基于区域协作的Cache压缩

The Cache compression based on region cooperation

为提高Cache的有效容量,进行了Cache压缩研究,并提出了一种区域协作压缩(RCC)方法,以提升最后一级缓存的压缩率。与传统的Cache压缩算法不同,RCC方法利用了缓存区域的压缩局部性,使用缓存区域中第一个缓存块的字典信息来协作压缩缓存区域中的其他各个缓存块,而不需要对缓存区域进行整体压缩。RCC有效发掘了缓存区域内缓存块之间的数据冗余,实现了接近以缓存区域为压缩粒度的字典压缩的压缩率,然而压缩、解压缩延时却仍然和压缩单个缓存块时相当。实验结果表明,与单缓存块压缩算法C-PACK相比,RCC方法的压缩率平均提升了12.34%,系统的性能提升了5%。与2倍容量的非压缩Cache相比,有效容量提升了27%,系统性能提升了8.6%,而面积却减少了63.1%。

The Cache compression was studied to increase Cache＇ s effective capacity, and a region cooperative compression （RCC） algorithm was proposed to improve the compression ratio of the last level Cache. Different to traditional Cache compression algorithms, the RCC algorithm exploits the compression locality to compress Cache blocks in a Cache region by the cooperation of the first block in the region, instead of compressing the whole Cache region. RCC effectively explores the duplications across the Cache blocks in a Cache region and shows a comparable com- pression ratio with dictionary compression approaches with the whole Cache region as the compression granularity, whereas the （de）compression latency is not increased. The experimental results show that RCC provides the better average compression ratio than the compression algorithm of C-PACK by 12.34%, which causes the performance improvement of 5%. Compared to the non-compressive Cache with double size, the effective capacity increases by 27%, the performance increases by 8.6% and the area decreases by 63.1%.