Set-associative caches achieve low miss rates for typical applications but result in significant energy dissipation. Set-associative caches minimize access time by probing all the data ways in parallel with the tag lookup, although the output of only the matching way is used. The energy spent accessing the other ways is wasted. Eliminating the wasted energy by performing the data lookup sequentially following the tag lookup substantially increases cache access time, and is unacceptable for high-performance L1 caches. In this paper, we apply two previously-proposed techniques, way-prediction and selective direct-mapping, to reducing L1 cache dynamic energy while maintaining high performance. The techniques predict the matching way and probe only the predicted way and not all the ways, achieving energy savings. While these techniques were originally proposed to improve set-associative cache access times, this is the first paper to apply them to reducing cache energy. We evaluate the effectiveness of these techniques in reducing L1 d-cache, L1 i-cache, and overall processor energy. Using these techniques, our caches achieve the energy-delay of sequential access while maintaining the performance of parallel access. Relative to parallel access L1 i-and d-caches, the techniques achieve overall processor energy-delay reduction of 8%, while perfect way-prediction with no performance degradation achieves 10% reduction. The performance degradation of the techniques is less than 3%, compared to an aggressive, 1-cycle, 4-way, parallel access cache.

Abstract-Process parameter variations are expected to be significantly high in a sub-50-nm technology regime, which can severely affect the yield, unless very conservative design techniques are employed. The parameter variations are random in nature and are expected to be more pronounced in minimum geometry transistors commonly used in memories such as SRAM. Consequently, a large number of cells in a memory are expected to be faulty due to variations in different process parameters.In this paper, we analyze the impact of process variation on the different failure mechanisms in SRAM cells. We also propose a process-tolerant cache architecture suitable for high-performance memory. This technique dynamically detects and replaces faulty cells by dynamically resizing the cache. It surpasses all the contemporary fault tolerant schemes such as row/column redundancy and error-correcting code (ECC) in handling failures due to process variation. Experimental results on a 64-K direct map L1 cache show that the proposed technique can achieve 94% yield compared to its original 33% yield (standard cache) in a 45-nm predictive technology under inter = intra = 30 mV.

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