Tag RAM

Abstract: A flash-memory system provides solid-state mass storage as a replacement to a hard disk. A unified re-map table in a RAM is used to arbitrarily re-map all logical addresses from a host system to physical addresses of flash-memory devices. Each entry in the unified re-map table contains a physical block address (PBA) of the flash memory allocated to the logical address, and a cache valid bit and a cache index. When the cache valid bit is set, the data is read or written to a line in the cache pointed to by the cache index. A separate cache tag RAM is not needed. When the cache valid bit is cleared, the data is read from the flash memory block pointed to by the PBA. Two write count values are stored with the PBA in the table entry. A total-write count indicates a total number of writes to the flash block since manufacture. An incremental-write count indicates the number of writes since the last wear-leveling operation that moved the block. Wear-leveling is performed on a block being written when both total and incremental counts exceed system-wide total and incremental thresholds. The incremental-write count is cleared after a block is wear-leveled, but the total-write count is never cleared. The incremental-write count prevents moving a block again immediately after wear-leveling. The thresholds are adjusted as the system ages to provide even wear.

Abstract: High performance general-purpose processors are increasingly being used for a variety of application domains - scientific, engineering, databases, and more recently, media processing. It is therefore important to ensure that architectural features that use a significant fraction of the on-chip transistors are applicable across these different domains. For example, current processor designs often devote the largest fraction of on-chip transistors (up to 80%) to caches. Many workloads, however, do not make effective use of large caches; e.g., media processing workloads which often have streaming data access patterns and large working sets.This paper proposes a new reconfigurable cache design. This design enables the cache SRAM arrays to be dynamically divided into multiple partitions that can be used for different processor activities. These activities can benefit applications that would otherwise not use the storage allocated to large conventional caches. Our design involves relatively few modifications to conventional cache design, and analysis using a modification of the CACTI analytical model shows a small impact on cache access time. We evaluate one representative use of reconfigurable caches - instruction reuse for media processing. We find this use gives IPC improvements ranging from 1.04X to 1.20X in simulation across eight media processing benchmarks.

Abstract: 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.