Exceeding the dataflow limit via value prediction
Proceedings of the 29th annual ACM/IEEE international symposium on Microarchitecture
Can program profiling support value prediction?
MICRO 30 Proceedings of the 30th annual ACM/IEEE international symposium on Microarchitecture
Highly accurate data value prediction using hybrid predictors
MICRO 30 Proceedings of the 30th annual ACM/IEEE international symposium on Microarchitecture
Efficacy and Performance Impact of Value Prediction
PACT '98 Proceedings of the 1998 International Conference on Parallel Architectures and Compilation Techniques
Latency and energy aware value prediction for high-frequency processors
ICS '02 Proceedings of the 16th international conference on Supercomputing
IEEE Transactions on Computers
Value Prediction as a Cost-Effective Solution to Improve Embedded Processors Performance
VECPAR '00 Selected Papers and Invited Talks from the 4th International Conference on Vector and Parallel Processing
Hybridizing and Coalescing Load Value Predictors
ICCD '00 Proceedings of the 2000 IEEE International Conference on Computer Design: VLSI in Computers & Processors
A Power Perspective of Value Speculation for Superscalar Microprocessors
ICCD '00 Proceedings of the 2000 IEEE International Conference on Computer Design: VLSI in Computers & Processors
Receiving message prediction method
Parallel Computing - Special issue: Parallel and distributed scientific and engineering computing
On the energy-efficiency of speculative hardware
Proceedings of the 2nd conference on Computing frontiers
Improving memory system performance with energy-efficient value speculation
ACM SIGARCH Computer Architecture News - Special issue: dasCMP'05
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Value prediction is as yet a very novel technique, whose efficiency has still to be proved. To take advantage of this emerging technique in the short term it is essential to design accurate and low cost value predictors. This work presents a new approach of implementing hybrid predictors that allows the maximum sharing of information between predictors. We show that the new hybrid predictor outperforms not only the accuracy of the others predictors, but also their hardware utilization.