On Consistency for Bulk-Bitwise Processing-in-Memory
Ben Perach, Ronny Ronen, Shahar Kvatinsky
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%.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
它引用的顶会 Paper5
- RecNMP: Accelerating Personalized Recommendation with Near-Memory ProcessingLiu Ke, Udit Gupta, Benjamin Youngjae Cho, David Brooks 等ISCA 2020 · 被引用 235 次
- TRiM: Enhancing Processor-Memory Interfaces with Scalable Tensor Reduction in MemoryJaehyun Park, Byeongho Kim, Sungmin Yun, Eojin Lee 等MICRO 2021 · 被引用 70 次
- RACER: Bit-Pipelined Processing Using Resistive MemoryMinh S. Q. Truong, Eric Chen, Deanyone Su, Liting Shen 等MICRO 2021 · 被引用 40 次
- MOUSE: Inference In Non-volatile Memory for Energy Harvesting ApplicationsSalonik Resch, S. Karen Khatamifard, Zamshed I. Chowdhury, Masoud Zabihi 等MICRO 2020 · 被引用 37 次
- OrderLight: Lightweight Memory-Ordering Primitive for Efficient Fine-Grained PIM ComputationsAnirban Nag, Rajeev BalasubramonianMICRO 2021 · 被引用 7 次
相关 Paper
- SHERLOCK: Scheduling Efficient and Reliable Bulk Bitwise Operations in NVMsHamid Farzaneh, João Paulo C. de Lima, Ali Nezhadi Khelejani, Asif Ali Khan 等DAC 2024 · 被引用 2 次
- Max-PIM: Fast and Efficient Max/Min Searching in DRAMFan Zhang, Shaahin Angizi, Deliang FanDAC 2021 · 被引用 10 次
- WISEDRAM: A Reliable Bitwise In-DRAM AcceleratorMohammad Arman Soleimani, Nezam Rohbani, Adrián Cristal Kestelman, Osman S. Unsal 等DAC 2025 · 被引用 1 次
- Accelerating Transactional Execution via Processing-In-MemoryAndré Lopes, Daniel Castro, Paolo RomanoEuroSys 2026
- A Case Study of Processing-in-Memory in off-the-Shelf SystemsJoel Nider, Craig Mustard, Andrada Zoltan, John Ramsden 等USENIX ATC 2021 · 被引用 62 次
