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Low-power Task Scheduling for GPU Energy Reduction

Low-power Task Scheduling for GPU Energy Reduction. Li Tang, Yiji Zhang. Introduction. DVFS (dynamic voltage and frequency scaling) i mplementation Building GPU linear regression power model. DVFS implementation. D ynamic V oltage and F requency S caling

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Low-power Task Scheduling for GPU Energy Reduction

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  1. Low-power Task Scheduling for GPU Energy Reduction Li Tang, Yiji Zhang

  2. Introduction • DVFS (dynamic voltage and frequency scaling) implementation • Building GPU linear regression power model

  3. 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

  4. GPU architecture and linear regression power model • GPU linear power model: On-chip Device Memory Total power Maximum power of the i-th component Usage rate of the i-th components Intercept power

  5. Energy measurement • NI USB-6216 DAQ+ two FLUKE 80i-110s current clamps • Sampling rate: • 10 readings per millisecond

  6. 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

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