Attaché: Towards Ideal Memory Compression by Mitigating Metadata Bandwidth Overheads

Abstract

Memory systems are becoming bandwidth constrained and data compression is seen as a simple technique to increase their effective bandwidth. However, data compression requires accessing Metadata which incurs additional bandwidth overheads. Even after using a Metadata-Cache, the bandwidth overheads of Metadata can reduce the benefits of compression. This paper proposes Attache, a framework that reduces the overheads of Metadata accesses. The Attache framework consists of two components. The first component, called the Blended Metadata Engine (BLEM), enables data and its Metadata to be accessed together. BLEM incurs additional Metadata accesses only 0.003% times and removes almost all Metadata bandwidth overheads. The second component, called the Compression Predictor (COPR), predicts if the memory block is compressed. The COPR predictor uses a fine-grained line-level predictor, a coarse-grained page-level predictor, and a global indicator. This enables Attache to predict the compressibility of the memory block before sending a memory read request. We implement Attache on a memory system that uses Sub-Ranking. On average, Attache achieves 15.3% speedup (ideal 17%) and saves 22% energy consumption (ideal 23%) when compared to a baseline system that does not employ data compression. Attache is completely hardware-based and uses only 368KB of SRAM.