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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2403.03442 |
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| _version_ | 1866916151799316480 |
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| author | Li, Mengyuan Liu, Shiyi Sharifi, Mohammad Mehdi Hu, X. Sharon |
| author_facet | Li, Mengyuan Liu, Shiyi Sharifi, Mohammad Mehdi Hu, X. Sharon |
| contents | Content addressable memory (CAM) stands out as an efficient hardware solution for memory-intensive search operations by supporting parallel computation in memory. However, developing a CAM-based accelerator architecture that achieves acceptable accuracy, while minimizing hardware cost and catering to both exact and approximate search, still presents a significant challenge especially when considering a broader spectrum of applications. This complexity stems from CAM's rapid evolution across multiple levels--algorithms, architectures, circuits, and underlying devices. This paper introduces CAMASim, a first comprehensive CAM accelerator simulation framework, emphasizing modularity, flexibility, and generality. CAMASim establishes the detailed design space for CAM-based accelerators, incorporates automated functional simulation for accuracy, and enables hardware performance prediction, by leveraging a circuit-level CAM modeling tool. This work streamlines the design space exploration for CAM-based accelerator, aiding researchers in developing effective CAM-based accelerators for various search-intensive applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_03442 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | CAMASim: A Comprehensive Simulation Framework for Content-Addressable Memory based Accelerators Li, Mengyuan Liu, Shiyi Sharifi, Mohammad Mehdi Hu, X. Sharon Hardware Architecture Content addressable memory (CAM) stands out as an efficient hardware solution for memory-intensive search operations by supporting parallel computation in memory. However, developing a CAM-based accelerator architecture that achieves acceptable accuracy, while minimizing hardware cost and catering to both exact and approximate search, still presents a significant challenge especially when considering a broader spectrum of applications. This complexity stems from CAM's rapid evolution across multiple levels--algorithms, architectures, circuits, and underlying devices. This paper introduces CAMASim, a first comprehensive CAM accelerator simulation framework, emphasizing modularity, flexibility, and generality. CAMASim establishes the detailed design space for CAM-based accelerators, incorporates automated functional simulation for accuracy, and enables hardware performance prediction, by leveraging a circuit-level CAM modeling tool. This work streamlines the design space exploration for CAM-based accelerator, aiding researchers in developing effective CAM-based accelerators for various search-intensive applications. |
| title | CAMASim: A Comprehensive Simulation Framework for Content-Addressable Memory based Accelerators |
| topic | Hardware Architecture |
| url | https://arxiv.org/abs/2403.03442 |