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Every Bit Counts -- Compressed Main Memory Architectures

Mattan Erez – Professor, University of Texas at Austin

Thu, 1-Dec-2022 / 2:00pm / Zoom Only

Zoom Link

https://stanford.zoom.us/j/93195368904?pwd=VFdBT0FyQk1wbjJ3VmhoaUhIS0E2QT09

Abstract

Memory capacity, bandwidth, and reliability are all critical for overall system capabilities and performance, but providing these is increasingly expensive with the cost of main memory going up year by year as a fraction of overall system cost. Memory compression offers an opportunity to reduce cost by increasing effective capacity and/or bandwidth without installing additional memory devices. Compressing main memory, however, is challenging and requires compression techniques that are low latency, effective at fine access granularities of just 32 - 128B, and can be implemented with low storage and bandwidth overheads. I will discuss some of the specific concerns related to compression techniques for main memory, including the concept of coverage-oriented compression. Coverage-oriented compression seeks to maximize the number of blocks that can be compressed to a certain size (with possibly low compression ratio), rather than maximizing overall compression ratio. Coverage-oriented compression is useful when the goal of compression is to provide a relatively small amount of additional capacity and bandwidth, e.g., to replace additional components used to provide out-of-band memory for ECC or other metadata.

Bio

Bio: Mattan Erez is a Professor at the Department of Electrical and Computer Engineering at the University of Texas at Austin. His research focuses on improving the performance, efficiency, and scalability of computing systems through advances in memory systems, hardware architecture, software systems, and programming models. His current focus areas are architectures for machine learning, large-scale and high-performance computing, and memory systems. Mattan received a BSc in Electrical Engineering and a BA in Physics from the Technion, Israel Institute of Technology and his MS and PhD. in Electrical Engineering from Stanford University. He was awarded a Presidential Early Career Award for Scientists and Engineers from President Obama.