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A Theoretical Framework for Value Prediction in Parallel Systems

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3 Author(s)

We present here a theoretical framework towards a fundamental understanding of the effects of value prediction. Our framework consists of two parts: first, an identification of the theoretical limit of value prediction and an indication of the potential to improve parallelism through the exploitation of value predictability; second, a demonstration of the feasibility of data prediction and a theoretical support to verify this feasibility. The experiment results demonstrate the immense potential of value prediction in enhancing the performance of many-core architectures.

Published in:

Parallel Processing (ICPP), 2010 39th International Conference on

Date of Conference:

13-16 Sept. 2010