On-line data compression is a new alternative technique for improving memory system performance, which can increase both the effective memory space and the bandwidth of memory systems. However, decompression time accompanied by accessing compressed data may offset the benefits of compression. In this paper, a selectively compressed memory system (SCMS) based on a combination of selective compression and hiding of decompression overhead is proposed and analyzed. The architecture of an efficient compressed cache and its management policies are presented. Analytical modeling shows that the performance of SCMS is influenced by the compression efficiency, the percentage of references to the compressed data block, and the percentage of references found in the decompression buffer. The decompression buffer plays the most important role in improving the performance of the SCMS. If the decompression buffer can filter more than 70% of the references to the compressed blocks, the SCMS can significantly improve performance over conventional memory systems.
All Science Journal Classification (ASJC) codes
- Hardware and Architecture
- Computer Networks and Communications
- Artificial Intelligence