Dortmund, FABIDO and Experiences concerning the Assist-Project
Department of Computer Science, University of Pisapvmmpi03/post/vanneschi.pdf · ASSIST...
63
ASSIST ASSIST High High - - performance performance Programming Programming Environment : Environment : Application Application Experiences Experiences and Grid Evolution and Grid Evolution Marco Marco Vanneschi Vanneschi Department of Computer Science, University of Pisa EuroPVM/MPI 2003, Venice
Transcript of Department of Computer Science, University of Pisapvmmpi03/post/vanneschi.pdf · ASSIST...
ASS
IST
ASS
IST
Hig
hH
igh --
perf
orm
ance
pe
rfor
man
ce
Prog
ram
min
g Pr
ogra
mm
ing
Envi
ronm
ent :
En
viro
nmen
t :
App
licat
ion
App
licat
ion
Expe
rienc
es
Expe
rienc
es
and
Grid
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lutio
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rid E
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Mar
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ASS
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-Mar
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AS
SIS
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Sof
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tem
bas
ed o
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tegr
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AC
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rst G
rid
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ssis
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f(on
top
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bus)
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n-go
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Hig
h-pe
rfor
man
ceC
ompo
nent
ASS
IST
Dep
artm
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f Com
pute
r Sci
ence
, Uni
vers
ity o
f Pis
a
ASS
IST
A P
rogr
amm
ing
Envi
ronm
ent f
or H
igh-
perf
orm
ance
Por
tabl
e A
pplic
atio
ns o
n C
lust
ers,
Lar
ge-s
cale
Pla
tform
s an
d G
rids
Dep
artm
ent
Dep
artm
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f Com
pute
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Com
pute
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ence
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ity o
f Pis
a, U
nive
rsity
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isa
ASS
IST
ASS
IST
A
A P
rogr
amm
ing
Envi
ronm
ent f
or
Prog
ram
min
g En
viro
nmen
t for
Hig
hH
igh --
perf
orm
ance
pe
rfor
man
ce P
orta
ble
Port
able
A
pplic
atio
ns
App
licat
ions
on on
Clu
ster
sC
lust
ers ,
, Lar
geLa
rge --
scal
e sc
ale
Plat
form
s Pl
atfo
rms
and
and
Grid
sG
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[Par
alle
lCom
putin
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002]
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ttp://
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ASS
IST
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AS
SIS
T as
a re
sear
ch v
ehic
le
From
�cl
assi
cal�
ske
leto
ns to
A
SSIS
T
Sign
ifica
nt im
prov
emen
ts fo
rcl
uste
r arc
hite
ctur
es
Feas
ible
and
suc
cess
ful a
ppro
ach
for a
pplic
atio
ns:
�C
ompu
tatio
nal C
hem
istr
y, a
nd o
ther
scie
ntifi
c co
des,
�Im
age
& S
igna
lPro
cess
ing,
�
Ear
th O
bser
vatio
nSy
stem
s, �
Vid
eo C
ompr
essi
on,
�K
now
ledg
e D
isco
very
and
Dat
a M
inin
g, U
ser
Prof
iling
, �
Sear
ch P
roce
ssin
g on
Str
uctu
red
/ Uns
truc
ture
dD
ata,
�
Que
ry L
angu
age
Inte
rpre
ters
, �
Can
it b
e a
feas
ible
ap
proa
ch
for L
arge
-sca
le a
nd
Grid
pla
tform
s
too
?
ASS
IST
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co V
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schi
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uroP
VM
/MPI
200
3, V
enic
e4
Out
line
1.S
truct
ured
Par
alle
l Pro
gram
min
g:
AS
SIS
T as
an
impr
ovem
ent wrt
�cla
ssic
al� s
kele
tons
2.Fl
exib
le im
plem
enta
tion
mod
el
3.To
war
ds G
rid p
rogr
amm
ing
ASS
IST
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co V
anne
schi
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uroP
VM
/MPI
200
3, V
enic
e5
Par
t 1
Stru
ctur
ed P
aral
lel P
rogr
amm
ing
AS
SIS
T as
an
impr
ovem
entwrt
�cla
ssic
al� s
kele
tons
ASS
IST
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co V
anne
schi
-E
uroP
VM
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200
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enic
e6
Stru
ctur
ed P
aral
lel P
rogr
amm
ing
Para
llel
prog
ram
pipe
line
farm
fora
ll
scan
Pipeline main
farm stage1
farm stage2
End pipe
ASS
IST
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co V
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schi
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uroP
VM
/MPI
200
3, V
enic
e7
Stru
ctur
ed P
aral
lel P
rogr
amm
ing
!H
igh-
leve
l con
stru
cts
fort
ask
para
llelis
m(e
.g.
PIP
ELI
NE
, FA
RM
), da
ta p
aral
lelis
m(e
.g. M
AP
, SC
AN
, S
TEN
CIL
S), m
ixed
task
+dat
a pa
ralle
lism
(D&
C,
PA
RM
OD
), an
d th
eir c
ompo
sitio
ns(G
EN
ER
IC o
r S
TRU
CTU
RE
D G
RA
PH
S)
!S
eman
ticm
odel
and
ass
ocia
ted
perfo
rman
ce m
odel
�co
nstra
ints
on th
e pa
ralle
l par
adig
m a
dopt
ed to
com
pose
(seq
uent
ial/
par
alle
l) m
odul
es in
to c
ompl
ex
appl
icat
ions
!M
any
pote
ntia
litie
s fo
rint
ensi
ve o
ptim
izat
ions
and
rest
ruct
urin
gof
app
licat
ions
ASS
IST
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co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e8
!A
ppro
ache
s to
Stru
ctur
ed P
aral
lel P
rogr
amm
ing:
�P
aral
lel S
kele
tons
mod
el�
Par
alle
lDes
ign
Pat
tern
s�
�
!O
verc
omin
gth
e di
fficu
lties
of tr
aditi
onal
data
par
alle
l lan
guag
es(H
PF)
and
thei
r evo
lutio
ns
!O
ur p
ast e
xper
ienc
e(U
niv.
Pis
a): s
kele
tons
-bas
ed
coor
dina
tion
lang
uage
s�
P3L
(199
1), C
-bas
ed, f
ixed
ske
leto
n se
t: pi
pe, m
ap �
�Sk
IE(1
997)
, C/C
++/F
77/J
ava
�Li
thiu
m(2
001)
, Jav
a-ba
sed,
mac
ro d
ata-
flow
, pip
e, fa
rm, m
ap, D
&C
�S
ever
al v
aria
nts
of th
em
Stru
ctur
ed P
aral
lel P
rogr
amm
ing
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e9
Stru
ctur
ed p
aral
lel p
rogr
amm
ing
and
perfo
rman
ce m
odel
s
Exa
mpl
e: F
arm
/ Mas
ter-
Sla
ve /
Par
amet
er S
wee
ping
/ �
Em
itter
: Ta
sk
Sche
dulin
g
Col
lect
or
of T
ask
Res
ults
Inpu
t St
ream
Out
put
Stre
am
W1
Wn. . .
Set o
f fun
ctio
nally
iden
tical
Wor
kers
Opt
imal
num
ber o
f wor
kers
and
oth
er p
erfo
rman
ce p
aram
eter
s (e.
g.
thro
ughp
ut, e
ffic
ienc
y) c
an b
e ex
pres
sed
as fu
nctio
ns o
f pro
cess
ing
times
, com
mun
icat
ion
times
, and
util
izat
ion
fact
ors
Effi
cien
t an
d pa
ram
etri
c im
plem
enta
tion
te
mpl
ates
for
plat
form
-an
d ap
plic
atio
n-de
pend
ent
opti
miz
atio
ns
Load
-bal
ance
d ex
ecut
ion
of T
asks
bel
ongi
ng to
a S
tream
ASS
IST
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co V
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/MPI
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3, V
enic
e10
!S
ever
al p
ros:
eas
y pr
ogra
mm
abili
ty, r
apid
pro
toty
ping
, se
quen
tial s
oftw
are
reus
e, e
ffici
ency
�m
ainl
y fo
r reg
ular
app
licat
ions
and
/or r
egul
ar c
ompo
sitio
ns
!C
ons:
for c
ompl
ex c
ompo
sitio
ns, a
nd fo
r som
e irr
egul
ar
and
dyna
mic
app
licat
ions
�La
ck o
f exp
ress
iven
ess
/ ine
ffici
ency
�La
ck o
f fle
xibi
lity
�A
ny m
odifi
catio
n le
d to
ext
ensi
ve c
hang
es w
ithin
com
pile
r & ru
n-tim
e su
ppor
t
!O
ptim
izat
ions
: �
nots
o in
tens
ive
at c
ompi
le ti
me
asit
was
expe
cted
,�
very
sig
nific
ant a
t the
run-
time
supp
ort l
evel
,�
also
for d
ynam
icap
proa
ches
to th
e ru
n-tim
e de
sign
Ske
leto
ns: o
ur p
ast e
xper
ienc
e
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e11
AS
SIS
T: g
ener
alpr
ogra
m s
truct
ures
!C
lass
ical
ske
leto
ns:o
ften,
fixe
d-pa
ttern
spr
ogra
m s
truct
ures
are
too
sim
ple
for
com
plex
app
licat
ions
!A
SS
IST:
para
llel p
rogr
ams
repr
esen
ted
as
gene
ric g
raph
s�
who
se n
odes
are
stru
ctur
ed
�an
d ca
n sh
are
obje
cts
ASS
IST
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co V
anne
schi
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uroP
VM
/MPI
200
3, V
enic
e12
Sim
ple
com
posi
tion
of fi
xed-
patte
rns
(stre
ampa
ralle
l: pi
pelin
e, fa
rm s
kele
tons
)
Exam
ple:
a si
mpl
eR
ay T
race
r
stag
e 1
stag
e 3
. . .
Stre
amof
in
put
scen
es
Stre
amof
ou
tput
sc
enes
stag
e 2
(far
m)
rend
erin
gal
gori
thm
Stre
ams
of
scen
es
Para
llelis
m
amon
g sc
enes
ASS
IST
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co V
anne
schi
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/MPI
200
3, V
enic
e13
Com
posi
tion
of s
tream
+ da
ta p
aral
lelis
m
Exam
ple:
a m
ore
pow
erfu
lRay
Tra
cer
stag
e 2
(far
m+
map
)re
nder
ing
algo
rith
m
stag
e 1
stag
e 3
. . .St
ream
of
inpu
t sc
enes
Stre
am of
outp
ut
scen
es
Para
llelis
m a
mon
g sc
enes
and
insi
de
ever
ysi
ngle
sce
ne
ASS
IST
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co V
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schi
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uroP
VM
/MPI
200
3, V
enic
e14
S
eque
ntia
lmod
ules
!w
ritte
nin
sev
eral
ho
st la
ngua
ges
(C, C
++, F
ortra
n, J
ava)
Arb
itrar
y C
ompo
sitio
n
ge
neric
gra
phs
!st
ream
-orie
nted
!bo
thda
ta-fl
owan
d no
ndet
erm
inis
ticw
ithin
tern
alst
ate
Not
only
fixed
-pat
tern
Par
alle
lSke
leto
ns...
AS
SIS
T C
oord
inat
ion
Lang
uage
(AS
SIS
T-C
L)
ASS
IST
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co V
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schi
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3, V
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{Ex
tern
al O
bjec
ts}
AS
SIS
T gr
aphs
and
Sha
red
Obj
ects
M3
Para
llel(
or se
quen
tial)
mod
ule
Inpu
t
stre
ams
Out
put
stre
am
M5
s 34
M4
s 25
s 45
s 54
M1
s 13
M2
s 23
�G
loba
l va
riabl
es
�Sh
ared
m
emor
y
�Fi
les a
nd
I/O
�Li
brar
ies
�CORBA,
DCOM, �
�A
SS
IST
mod
ules
�. .
.
Com
posi
tion
by
�Ty
ped
stre
ams
�E
xter
nal
obje
cts
ASS
IST
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co V
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3, V
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Gen
eric
gra
phs:
dat
a-flo
w +
non
dete
rmis
ms
Stre
am-b
ased
, po
ssib
ly c
yclic
gr
aph
of
com
pone
nts:
da
ta-f
low
and/
or
nond
eter
min
istic
be
havi
our
Acy
clic
prec
eden
ce
grap
h (D
AG
) of
com
pone
nts
with
dat
a-flo
wbe
havi
our
Stre
am-b
ased
com
puta
tion
s ar
e m
ore
gene
ral a
nd p
osse
ss in
tere
stin
g fe
atur
es o
f co
mpl
ex a
pplic
atio
ns (e
.g. d
ata
man
agem
ent,
ser
vers
)N
onde
term
inis
m +
sta
teis
a p
ower
ful f
eatu
re wrt
pure
ly f
unct
iona
l (e
.g. d
ata-
flow
) beh
avio
ur
ASS
IST
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co V
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Par
alle
l Mod
ule
(parm
od):
a pa
radi
gm fo
r stru
ctur
ed p
aral
lelis
m
!In
stea
d of
spe
cific
ske
leto
ns:
a G
ENER
IC S
KEL
ETO
N�
i.e. a
stru
ctur
eth
atca
n be
effe
ctiv
ely
spec
ializ
edat
eve
ry u
tiliz
atio
n
!Th
e parmod
cons
truct
incl
udes
the
clas
sica
l (st
ream
-pa
ralle
land
dat
a-pa
ralle
l) sk
elet
ons
as s
peci
al c
ases
�,
!�
but
it ai
ms
to a
chie
vem
uch
mor
e ex
pres
sive
pow
er.
!In
add
ition
, parmode
xpre
sses
par
alle
l com
puta
tions
with
stat
e, n
onde
term
inis
m, a
nd a
cces
s to
ext
erna
l sha
red
obje
cts.
ASS
IST
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co V
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schi
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3, V
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e18
The parmod
cons
truct
VP
VP
VP
VP
VP
VP
VP
VP
i n p u t s e c t i o n
Shar
ed st
ate
o u t p u t s e c t
Mul
tiple
inpu
t and
out
put t
yped
data
stre
ams
Set o
f Virt
ual P
roce
ssor
s(V
P) e
xecu
ting
user
code
VPs
hav
e as
sign
ed to
polo
gy fo
r nam
ing
(o
ne, n
one,
arr
ays)
ASS
IST
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co V
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schi
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3, V
enic
e19
The parmod
cons
truct
VP
VP
VP
VP
VP
VP
VP
VP
i n p u t s e c t i o n
Shar
ed st
ate
o u t p u t s e c t
inde
pend
ent d
istri
butio
nan
d co
llect
ion
stra
tegi
es(e
.g. b
road
cast
, mul
ticas
t, sc
atte
r, on
-dem
and)
inpu
t and
out
put s
ectio
nsca
n al
so h
ost a
rbitr
ary
user
code
ASS
IST
-Mar
co V
anne
schi
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uroP
VM
/MPI
200
3, V
enic
e20
The parmod
cons
truct
VP
VP
VP
VP
VP
VP
VP
VP
i n p u t s e c t i o n
Shar
ed st
ate
o u t p u t s e c t
VPs
hos
t sev
eral
use
r fun
ctio
ns, a
ctiv
atio
nca
n be
data
-driv
en(C
SP-li
ke n
onde
term
inis
tic e
xecu
tion,
gua
rded
cha
nnel
s)
VPs
shar
e da
ta st
ruct
ures
(r
un-ti
me
prov
ides
con
sist
ency
)
Par
titio
ning
ru
les,
re
plic
atio
n
ASS
IST
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co V
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schi
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uroP
VM
/MPI
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3, V
enic
e21
Effi
cien
t run
-tim
e su
ppor
t of parmod
!O
ne o
f the
mai
n ad
vant
ages
of s
truct
ured
par
alle
l pr
ogra
mm
ing
is th
e op
portu
nity
for e
ffici
ent r
un-
time
impl
emen
tatio
nof
�spe
cific
� ske
leto
ns.
!A
SS
IST
has
prov
ed th
at th
is is
true
for �
gene
ric�
skel
eton
s to
o: parmod
perfo
rman
ce is
�
com
para
ble
toth
atof
the
sam
e pr
ogra
ms
writ
ten
in M
PI,
�co
mpa
rabl
e to
, or b
ette
r tha
n, th
at o
f the
sam
e pr
ogra
ms
expr
esse
d by
�spe
cific
� ske
leto
ns�
Mor
e di
fficu
lt im
plem
enta
tion
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e22
Par
alle
lPar
titio
ned
Apr
iori
(Dat
a M
inin
g)!
Mai
nly
stre
am-p
aral
lel
!C
ompu
tatio
nin
tens
ive,
w
ell b
alan
ced
!da
tase
t> 1
60 M
b!
regu
lar I
/O p
atte
rn
!8
x P
entiu
m4,
Gbi
tEth
Apr
iori
spee
d-up
0,00
1,00
2,00
3,00
4,00
5,00
6,00
7,00
8,00
9,00
12
34
56
78
N. o
f Pro
cess
ors
Idea
lM
easu
red
Per
form
ance
Ben
chm
arks
of par
mod
(effi
cien
t as
MP
I or c
lass
ical
ske
leto
ns)
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e23
Apr
iori
algo
rithm
(dat
a m
inin
g) a
sa
pipe
line
of par
mod-
farm
s (�n
one�
topo
logy
)
stag
e 1
stag
e 4
. . .st
age
3
. . .
stag
e 2
stag
e 5
stag
e 6
1.D
atab
ase
read
ing,
gen
erat
ion
of s
tream
of p
artit
ions
2.Apriori
algo
rithm
in p
aral
lel(
load
bala
nced
farm
)
3.C
ombi
natio
nof
par
tial r
esul
ts: c
olla
psin
g hash-tree
data
stru
ctur
es
4.D
atab
ase scan
, gen
erat
ion
of a
new
stre
amof
par
titio
nsof
app
ropr
iate
siz
e
5.C
ompu
tatio
nof
"sup
port"
of t
he c
andi
date
sol
utio
n(fa
rmw
ithbr
oadc
ast)
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e24
Per
form
ance
Ben
chm
arks
of par
mod
(effi
cien
t as
MP
I, be
tter t
han
clas
sica
l ske
leto
ns)
Dat
a-P
aral
lel B
ench
mar
kV
aria
ble
Ste
ncil
�si
ngle
pa
rmod
!2-
D m
atrix
400
x400
!pa
rtitio
ned
row
-wis
e!
com
mun
icat
ion
sten
cil
varie
s at
eac
h st
epfo
r h
�
fora
ll i,
j �
!8
x P
entiu
m 4
, Gbi
tEth
Dat
a pa
ralle
l spe
ed-u
p
0,00
1,00
2,00
3,00
4,00
5,00
6,00
7,00
8,00
9,00
02
46
810
N. o
f Pro
cess
ors
Idea
lM
easu
red
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e25
An
irreg
ular
-dyn
amic
benc
hmar
k(m
uch
bette
r tha
n cl
assi
cal s
kele
tons
)
N-b
ody,
Bur
nes-
Hut
!P
arm
odim
plem
entin
g a
�spe
cial
ized
farm
�, w
ith s
hare
d m
emor
y ob
ject
s
!P
lum
mer
Mod
el, v
ery
irreg
ular
dat
a-se
t
!8
x P
entiu
m 4
, Gbi
tEth
N-b
ody
spee
d-up
, siz
e10
00K
0,00
1,00
2,00
3,00
4,00
5,00
6,00
7,00
8,00
9,00
02
46
810
N. o
f Pro
cess
ors
Idea
lM
easu
red
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e26
Com
plex
par
alle
l pro
gram
s in
AS
SIS
T
!C
ompl
ex a
pplic
atio
ns, f
ram
ewor
ksan
d/or
crit
ical
cas
es fo
r co
mpo
sitio
ns
!In
timat
e m
ix o
f tas
k +
data
par
alle
lism
:�
Syst
olic
com
puta
tions
(sin
gle
parm
od, t
ask
+ da
ta p
aral
lelis
m)
�C
lass
ifica
tion,
clu
ster
ing
algo
rithm
s (g
raph
of p
arm
ods)
�U
ser p
rofil
ing
by d
ata
min
ing
(gra
phof
par
mod
s)�
Lang
uage
inte
rpre
ters
�K
now
ledg
e di
scov
ery
in s
emi-s
truct
ured
da
tase
ts(g
raph
of p
arm
ods)
!P
aral
lel e
xter
nal o
bjec
ts�
Dat
a re
posi
torie
s�
Web
cac
hing
�In
terf
aces
for l
egac
y SW
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e27
Exa
mpl
e: d
ata-
min
ing
C4.
5 as
a pa
ralle
lD&
C
Γ
Γ 2Γ
Γ 1T
Clie
nt
Tes
t
Div
ide
Con
quer
{tr
aini
ng se
t TS,
dec
isio
n tr
eeΓ
}
P 1
P N
For
load
bal
anci
ng:
"du
ring
som
e ph
ases
: Div
ide
wor
ksin
a d
ata-
para
llelm
anne
r,
"in
oth
er p
hase
s:
in a
farm
-like
m
anne
r,
"in
oth
er p
hase
s�
Shar
ed T
ree
obje
cts
expl
oite
d ef
ficie
ntly
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e28
Inte
rfac
e CR
M-D
B ->
DR CR
M-D
B(O
racl
e)
Selec
tion
Clas
sif
Ass
oc
Know
ledg
eRe
posi
tory
.(X
ML)
Inte
rfac
eLa
yout
Gen
erat
or
Cont
rol a
ndtu
ning
Inte
rfac
e D
R ->
CRM
-DB
Feed
back
A u
ser-
prof
iling
fram
ewor
k
Vis
ualiz
e
Clus
t
SA
IB p
roje
ct: M
IUR
L46
SE
MA
Sch
lum
berg
er, U
niv.
Pis
a, P
oly.
Turin
Dat
a Re
posito
ry(p
aral
lelf
ile s
yste
m)
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e29
Ext
erna
l obj
ects
: a n
eces
sary
feat
ure
for f
lexi
bilit
y
!In
tera
ctiv
e ap
plic
atio
ns!
Obj
ects
reus
e w
ith p
rimiti
ve A
PIs
!D
evic
es, f
iles,
Par
alle
lFile
Sys
tem
!D
ata
repo
sito
ries
!S
hare
d m
emor
y ob
ject
s!
AS
SIS
T pr
ogra
ms
them
selv
es
!C
ompo
sitio
n by
stre
ams
only
is n
ot s
uffic
ient
!To
war
ds C
ompo
nent
AS
SIS
T
{E
xter
nal O
bjec
ts}
M3
M5
M4
M1
M2
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e30
Exa
mpl
e: d
ata-
min
ing
C4.
5 as
a pa
ralle
lD&
C
Γ
Γ 2Γ
Γ 1T
Clie
nt
Tes
t
Div
ide
Con
quer
{tr
aini
ng se
t TS,
dec
isio
n tr
eeΓ
}
P 1
P N
Shar
ed T
ree
obje
cts
expl
oite
d ef
ficie
ntly
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e31
Stru
ctur
eof t
heAS
SIST
prog
ram
Inte
grat
ion
with
CO
RB
AC
ode
comp
ute(P
arMo
d)co
mpute
(Par
Mod)
sequ
entia
lcod
eloo
p co
ntrol
initia
lda
tasim
ulatio
nres
ults
CORB
Aint
erfac
e
Clien
t side
Serve
r side
Grafi
cal in
terfac
e
!N
-bod
y si
mul
atio
n!
GU
I CO
RB
A
serv
er!
para
llelc
lient
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e32
Par
t 2
AS
SIS
T
Flex
ible
Impl
emen
tatio
n M
odel
AS
SIS
T im
plem
enta
tion
[E
uroP
ar20
03, P
arC
o200
3]
Run
-tim
e su
ppor
tfor
clus
ter
arch
itect
ures
: on
top
of A
CE
libra
ryan
d di
strib
uted
sh
ared
mem
ory
(DVS
A)
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e34
Assi
stpr
ogra
m
parco.ast
Des
ign
patte
rns
base
d
Pars
erty
pech
eck
Modu
lebu
ilder
Code
build
er
Conf
igur
atio
nbu
ilder
façad
efro
nt-e
ndfa
ctor
y
conf
igfa
ctor
y
code
fact
ory
mod
ule
fact
ory
XML
conf
XML
conf
C++,
Make
file
C++,
Make
file
ASSI
STco
mpi
ler
> astccparco.ast
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e35
Exp
erim
entin
g w
ith e
xten
sion
s
1.Ta
rget
ing
hete
roge
neou
s C
OW
s
2.In
tegr
atin
g pa
ralle
l MP
I lib
rarie
s
3.A
ssis
tCon
fand
AS
SIS
T-G
: firs
t A
SS
IST
Grid
ver
sion
on
top
of G
lobu
s
Targ
eting
heter
ogen
eous
COW
s
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e37
Assi
stpr
ogra
m
parco.ast
Just
enr
ich
the
code
fact
ory
Pars
erty
pech
eck
Modu
lebu
ilder
Code
build
er
Conf
ig.
build
er
façad
efro
nt-e
ndfa
ctor
y
conf
igfa
ctor
y
code
fact
ory
mod
ule
fact
ory
ASSI
STco
mpi
ler
C++
C++
XML
conf
XML
conf
Make
file
OsX
Make
file
OsX
Make
file
Win
Make
file
Win
Code
build
er2
Add p
arall
el MP
I libr
aries
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e39
Assi
stpr
ogra
m
parco.ast
Just
enr
ich
the
mod
ule
fact
ory
Pars
erty
pech
eck
Modu
lebu
ilder
Code
build
er
Conf
ig.
build
er
façad
efro
nt-e
ndfa
ctor
y
conf
igfa
ctor
y
code
fact
ory
mod
ule
fact
ory
ASSI
STco
mpi
ler
C++
C++
XML
conf
XML
conf
MPI
build
er
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e40
MP
I int
egra
tion
[Euro
Mic
ro 2
003]
VP
VP
VP
VP
VP
VP
VP
VP
VP
MP
I wra
pper
0V
P
VP
VP
VP
VP
VP
VP
VP
VP
3
1 �
2 n
0 3�1
2 n0
3�
1 2n
parm
odpa
rmod
parm
od_M
PI
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e41
Assi
stpr
ogra
m
parco.ast
Ass
istC
onfa
nd A
SS
IST-
G: a
firs
t Grid
im
plem
enta
tion
on to
p of
Glo
bus
[E
uroM
icro
2003
]
Pars
erty
pech
eck
Modu
lebu
ilder
Code
build
er
Conf
ig.
build
er
façad
efro
nt-e
ndfa
ctor
y
conf
igfa
ctor
y
code
fact
ory
mod
ule
fact
ory
ASSI
STco
mpi
ler
C++
C++
XML
conf
XML
conf
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e42
XM
L co
nfig
urat
ion
file
!m
odul
es li
st (p
aral
lel a
ctiv
ities
)!
mod
ules
gra
ph!
path
nam
es, l
ib-n
ames
, cod
e-na
mes
!lib
-mod
ules
bin
ding
s
!m
achi
ne n
ames
!m
odul
es p
aral
lel d
egre
es!
mod
ules
-mac
hine
s m
appi
ng
stat
ic
dyna
mic
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e43
Assi
stpr
ogra
m
parco.ast
Just
enr
ich
the
conf
igfa
ctor
y
Pars
erty
pech
eck
Modu
lebu
ilder
Code
build
er
Conf
ig.
build
er
façad
efro
nt-e
ndfa
ctor
y
conf
igfa
ctor
y
code
fact
ory
mod
ule
fact
ory
ASSI
STco
mpi
ler
C++
C++
XML
conf
XML
conf
GRID
conf
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e44
AS
SIS
Tcon
f
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e45
AS
SIS
T-G
XMLc
onf
(sta
tic)
XMLc
onf
(sta
tic)
ASS
ISTc
onf
Pars
erty
pech
eck
Modu
lebu
ilder
Code
build
er
Conf
ig.
build
er
façad
efro
nt-e
ndfa
ctor
y
conf
igfa
ctor
y
code
fact
ory
mod
ule
fact
ory
ASSI
STco
mpi
ler
Pars
erty
pech
eck
Modu
lebu
ilder
Code
build
er
Conf
ig.
build
er
façad
efro
nt-e
ndfa
ctor
y
conf
igfa
ctor
y
code
fact
ory
mod
ule
fact
ory
ASSI
STco
mpi
ler
Pars
erty
pech
eck
Modu
lebu
ilder
Code
build
er
Conf
ig.
build
er
façad
efro
nt-e
ndfa
ctor
y
conf
igfa
ctor
y
code
fact
ory
mod
ule
fact
ory
ASSI
STco
mpi
ler
Pars
erty
pech
eck
Modu
lebu
ilder
Code
build
er
Conf
ig.
build
er
façad
efro
nt-e
ndfa
ctor
y
conf
igfa
ctor
y
code
fact
ory
mod
ule
fact
ory
ASSI
STco
mpi
ler
AS
SIS
T co
mpi
ler
reso
urce
sre
quire
men
ts
brok
erbr
oker
CLA
MC
LAM
MD
S
GR
IS/G
IIS
MD
S
GR
IS/G
IISG
RA
M
DU
RO
C
GR
AM
DU
RO
C
gath
er &
rese
rvat
ion
reso
urce
slib
sta
ging
allo
catio
n
XMLc
onf
stat
icdy
nam
ic
XMLc
onf
stat
icdy
nam
ic
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e46
Par
t 3
AS
SIS
T
Tow
ards
Grid
pro
gram
min
g
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e47
!M
IUR
�FI
RB
and
CN
R�
CN
R, I
NFN
, AS
I, C
NIT
, Uni
vers
ities
!B
asic
Res
earc
h P
rogr
amm
e -I
CT
�+
infra
stru
ctur
ean
d de
mon
stra
tors
(25%
)
!Ti
mef
ram
e: N
ovem
ber 2
002
�O
ctob
er 2
005
!To
tal C
ost:
11 M
��
othe
r syn
ergi
es b
y M
IUR
-CN
R P
roje
cts
on C
ompl
ex
Ena
blin
g P
latfo
rms:
2,5
M�
Grid
.it P
roje
ctE
nabl
ing
Pla
tform
s fo
rHig
h-pe
rform
ance
Com
puta
tiona
l Grid
s O
rient
ed to
S
cala
ble
Virt
ual O
rgan
izat
ions
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e48
Prog
ram
min
g En
viro
nmen
t
Hig
hH
igh --
leve
l ser
vice
sle
vel s
ervi
ces
Kno
wle
dge
serv
ices
Kno
wle
dge
serv
ices
, Dat
a , D
ata
base
sba
ses ,
, Sci
entif
ic li
brar
ies
Sci
entif
ic li
brar
ies ,
, Im
age
Imag
epr
oces
sing
, �pr
oces
sing
, �
Dom
ain-
spec
ific
Prob
lem
Sol
ving
Env
ironm
ents
(PS
Es)
Hig
hH
igh --
perf
orm
ance
, pe
rfor
man
ce, G
ridG
rid-- a
war
e co
mpo
nent
awar
e co
mpo
nent
-- bas
ed
base
d pr
ogra
mm
ing
prog
ram
min
gm
odel
and
m
odel
and
tool
sto
ols
Res
ourc
e Res
ourc
e m
anag
emen
t, P
erfo
rman
ce
man
agem
ent,
Per
form
ance
too
lsto
ols ,
, Se
curit
ySe
curit
y , V
O, �
, VO
, �
Nex
t N
ext
Gen
erat
ion
Gen
erat
ion
Mid
dlew
are
Mid
dlew
are
Bas
ic in
fras
truc
ture
-st
anda
rds(
OG
SA-c
ompl
iant
)
Sof
twar
e te
chno
logy
of G
rid.it
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e49
!D
ealin
g w
ith h
eter
ogen
eity
!N
ew c
ompi
lers
, run
-tim
e
supp
orts
, res
ourc
e
man
agem
ent
!S
ecur
e an
d fa
ult t
oler
ant
impl
emen
tatio
ns
!D
ynam
ic, a
dapt
ive
appl
icat
ions
!Im
plem
entin
g re
quire
men
ts
for Q
ualit
yof
Ser
vice
Crit
ical
rese
arch
issu
es
Focu
s of
this
Par
t
�P
rinci
ples
�P
erso
nal i
deas
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e50
Not
able
refe
renc
e: G
rAD
S P
roje
ct
!C
once
pt o
f rec
onfig
urab
le p
rogr
am�
Hig
h-le
vel f
orm
alis
m�
Hig
h-le
vel i
nfor
mat
ion
on a
pplic
atio
n re
quire
men
ts�
Com
pone
nts
tech
nolo
gy a
nd c
ompo
sitio
n of
ap
plic
atio
ns�
Per
form
ance
mod
el (�
nego
tiatio
n� a
t run
-tim
e)
!A
pplic
atio
nm
anag
er:
�se
t of s
tatic
and
dyn
amic
tool
s th
at c
ontro
l all
the
deve
lopm
ent-e
xecu
tion
cycl
e of
the
appl
icat
ion
(incl
udin
g dy
nam
ic re
stru
ctur
ing)
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e51
Grid
.it:
Grid
san
d st
ruct
ured
par
alle
l pro
gram
min
g
!A
pplic
atio
ns m
ay c
onta
in p
aral
lel c
ompo
nent
s�
in th
e si
mpl
est c
ase,
a p
aral
lel c
ompo
nent
is a
lloca
ted
to a
si
ngle
Grid
nod
e(c
lust
er, s
uper
com
pute
r),
�ad
vanc
emen
tin
netw
orki
ng te
chno
logy
: par
alle
lism
can
be
effe
ctiv
ely
expl
oite
dat
the
larg
e-sc
ale
leve
ltoo
.
#M
ore
in g
ener
al, a
nd m
ore
impo
rtant
:str
uctu
red
para
llelis
mis
a m
etho
dolo
gy fo
rdes
igni
ngan
d fo
r man
agin
ghi
gh-
perf
orm
ance
Gri
d-aw
are
appl
icat
ion
com
pone
nts a
ccor
ding
to
QoS
requ
irem
ents
.
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e52
Grid
.it a
ppro
ach:
hi
gh-p
erfo
rman
ce, G
rid-a
war
e co
mpo
nent
tech
nolo
gy
!Jo
inin
g co
mpo
nent
tech
nolo
gyan
dst
ruct
ured
par
alle
l pr
ogra
mm
ing
tech
nolo
gy�
to a
chie
vehi
gh-p
erfo
rman
ce, G
rid-a
war
e, c
ompo
nent
-bas
ed a
pplic
atio
ns
!Th
e intimat
e lin
k be
twee
n Gr
id p
rogr
amming
and
stru
ctur
ed p
arallel pr
ogra
mming
�St
ruct
ured
par
alle
l pro
gram
min
g as
a m
etho
dolo
gy to
enr
ich
the
com
pone
nt
mod
el w
ith f
eatu
res
able
to m
eet Q
oS re
quire
men
ts
�D
ynam
ical
ly m
odify
ing
the
allo
catio
n, re
plic
atio
n/ p
artit
ioni
ngof
the
appl
icat
ion
com
pone
nts,
in o
rder
to m
anta
inth
e pr
oper
deg
ree
of p
erfo
rman
ce, o
r in
orde
r to
sign
ifica
ntly
incr
ease
perfo
rman
ce w
hen
nece
ssar
y
�R
un-ti
me
expl
oita
tion
of th
e pe
rfor
man
ce m
odel
san
d im
plem
enta
tion
tem
plat
es (f
unda
men
tal f
eatu
re o
f str
uctu
red
para
llel p
rogr
amm
ing)
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e53
!�C
ontr
act�
asso
ciat
ed to
eve
ry c
ompo
nent
(inte
rface
), de
finin
g po
ssib
le a
pplic
atio
n re
quire
men
ts:
�pe
rform
ance
, fau
lt to
lera
nce,
�
!E
very
con
tract
is s
peci
fied
by m
eans
a st
ruct
ured
par
alle
lpro
gram
�us
ing
the
ASS
IST
mod
el
!In
itial
con
figur
atio
n: e
stab
lishe
dat
com
pile
-tim
e
!A
t run
-tim
e, th
e pe
rfor
man
ce m
odel
is u
sed
to m
odify
the
conf
igur
atio
nof
the
com
posi
tion
(in a
par
amet
ricm
anne
r):
�re
plic
atio
n, p
artit
ioni
ng, s
ched
ulin
g po
licy,
dis
tribu
tion
of d
ata,
�
(all
are
prog
ram
min
g co
nstru
cts
in A
SS
IST)
�ex
ploi
ting
mon
itorin
g, p
rofil
ing,
per
form
ance
mod
elin
g, re
sour
cem
anag
emen
t and
info
rmat
ion
serv
ices
Idea
s fo
rGrid
-aw
are
com
pone
nts
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e54
Exa
mpl
e: a
n �a
dapt
ive
pipe
line�
Gen
erat
or
of o
bjec
ts
stre
am
Gen
Obj
ects
tra
nsfo
rmat
ion
by fu
nctio
n F2
F2
Obj
ects
tra
nsfo
rmat
ion
by fu
nctio
n F3
F3
Obj
ects
tra
nsfo
rmat
ion
by fu
nctio
n F1
F1
Dat
a in
tens
ive,
Gr
id m
emor
y hi
erar
chy
inte
rfac
e
�By
def
ault
: se
quen
tial
impl
emen
tati
on.
�O
n re
stru
ctur
ing:
fa
rmim
plem
enta
tion
,
�nu
mbe
rof
wor
kers
de
term
ined
dy
nam
ical
ly.
�By
def
ault
: dat
a-pa
ralle
l im
plem
enta
tion
onto
a sing
le p
arallelno
de.
�O
n re
stru
ctur
ing:
the
nu
mbe
rof
par
titi
ons
may
be
vari
ed a
nd
allo
cate
d on
to
diff
eren
t no
des.
A s
trea
mpa
ralle
l+
data
par
alle
lco
mpo
siti
on
map
ped
onto
a
sing
le
para
llel
node
.
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e55
Com
pone
nt-s
truct
ured
app
licat
ion
Farm
(initi
ally
se
q)D
ata
para
llel+
Far
m
Dat
a pa
ralle
l Ste
ncil
Dat
a-in
tens
ive
Stre
am
Gen
erat
or
A sn
apsh
otof
th
e ev
olut
ion
of
our a
dapt
ive
appl
icat
ion
at a
ce
rtain
time.
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e56
Com
pone
nt-s
truct
ured
app
licat
ion
A p
ossi
ble
re-
allo
catio
n:
acco
rdin
g to
th
e ou
tcom
eof
th
e pe
rfor
man
ce
mod
el, s
ome
data
-par
alle
lpa
rtiti
onsa
nd
the
farm
co
llect
orca
n be
re
-allo
cate
d on
to d
iffer
ent
node
s.
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e57
Com
pone
nt-s
truct
ured
app
licat
ion
Rec
onfig
urat
ion
of th
e fa
rm
com
pone
nt:
mor
e w
orke
rsar
e re
quire
d to
gr
ant t
he n
eede
d de
gree
of
perf
orm
ance
.
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e58
Com
pone
nt-s
truct
ured
app
licat
ion
Rec
onfig
urat
ion
of th
e da
ta-
para
llel
com
pone
nt: m
ore
part
ition
sare
re
quire
d to
gra
nt
the
need
ed d
egre
e of
per
form
ance
.
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e59
Com
pone
nt-s
truct
ured
app
licat
ion
Abs
trac
tion
of
Mem
ory
Hiera
rchy
Abs
trac
tion
of
Shar
ed O
bjec
ts
Sche
dulin
g an
d co
nfig
urat
ion
of
com
plex
, hig
h-vo
lum
e da
ta fl
ows
thro
ugh
mul
tiple
le
vels
of
hier
arch
y
Dat
a-in
tens
ive
appl
icat
ions
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e60
Dat
a-in
tens
ive
com
puta
tions
in A
SS
IST
Obj
ect(
poss
ibly
hig
h-ba
ndw
idth
)A
bstra
ctio
nof
hi
gh-
perf
orm
ance
ob
ject
scan
be
impl
emen
ted
by
ASS
IST
parm
od(s
), w
ith p
rope
r in
terf
ace
(exp
ress
ed in
A
SSIS
T or
ano
ther
fo
rmal
ism
)
VP
VP
VP
VP
VP
VP
VP
VP
VP
Inpu
t Se
ctio
nO
utpu
t Se
ctio
n
ASSI
STpa
rmod
fort
he h
igh-
perf
orm
ance
abs
tract
ion
of O
bjec
t
Exte
rnal
Obj
ect I
nter
face
(pos
sibl
y pa
ralle
l)
Than
ks to
ASS
IST
grou
p �
Dep
artm
ent
of C
ompu
ter
Scie
nce,
Uni
v. o
f Pi
sa:
M.A
ldin
ucci
, S.C
ampa
, P.C
iullo
, M. C
oppo
la, M
.Dan
elut
to, S
.Mag
ini,
S.
Moi
, A
.Pa
tern
esi,
P.Pe
sciu
llesi
, A
.Pe
troce
lli,
E.Pi
stol
etti,
L.
Potit
i, R
.R
avaz
zolo
, M.T
orqu
ati,
G.V
irdis
, P. V
itale
, C.Z
occo
lo
ISTI
-CN
R g
roup
, Pis
a:D
omen
ico
Lafo
renz
a, S
alva
tore
Orla
ndo
(Uni
v. o
f V
enic
e), R
affa
ele
Pere
go, N
icol
a To
nello
tto, R
anie
ri B
arag
lia
Than
k yo
u fo
r atte
ntio
n
ASS
IST
-Mar
co V
anne
schi
-E
uroP
VM
/MPI
200
3, V
enic
e63
Cur
rent
vi
ew
Hig
h-le
vel v
iew
of G
ridap
plic
atio
ns
App
licat
ion
Bas
ic H
W+S
W p
latfo
rm
Mid
dlew
are
It is
not n
eces
saril
yth
e sa
me
Mid
dlew
are
�as b
efor
e�: i
t sho
uld
be d
efin
ed a
nd
real
ized
acc
ordi
ng to
the
need
s of t
he
Prog
ram
min
g En
viro
nmen
t.
�H
igh-
leve
l lan
guag
es,
com
posi
tion
alit
y, m
odul
arit
y a
nd
inte
rope
rabi
lity
�Co
mpi
ling
Tool
s�
Run
Tim
e Su
ppor
t�
Perf
orm
ance
Mod
el (C
ost
Mod
el)
for
stat
ic a
nd d
ynam
ic
opti
miz
atio
ns�
Dev
elop
men
t, lo
adin
g, e
xecu
tion
, m
onit
orin
g,�,
rec
onfi
guri
ng t
ools
Mid
dlew
are
⇒Gr
id A
bstr
act
Mac
hine
Prog
ram
min
g En
viro
nmen
tX
