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GBDI: Going Beyond Base-Delta-Immediate Compression with Global Bases

Alexandra Angerd, Angelos Arelakis, Vasilis Spiliopoulos, Erik Sintorn, Per Stenström

2022Year
13Citations
4Top-tier citations

Abstract

Memory bandwidth is limiting performance for many emerging applications. While compression techniques can unlock a higher memory bandwidth, prior art offers only modestly better bandwidth. This paper contributes with a new compression method – Global Base Delta Immediate compression (GBDI) – that offers substantially higher memory bandwidth by, unlike prior art, selecting base values across memory blocks. GBDI uses a novel clustering algorithm through data analysis in the background. The presented accelerator infrastructure offers low area overhead and latency. This paper shows that GBDI offers a compression ratio of 2.3×, and yields 1.5× higher bandwidth and 1.1× higher performance compared with a baseline without compression support, on average, for SPEC2017 benchmarks requiring medium to high memory bandwidth.

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