In-DRAM Bulk Bitwise Execution Engine
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Abstract (arXiv)
Many applications heavily use bitwise operations on large bitvectors as part of their computation. In existing systems, performing such bulk bitwise operations requires the processor to transfer a large amount of data on the memory channel, thereby consuming high latency, memory bandwidth, and energy. In this paper, we describe Ambit, a recently-proposed mechanism to perform bulk bitwise operations completely inside main memory. Ambit exploits the internal organization and analog operation of DRAM-based memory to achieve low cost, high performance, and low energy. Ambit exposes a new bulk bitwise execution model to the host processor. Evaluations show that Ambit significantly improves the performance of several applications that use bulk bitwise operations, including databases.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 May 2019.
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Citing papers per year: 2022: 4; 2023: 1; 2024: 1.
6 papers.
- 2022Machine Learning Training on a Real Processing-in-Memory Systemcited by 4
- 2022Accelerating Neural Network Inference with Processing-in-DRAM: From the Edge to the Cloudcited by 4
- 2022An Experimental Evaluation of Machine Learning Training on a Real Processing-in-Memory Systemcited by 2
- 2022Heterogeneous Data-Centric Architectures for Modern Data-Intensive Applications: Case Studies in Machine Learning and Databasescited by 1
- 2023TransPimLib: A Library for Efficient Transcendental Functions on Processing-in-Memory Systemscited by 1
- 2024SwiftRL: Towards Efficient Reinforcement Learning on Real Processing-In-Memory Systemscited by 1
- 2024SwiftRL: Towards Efficient Reinforcement Learning on Real Processing-In-Memory Systems7 May 2024
- 2023TransPimLib: A Library for Efficient Transcendental Functions on Processing-in-Memory Systems3 Apr 2023
- 2022Accelerating Neural Network Inference with Processing-in-DRAM: From the Edge to the Cloud19 Sep 2022
- 2022An Experimental Evaluation of Machine Learning Training on a Real Processing-in-Memory System16 Jul 2022
- 2022Machine Learning Training on a Real Processing-in-Memory System13 Jun 2022
- 2022Heterogeneous Data-Centric Architectures for Modern Data-Intensive Applications: Case Studies in Machine Learning and Databases29 May 2022