
ownt
o 8)
:= A
DD
Rp
;R
Dp
<=
’1’ ;
MA
DD
Rp
<=
Tem
pVar
1;w
ait f
or 1
00 n
s;D
RD
Yp
<=
’1’ ;
DR
EQ
p
RD
p
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t19
0of
214
Tran
sduc
ersy
nthe
sis
[BK
87]
r Inpu
t:Ti
min
gdi
agra
mde
scrip
tion
oftw
o�x
edpr
otoc
ols
r Out
put:
Logi
cci
rcui
tdes
crip
tion
oftr
ansd
ucer
r Ste
psfo
rge
nera
ting
logi
cci
rcui
tfro
mtim
ing
diag
ram
s:C
reat
eev
entg
raph
sfo
rbo
thpr
otoc
ols
Con
nect
grap
hsba
sed
onda
tade
pend
enci
esor
expl
icitl
ysp
eci�e
dor
derin
gA
ddte
mpl
ates
for
each
outp
utno
dein
com
bine
dgr
aph
Mer
gean
dco
nnec
ttem
plat
esS
atis
fym
in/m
axtim
ing
cons
trai
nts
Opt
imiz
esk
elet
alci
rcui
t
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gR
e�ne
men
t19
1of
214
Gen
erat
ing
even
tgr
aphs
from
timin
gdi
agra
ms
e.g.
FIF
Ost
ack
cont
rolc
ell
Ri
L Ro
Ao
Ai
Ri
Ao
Ai
L
Cel
l
Ro
E
SR
i
L
Ro
L
Ai
Ri
LL
Ro
Ao
Ai
Ao
UC
Irvi
neC
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UC
Irvi
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199
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l D. G
ajsk
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199
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rank
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l D. G
ajsk
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rank
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UC
Irvi
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(c)
199
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l D. G
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rank
Vah
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rank
Vah
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rank
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An
exam
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desi
gnm
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gy
Com
pone
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plem
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des
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UC
Irvi
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(c)
199
4 D
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l D. G
ajsk
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rank
Vah
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UC
Irvi
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199
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l D. G
ajsk
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rank
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One
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UC
Irvi
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199
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l D. G
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rank
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Gen
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synt
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requ
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llle
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UC
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199
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l D. G
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rank
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synt
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synt
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ICDescription generators
UC
Irvi
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199
4 D
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l D. G
ajsk
i, F
rank
Vah
id, S
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Age
neric
syst
em-s
ynth
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UC
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rank
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UC
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199
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UC
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199
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rank
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UC
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199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
etho
dolo
gy21
3of
214
Sum
mar
y
z Thr
ee-s
tep
desi
gnm
etho
dolo
gyF
unct
iona
lity
spec
i�cat
ion
Sys
tem
desi
gnC
ompo
nent
impl
emen
tatio
n
z Maj
orta
sks
insy
stem
desi
gnA
lloca
tion
Par
titio
ning
Re�
nem
ent
z Gen
eric
synt
hesi
sto
ol
z Con
cept
ualiz
atio
nen
viro
nmen
tC
ruci
alto
prac
tical
use
UC
Irvi
neC
opyr
ight
(c)
199
4 D
anie
l D. G
ajsk
i, F
rank
Vah
id, S
anjiv
Nar
ayan
, and
Jie
Gon
gM
etho
dolo
gy21
4of
214
Fut
ure
dire
ctio
ns
z Adv
ance
des
timat
ion
met
hods
z For
mal
veri�
catio
n
z Test
abili
ty
z Fra
mew
orks
and
data
base
s
z Reg
ular
ityex
ploi
ting
z Sys
tem
-leve
ltra
nsfo
rmat
ions
z Fee
dbac
kin
corp
orat
ion
Ref
eren
ces
[BH
S91
]F.
Bel
ina,
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ogre
fe,a
ndA
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SD
Lw
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omP
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R.G
upta
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li.\P
artit
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ngof
func
tiona
lmod
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ofsy
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onou
sdi
gita
lsys
tem
s,".
InP
roce
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Inte
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R.G
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ings
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eE
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spec
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men
t,".In
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C.A
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]R
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tpa
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E.D
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nese
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vels
ynth
esis
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tegr
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ion,
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P.G
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esis
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Com
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[PP
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]A
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r,T.
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AH
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prog
ram
ford
atap
ath
synt
hesi
s,".
InP
roce
edin
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[TM
91]
D.E
.Tho
mas
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oorb
y.T
heV
erilo
gH
ardw
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Des
crip
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uage
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luw
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[VG
92]
F.V
ahid
and
D.D
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ski.
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rtiti
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gn,"
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Pro
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eD
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[VG
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id,J
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g,an
dD
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ajsk
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hard
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ftwar
epa
rtiti
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gorit
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rm
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izin
gha
rdw
are,
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CIr
vine
,Dep
t.of
ICS
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alR
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38,1
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