SCHEDULE: NOV 12-18, 2011

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GROPHECY: GPU Performance Projection from CPU Code Skeletons

SESSION: GPU Optimizations

EVENT TYPE: Paper

TIME: 11:30AM - 12:00PM

AUTHOR(S):Jiayuan Meng, Vitali Morozov, Kalyan Kumaran, Venkatram Vishwanath, Thomas Uram

ROOM:TCC 303

ABSTRACT:
We propose a GPU projection framework that can estimate the performance benefit of GPU acceleration without actual GPU programming or hardware. Users only need to skeletonize pieces of CPU code that are targets for GPU acceleration. The framework will then transform the code skeleton in various ways to mimic tuned GPU code with characteristics resembling real implementations. The synthesized characteristics are used by an existing analytical model to project GPU performance. The cost and benefit of GPU development can then be estimated according to the transformed code skeleton that yields the best projected performance. With this framework, users can leap towards GPU acceleration only when the cost-benefit makes sense. We validate the framework using micro-benchmarks as well as data-parallel codes in legacy high performance computing applications. The measured performance of manually tuned codes deviates from the projected performance by 17% in geometric mean.

Chair/Author Details:

Jiayuan Meng - Argonne National Laboratory

Vitali Morozov - Argonne National Laboratory

Kalyan Kumaran - Argonne National Laboratory

Venkatram Vishwanath - Argonne National Laboratory

Thomas Uram - Argonne National Laboratory

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The full paper can be found in the ACM Digital Library