gpu power model nandhini sudarsanan [email protected]@umn.edu nathan vanderby...

22
GPU Power Model Nandhini Sudarsanan [email protected] Nathan Vanderby [email protected] Neeraj Mishra [email protected] Usha Vinodh [email protected] Chi Xu [email protected]

Upload: dora-stanley

Post on 20-Jan-2016

232 views

Category:

Documents


0 download

TRANSCRIPT

Page 1: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

GPU Power Model

Nandhini Sudarsanan [email protected] Vanderby [email protected]

Neeraj Mishra [email protected] Vinodh [email protected]

Chi Xu [email protected]

Page 2: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

Outline

• Introduction and Motivation• Analytical Model Description• Experiment Setup• Results• Conclusion and Further Work

Page 3: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

Introduction

Page 4: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

Motivation

Page 5: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

Outline

• Introduction and Motivation• Analytical Model Description

o Parser o Power Model

• Experiment Setup• Results• Conclusion and Further Work

Page 6: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

Parser

Page 7: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

Outline

• Introduction and Motivation• Analytical Model Description

o Parser o Power Model

• Experiment Setup• Results• Conclusion and Further Work

Page 8: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

Power Model

• PTX Level

Page 9: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

Power Model

• Assembly Level

Page 10: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

Outline

• Introduction and Motivation• Analytical Model Description

o Parser o Power Model

• Experiment Setup• Results• Conclusion and Further Work

Page 11: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

Experiment Setup - Hardware

• Measure Power Consumption and Temperatureo Current Clamp for PCIE & GPU Power Cable

Data Acquisition Card @ 100Hzo GPU Performance Countero Sample Temperature @ 10Hz, GPU sensor

Page 12: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

Experiment Setup - Software

• Driver API• Generate and Modify PTX code

o Minimize control loops• CUDA 4.0

o Built in Binary -> Assembly Converter (cuobjdump)• MATLAB to build model• Remote login

Page 13: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

CUDA- Fermi Architecture

• Third Generation Streaming Multiprocessor(SM)o 32 CUDA cores per SM, 4x over GT200o 1024 thread block size, 2x over GT200o Unified address space enables full C++ supporto  Improved Memory Subsystem

Page 14: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

Benchmarks

• Small number of overhead operations (loop counters, initialization, etc.).

• Computational intensive work  to allow for an experiment of significant length for accurate  current measurement.

• Exhibit high utilization of the CUDA cores, few data hazards as possible.

• Grid and block sizes appropriately so that all SM are used, since idle SM leak.

•  Accordingly 7 benchmarks were selected from CUDA SDK.

Page 15: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

Benchmarks

For this project we tested out a few benchmarks.• 2D convolution• Matrix Multipication• Vector Addition• Vector Reduction• Scalar Product• DCT 8x8• 3DFD

Page 16: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu
Page 17: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

Limitations of PTX

• Higher level than assemblyo Divide & Sqrt: 1 PTX line, library in assembly

• Compiler optimizations from PTX -> assembly• Doesn’t reflect RAW dependencies• Performance counters use assembly

Page 18: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

Outline

• Introduction and Motivation• Analytical Model Description

o Parser o Power Model

• Experiment Setup• Results• Conclusion and Further Work

Page 19: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

Results

Page 20: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

Outline

• Introduction and Motivation• Analytical Model Description

o Parser o Power Model

• Experiment Setup• Results• Conclusion and Further Work

Page 21: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

Conclusion and Further Work

• Conclusion

• Further Worko Take into account context switcheso Consider Multiple kernels running simultaneously

Page 22: GPU Power Model Nandhini Sudarsanan sudar003@umn.edusudar003@umn.edu Nathan Vanderby vande501@umn.edu Neeraj Mishra mish0088@umn.edu Usha Vinodh kuma0253@un.edu

The End

Thanks

Q&A