Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging...

43
0 0 0 University of Michigan Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor Mudge, Ronald Dreslinski *University of Michigan, Ann Arbor The 3 rd International Workshop on Parallelism in Mobile Platforms (PRISM-3) Jun 14, 2015

Transcript of Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging...

Page 1: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

0 0

0

0 University of Michigan

Leveraging Mobile GPUs for Flexible High-speed Wireless Communication

Qi Zheng, Cao Gao, Trevor Mudge, Ronald Dreslinski *University of Michigan, Ann Arbor

The 3rd International Workshop on Parallelism in Mobile Platforms

(PRISM-3) Jun 14, 2015

Page 2: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

1 1

1

1 University of Michigan

Popular Mobile Device & Applications

Page 3: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

2 2

2

2 University of Michigan

1.0E-01

1.0E+00

1.0E+01

1.0E+02

1.0E+03

2000 2004 2008 2010

Fast Technology Evolution

Page 4: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

3 3

3

3 University of Michigan

Support of Multiple Standards

Page 5: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

4 4

4

4 University of Michigan

Wireless Processor in Mobile Devices !  Hardware accelerator based processors

!  ASIC !  DSP with many ASICs !  FPGA customized as ASICs

" High performance " High energy efficiency

Software-defined Radio!

✕ Long time to market ✕ Hard and costly to maintain compatibility

Page 6: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

5 5

5

5 University of Michigan

Software-defined Radio (SDR) ! Wireless system is implemented entirely in software

!  General-purpose programming language

" Very short time to market •  Only implement new software for new technologies

" Easy to maintain compatibility •  Different programs for different standards

?  Performance ?  Energy efficiency

Page 7: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

6 6

6

6 University of Michigan

Processor for SDR

!  Good programmability

!  High computing throughput

!  High energy efficiency

!  Explore DLP and TLP

GPU!

Page 8: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

7 7

7

7 University of Michigan

Desktop GPU Power ≥ 100W

Graphics Processing Unit (GPU) !  High throughput:

!  GOPS-level peak throughput

!  SIMT execution model ! Make use of abundant DLP and TLP

!  Good programming support !  CUDA/OpenCL

Mobile GPU Power ~ 1W

Page 9: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

8 8

8

8 University of Michigan

Our Contribution !  Parallel implementations of LTE baseband kernels on a mobile

GPGPU

!  Performance of running LTE baseband ! Meet the specification peak data rate for physical layer kernels !  Get close to 10Mpbs typical data rate with for the Turbo decoder ! Meet 20ms latency budget

!  Power and energy efficiency of a mobile GPGPU !  High power compared with application-specific processors !  Still in an acceptable range !  Implications of GPU architecture to further reduce the power

Page 10: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

9 9

9

9 University of Michigan

Outline ! Motivation

!  LTE baseband kernels !  Running LTE baseband on a mobile GPGPU

!  Implications for future mobile GPGPUs

!  Conclusion

Page 11: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

10 10

10

10 University of Michigan

LTE Baseband Downlink Receiver !  Downlink Receiver has the most computations in a mobile device

RF# OFDM#Demodula.on#

MIMO##Detect#

Channel#Es.mate#

Modula.on#Demapper#Descrambling#Rate#

Match#Turbo#

Decoder#

Antenna

PHY Layer kernel MAC Layer kernel Radio

Page 12: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

11 11

11

11 University of Michigan

Parallelism in Each Kernel !  The PHY layer kernels

!  Antenna-level !  Symbol-level !  Subcarrier-level !  Algorithm-level

!  The Turbo Decoder !  Trellis-level !  Subblock-level

!  For all kernels !  Batch multiple packets

Page 13: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

12 12

12

12 University of Michigan

Outline ! Motivation

!  LTE baseband kernels !  Running LTE baseband on a mobile GPGPU

! Methodology !  PHY layer !  Turbo decoder !  Power and energy efficiency

!  Implications for future mobile GPGPUs

!  Conclusion

Page 14: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

13 13

13

13 University of Michigan

Experimental Setup !  Jetson TK1 Board

!  NVIDIA 4-Plus-1™ quad-core ARM® Cortex-A15 CPU

!  NVIDIA Kepler GK20a GPU

! 192 CUDA cores

! ≤ 852MHz

! 256 KB RF / 64 KB L1 memory / 128 KB L2 cache

!  2G DDR3L RAM (shared by CPU and GPU)

! Wattsup.net Power Meter !  33% board power consumed by SoC

Page 15: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

14 14

14

14 University of Michigan

Outline ! Motivation

!  LTE baseband kernels !  Running LTE baseband on a mobile GPGPU

! Methodology !  PHY layer !  Turbo decoder !  Power and energy efficiency

!  Implications for future mobile GPGPUs

!  Conclusion

Page 16: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

15 15

15

15 University of Michigan

PHY Layer Throughput

Packet batching increases throughput Saturate at 8

0 20 40 60 80

100 120 140 160 180 200

0 5 10 15 20 25 30 35

Ach

ieve

d Th

roug

hput

s (M

bps)

The number of packets 1x1+QPSK 2x2+QPSK 1x1+16QAM 2x2+16QAM

Page 17: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

16 16

16

16 University of Michigan

Compare with Specification Peak

0.0#

1.0#

2.0#

3.0#

4.0#

5.0#

6.0#

7.0#

0# 1# 2# 3# 4# 5# 6# 7#

Throughp

ut#Normalized

#to#

Specifica>o

n#Pe

ak#

The#number#of#packets#

1x1+QPSK# 2x2+QPSK# 1x1+16QAM# 2x2+16QAM#

Fulfill all but one specification peak data rates Overall, 2 packets -- a good batching size

Page 18: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

17 17

17

17 University of Michigan

0.0#

2.0#

4.0#

6.0#

8.0#

10.0#

12.0#

14.0#

16.0#

18.0#

0# 1# 2# 3# 4# 5# 6# 7# 8# 9#

Throughp

ut#Normalized

#to#

Average/Typical#U

ser#R

ate#

The#number#of#packets#

1x1+QPSK# 2x2+QPSK# 1x1+16QAM# 2x2+16QAM#

Compare with 10Mbps Typical Rate

Fulfill all typical user data rates

Page 19: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

18 18

18

18 University of Michigan

0 10 20 30 40 50 60 70 80 90

0 5 10 15 20 25 30 35 Wor

st C

ase

Late

ncy

(ms)

The number of packets

1x1+QPSK 2x2+QPSK 1x1+16QAM 2x2+16QAM

PHY Layer Latency

Packet batching also increases latency Packet batching also increases latency, can batch ≤ 8 packets given 20ms budgets

Page 20: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

19 19

19

19 University of Michigan

Outline ! Motivation

!  LTE baseband kernels !  Running LTE baseband on a mobile GPGPU

! Methodology !  PHY layer !  Turbo decoder !  Power and energy efficiency

!  Implications for future mobile GPGPUs

!  Conclusion

Page 21: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

20 20

20

20 University of Michigan

Turbo Throughput

0"

2"

4"

6"

8"

10"

0" 2" 4" 6" 8" 10" 12" 14" 16" 18"

Turbo"De

coding"

Throughp

ut"(M

bps)"

The"number"of"packets"#Subblock=16" #Subblock=32" #Subblock=64"

Throughput increases with #subblocks an batching sizes

*Qi Zheng, et al, “Parallelization Techniques for Implementing Trellis Algorithms on Graphics Processors”, ISCAS 2013, Beijing

32 subblocks + 2 packets: 8.4 Mpbs throughput, 4.8 ms latency <<peak rate, but ~10Mbp typical rate

Page 22: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

21 21

21

21 University of Michigan

Outline ! Motivation

!  LTE baseband kernels !  Running LTE baseband on a mobile GPGPU

! Methodology !  PHY layer !  Turbo decoder !  Power and energy efficiency

!  Implications for future mobile GPGPUs

!  Conclusion

Page 23: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

22 22

22

22 University of Michigan

Energy Efficiency

Higher frequency achieves better energy efficiency – “Run to finish”

0.0

5.0

10.0

15.0

20.0

25.0

30.0

72 252 468 684 852

Ene

rgy

Effi

cien

cy (M

b/J)

GPU Frequency (MHz)

Page 24: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

23 23

23

23 University of Michigan

Power Consumption

Processor Standards Details

ASIC (LeoCore) WiMAX 70mW@ 70MHz

FPGA (MAGALI) LTE 234mW@400MHz

DSP (Tomahawk) LTE, WiMAX 904mW@170MHz

CPU (SoftLTE) LTE [email protected]

Mobile GPU LTE 1390mW@852MHz

Page 25: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

24 24

24

24 University of Michigan

Outline ! Motivation

!  LTE baseband kernels !  Running LTE baseband on a mobile GPGPU

!  Implications for future mobile GPGPUs

!  Conclusion

Page 26: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

25 25

25

25 University of Michigan

Reduce Energy from Unused Register !  Register file is underutilized running PHY layers

!  Due to max_thread/SM and max_thread_block/SM

!  Power gate unused registers

0%#10%#20%#30%#40%#50%#60%#70%#80%#90%#100%#

1# 2# 4# 8# 16#

Normalized

#RF#U:liza:

on#

The#number#of#packets#

1x1+QPSK# 2x2+QPSK# 1x1+16QAM# 2x2+16QAM#

Page 27: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

26 26

26

26 University of Michigan

!  Trellis Algorithm !  Turbo algorithm !  Viterbi algorithm !  Baum-Welch algorithm !  Coding theory !  Speech recognition !  Data compression

!  Architecture and ISA support !  Similar to AES instruction set in Intel CPU

GPU Support for Trellis Algorithm

Page 28: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

27 27

27

27 University of Michigan

Outline ! Motivation

!  LTE baseband kernels !  Running LTE baseband on a mobile GPGPU

!  Implications for future mobile GPGPUs

!  Conclusion

Page 29: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

28 28

28

28 University of Michigan

Conclusion ! Mobile GPUs can be used for wireless communication in a

mobile device ! Meet specification peaks for 3 out of 4 PHY configurations ! Meet the typical rate for all PHY configurations !  Turbo is close to the typical data rate

!  Need special supports for the Turbo decoder in a mobile GPU

!  Energy is high compared with application-specific solutions !  But in the accepting range !  Need further optimizations

Page 30: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

29 29

29

29 University of Michigan

Thanks!

Any questions?

Page 31: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

30 30

30

30 University of Michigan

Backup Slides

Page 32: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

31 31

31

31 University of Michigan

Quick Subscription Growth

0

1000

2000

3000

4000

5000

6000

7000

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Wor

ld m

obile

-cel

lula

r sub

scrip

tions

(M

illio

ns)*

Year

*ITU report -- The World in 2011: ICT Facts and Figures

Page 33: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

32 32

32

32 University of Michigan

Our Contribution !  Parallel implementations of LTE baseband kernels on a mobile

GPGPU

!  Throughputs and latency of different configurations

!  Energy efficiency of a mobile GPGPU

Page 34: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

33 33

33

33 University of Michigan

Parallelism in PHY Layer Kernels Kernel Parallelism Number of threads

OFDM Modulation

(FFT)

Antenna-level Symbol-level

Algorithm-level

Channel Estimation

Antenna-level Subcarrier-level

MIMO detector Symbol-level Subcarrier-level

Modulation demapper

Antenna-level Symbol-level

Subcarrier-level Algorithm-level

Descrambling Antenna-level Symbol-level

Subcarrier-level

Nant ×Nsym ×NFFT

Nant ×Nsub

Nsym ×Nsub

Nant ×Nsym ×Nsub ×NMod

Nant ×Nsym ×Nsub × log2(NMod )

Nant ×Nsym ×Nsub

Page 35: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

34 34

34

34 University of Michigan

Parallelism in Turbo Decoder* !  Total number of threads

!  Implementation performance tradeoff

Nthread = N packet ⋅Nsubblock ⋅Threadtrellis

Parallelism Scheme Throughput Latency Bit Error Rate

Packet-level Better Worse No Change

Subblock-level Better No Change Worse

Trellis-level Better No Change No Change

Subblock+NII Worse No Change Better

Subblock+TS Worse No Change Better

*Qi Zheng, et al, “Parallelization Techniques for Implementing Trellis Algorithms on Graphics Processors”, ISCAS 2013, Beijing

Page 36: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

35 35

35

35 University of Michigan

Mobile GPU Architecture !  GPU on NVIDIA Jetson Tegra K1 board

!  Kepler architecture – 192 CUDA cores@852 MHz !  64KB L1 memory / 128KB L2 cache / Share 2GB DDR3L with CPU

Page 37: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

36 36

36

36 University of Michigan

Performance Metrics !  Collected stats for a variety of important events !  CUDA Event API

!  Throughput !  Latency

!  NVIDIA Profiler !  Achieved occupancy ! Memory utilization !  Dynamic instruction count

Page 38: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

37 37

37

37 University of Michigan

GPU Occupancy

Packet batching increases throughput… which saturates at 8 packets due to full GPU utilization

0%#10%#20%#30%#40%#50%#60%#70%#80%#90%#100%#

0# 2# 4# 6# 8# 10# 12# 14# 16# 18#

Achieved

#Occup

ancy#

The#number#of#packets#

1x1+QPSK# 2x2+QPSK# 1x1+16QAM# 2x2+16QAM#

0"20"40"60"80"

100"120"140"160"180"200"

0" 5" 10" 15" 20" 25" 30" 35"

Achieved

"Throu

ghpu

ts"(M

bps)"

The"number"of"packets"

1x1+QPSK" 2x2+QPSK" 1x1+16QAM" 2x2+16QAM"

Page 39: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

38 38

38

38 University of Michigan

Hotspot Analysis

0%#10%#20%#30%#40%#50%#60%#70%#80%#90%#100%#

1x1+QPSK#

2x2+QPSK#

1x1+16QAM#

2x2+16QAM#

Execu9

on#Tim

e#Breakd

own#

Rate#Matching#

Descrambling#

Demodula9on#

MIMO#Detec9on#

Channel#Es9ma9on#

FFT#

Demodulation dominates due to its heavy computation

Page 40: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

39 39

39

39 University of Michigan

Hotspot Analysis -- #instructions

Demodulation dominates due to its heavy computation

0%#10%#20%#30%#40%#50%#60%#70%#80%#90%#

100%#

1x1+QPSK(

2x2+QPSK(

1x1+16QAM(

2x2+16QAM(

Executed

(Instruc7on

s(

Rate(Matching(

Descrambling(

Demodula7on(

MIMO(Detec7on(

Channel(Es7ma7on(

FFT(

Page 41: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

40 40

40

40 University of Michigan

Turbo Throughput

0"

2"

4"

6"

8"

10"

0" 2" 4" 6" 8" 10" 12" 14" 16" 18"

Turbo"De

coding"

Throughp

ut"(M

bps)"

The"number"of"packets"#Subblock=16" #Subblock=32" #Subblock=64"

Throughput increases with the number of subblocks and packets, and starts saturating at 64 subblocks

Page 42: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

41 41

41

41 University of Michigan

Frequency Scaling -- PHY

0 5

10 15 20 25 30 35 40 45

0 100 200 300 400 500 600 700 800 900

Ach

ieve

d Th

roug

hput

(M

bps)

GPU Frequency (MHz)

1x1+QPSK 2x2+QPSK 1x1+16QAM 2x2+16QAM

Throughputs have almost linear scaling with the frequency

Page 43: Leveraging Mobile GPUs for Flexible High-speed Wireless ...caogao/prism_3_talk.pdf · Leveraging Mobile GPUs for Flexible High-speed Wireless Communication Qi Zheng, Cao Gao, Trevor

42 42

42

42 University of Michigan

Frequency Scaling -- Turbo

Throughputs have almost linear scaling with the frequency

0.0#

1.0#

2.0#

3.0#

4.0#

5.0#

6.0#

7.0#

8.0#

9.0#

0# 100# 200# 300# 400# 500# 600# 700# 800# 900#

Achieved

#Throu

ghpu

t#(Mbp

s)#

GPU#Frequency#(MHz)#