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HPCA2023顶会

On Consistency for Bulk-Bitwise Processing-in-Memory

Ben Perach, Ronny Ronen, Shahar Kvatinsky

2023年份
6被引次数

摘要

Processing-in-memory (PIM) architectures allow software to explicitly initiate computation in the memory. This effectively makes PIM operations a new class of memory operations, alongside standard memory operations (e.g., load, store). For software correctness, it is crucial to have ordering rules for a PIM operation with other PIM operations and other memory operations, i.e., a consistency model that takes into account PIM operations is vital. To the best of our knowledge, little attention to PIM operation consistency has been given in existing works. In this paper, we focus on a specific PIM approach, named bulk-bitwise PIM. In bulk-bitwise PIM, large bitwise operations are performed directly and stored in the memory array. We show that previous solutions for the related topic of maintaining coherency of bulk-bitwise PIM have broken the host native consistency model and prevent any guaranteed correctness. As a solution, we propose and evaluate four consistency models for bulk-bitwise PIM, from strict to relaxed. Our designs also preserve coherency between PIM and the host processor. Evaluating the proposed designs’ performance with a gem5 simulation, using the YCSB short-range scan benchmark and TPC-H queries, shows that the run time overhead of guaranteeing correctness is at most 6%, and in many cases the run time is even improved. The hardware overhead of our design is less than 0.22%.

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