Publications

Dynamic Rank Subsetting with Data Compression

Journal of the Korea Society of Computer and Information, Volume 25 Issue 4, pp.1-9, 2020

  • Seokin Hong

Abstract

In this paper, we propose Dynamic Rank Subsetting (DRAS) technique that enhances the energy-efficiency and the performance of memory system through the data compression. The goal of this technique is to enable a partial chip access by storing data in a compressed format within a subset of DRAM chips. To this end, a memory rank is dynamically configured to two independent sub-ranks. When writing a data block, it is compressed with a data compression algorithm and stored in one of the two sub-ranks. To service a memory request for the compressed data, only a sub-rank is accessed, whereas, for a memory request for the uncompressed data, two sub-ranks are accessed as done in the conventional memory systems. Since DRAS technique requires minimal hardware modification, it can be used in the conventional memory systems with low hardware overheads. Through experimental evaluation with a memory simulator, we show that the proposed technique improves the performance of the memory system by 12% on average and reduces the power consumption of memory system by 24% on average.

Keywords

  • Memory System
  • DRAM
  • Data Compression
  • Performance
  • Power