A Theoretical Framework for Value Prediction in Parallel Systems

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 exploitatio...

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Bibliographic Details
Main Authors: Shaoshan Liu, Eisenbeis, C, Gaudiot, Jean-Luc
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Entropy
Equations
Mathematical model
Parallel processing
Redundancy
Synchronization
Online Access:Request full text
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Summary: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.
ISSN:0190-3918
2332-5690
DOI:10.1109/ICPP.2010.10