CAMASim: A Comprehensive Simulation Framework for Content-Addressable Memory based Accelerators
<|reference_start|>CAMASim: A Comprehensive Simulation Framework for Content-Addressable Memory based Accelerators: 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.<|reference_end|>
@article{li2024camasim:,
    title={CAMASim: A Comprehensive Simulation Framework for Content-Addressable
  Memory based Accelerators},
    author={Mengyuan Li, Shiyi Liu, Mohammad Mehdi Sharifi, X. Sharon Hu},
    journal={arXiv preprint arXiv:2403.03442},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.03442},
    primaryClass={cs.AR}
}