Value prediction is a technique that bypasses inter-instruction data
dependencies by speculating on the outcomes of producer instructions,
thereby allowing dependent consumer instructions to execute in
parallel. This work makes several contributions in value prediction
research. A hybrid value predictor that achieves an overall prediction
rate of up to 83% is presented. The design of a value-predicting
eight-wide superscalar machine with its speculative execution core is
described. This design is able to achieve 8.6% to 23% IPC improvements
on the SPEC benchmarks. Furthermore, it is shown that prediction rate
is not a good indicator of speedup because over 40% of predictions
made may not be useful in enhancing performance, and a simple hardware
mechanism that eliminates many of these useless predictions is
introduced.

									 
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The author's web site:

<a href="http://www.ece.cmu.edu/~cmuart/">www.ece.cmu.edu/~cmuart/</a>