Exploiting Inter-block Entropy to Enhance the Compressibility of Blocks with Diverse Data

Abstract

As higher memory bandwidth is required for data-intensive environments, memory compression can be a simple but effective solution to increase memory bandwidth. However, previous infra-block compression techniques do not provide sufficient bandwidth improvement owing to the incompressibility of blocks with diverse data while previous inter-block compression techniques suffer from huge additional memory access overheads or low compression coverages. To overcome the limitations of the previous intra-and inter-block compression techniques, we leverage both the naturally observed low-entropy among blocks and the artificially generated low-entropy resulting from our optimization techniques. Based on these two low-entropies, we propose an Entropy-based Pattern Compression (EPC), which generates an inter-block pattern from the same low-entropy region in numerous blocks and then compresses these blocks by using the selected pattern. Our evaluations show that EPC achieves up to 13% (3% on average) higher speedup and 13% (4% on average) DRAM energy consumption reduction with 160x (20x on average) fewer patterns(groups) compared to the state-of-the-art inter-block compression technique.