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CPU-GPU Collaboration for Output Quality Monitoring CPU-GPU Collaboration for Output Quality Monitoring

CPU-GPU Collaboration for Output Quality Monitoring - PowerPoint Presentation

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Uploaded On 2016-03-06

CPU-GPU Collaboration for Output Quality Monitoring - PPT Presentation

Mehrzad Samadi and Scott Mahlke University of Michigan March 2014 Compilers creating custom processors University of Michigan Electrical Engineering and Computer Science Output Quality Monitoring ID: 243951

toq quality delta monitoring quality toq monitoring delta check cpu gpu approximate output sampling applications adaptive fixed run conservative

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Slide1

CPU-GPU Collaboration for Output Quality Monitoring

Mehrzad Samadi and Scott MahlkeUniversity of MichiganMarch 2014

Compilers creating custom processors

University of Michigan

Electrical Engineering and Computer ScienceSlide2

Output Quality Monitoring

Sampling over timeGreen[PLDI2010], SAGE[MICRO2013] Works fine for applications with temporal similarity for example video processing What about applications without temporal similarity?QualityTOQ

TOQ + delta

TOQ - delta

Check the qualitySlide3

Output Quality Monitoring

Sampling over time

Sampling over spaceSlide4

Partial Output Quality Monitoring

Accurate VersionApproximate

Version

Evaluation

Metric

Subset of

Input DataSlide5

CCG

Collaborative CPU-GPU Output Quality MonitoringApproximate Run 0GPUCPU

Approximate Run 1

Approximate

Run 2Approximate

Run 3

Check 1

Check

2

Check 3

Check

4

Decision

Decision

Decision

CPU performs the monitoring while GPU is executing the approximate codeSlide6

Evaluation

Two Image processing applications: Mosaic Mean Filter 1600 flower images NVIDIA GTX 560 + Intel Core i7 CCG: Collaborative CPU-GPU approachTime SamplingConservative

Aggressive

Adaptive

Fixed

Adaptive

Fixed

CFI

CAI

A

FI

A

AISlide7

Conservative/ Aggressive

QualityTOQ

TOQ + delta

TOQ - delta

Speedup

Conservative

AggressiveSlide8

ResultsSlide9

Conclusions

Sampling over time is not the answer for all applications We need to check all invocations for most of the applications Full quality monitoring has really high overhead Partial quality monitoring can be a solution9Slide10

CPU-GPU Collaboration for Output Quality Monitoring

Mehrzad Samadi and Scott MahlkeUniversity of MichiganMarch 2014

Compilers creating custom processors

University of Michigan

Electrical Engineering and Computer ScienceSlide11

Fixed/Adaptive Fixed

Adaptive: Reduce the overhead of checking.QualityTOQ

TOQ + delta

TOQ - delta

Quality

TOQ

TOQ + delta

TOQ - deltaSlide12

Results