Branch prediction techniques for low-power VLIW processors
Gianluca Palermo, Maxwell Sam, C. Silvan, V. Zaccari, R. Zafalo
Abstract
Gianluca Palermo, Maxwell Sam, C. Silvan, V. Zaccari, R. Zafalo
Abstract
Main goal of the paper is to introduce a branch prediction scheme suitable for energy-efficient VLIW (Very Long Instruction Word) processors aiming at reducing the energy associated with the prediction phase by filtering the accesses to the branch predictor block. To analyze the effectiveness of the proposed low-power branch prediction scheme, we combined it to some well-known dynamic branch prediction techniques suitable for VLIW processors. Experimental results have been carried out on Lx, a 4-issue VLIW architecture with 6-stage pipeline. The proposed solution implies a performance improvement of 7% on average and an average energy reduction of 15%.
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Main goal of the paper is to introduce a branch prediction scheme suitable for energy-efficient VLIW (Very Long Instruction Word) processors aiming at reducing the energy associated with the prediction phase by filtering the accesses to the branch predictor block. To analyze the effectiveness of the proposed low-power branch prediction scheme, we combined it to some well-known dynamic branch prediction techniques suitable for VLIW processors. Experimental results have been carried out on Lx, a 4-issue VLIW architecture with 6-stage pipeline. The proposed solution implies a performance improvement of 7% on average and an average energy reduction of 15%.
Key concepts: Very long instruction word, Computer science, Pipeline (software), Branch predictor, Superscalar, Parallel computing, Block (permutation group theory), Reduction (mathematics)