Many modern computer systems, including homogeneous and heterogeneous architectures, support shared memory in hardware. In a shared memory system, each of the processor cores may read and write to a single shared address space. For a shared memory machine, the memory consistency model defines the architecturally visible behavior of its memory system. Consistency definitions provide rules about loads and stores (or memory reads and writes) and how they act upon memory. As part of supporting a memory consistency model, many machines also provide cache coherence protocols that ensure that multiple cached copies of data are kept up-to-date. The goal of this primer is to provide readers with a basic understanding of consistency and coherence. This understanding includes both the issues that must be solved as well as a variety of solutions. We present both high-level concepts as well as specific, concrete examples from real-world systems.
This second edition reflects a decade of advancements since the first edition and includes, among other more modest changes, two new chapters: one on consistency and coherence for non-CPU accelerators (with a focus on GPUs) and one that points to formal work and tools on consistency and coherence.
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Vijay Nagarajan is a Reader at the School of Informatics at the University of Edinburgh. He received a Ph.D. in Computer Science from University of California, Riverside. His research interests span computer architecture, compilers, and computer systems with a focus on memory consistency models and cache coherence protocols. He is a recipient of the Intel early career faculty honour award, a PACT best paper award, and an IEEE Top Picks honorable mention. He has served (or is currently serving) on multiple program committees including ISCA, MICRO, and HPCA. He was General Chair of LCTES 2017 and is currently serving as an Associate Editor of IEEE Computer Architecture Letters (IEEE CAL).
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