Low-power Task Scheduling for GPU Energy ReductionLi Tang, Yiji Zhang

Introduction

•DVFS (dynamic voltage and frequency scaling) implementation

•Building GPU linear regression power model

DVFS implementation•Dynamic Voltage and Frequency Scaling

a method to provide variable amount of energy for a task by scaling the operating voltage/frequency.

•Power & Energy consumption

•

GPU architecture and linear regression power model

On-chip

Device Memory

• GPU linear power model:

Total power Maximum power

of the i-th component

Usage rate of the i-th components

Intercept power

Energy measurement

• NI USB-6216 DAQ+ two FLUKE 80i-110s current clamps

• Sampling rate:▫ 10 readings per millisecond

Preliminary results

• WAXPY function:▫ W[i]=alpha*X[i]+beta*Y[i] (i: thread number)

• Kernel launch:▫ WAXPY<<<num_blocks, num_threads>>>

• Vector size and type:▫ 1,000,000 float

Thread*Block 1*1 1*4 1*16 1*64 4*64 16*64 64*16

WAXPY Time 44.053 11.529 3.503 1.056 0.266 0.070 = 0.071

WAXPY GPU Power 31.878 33.872 43.263 59.015 57.223 63.709 > 48.098

WAXPY GPU Energy 1404.298 390.498 151.542 62.298 15.195 4.466 3.415