CAMASim: A Comprehensive Simulation Framework for Content-Addressable Memory based Accelerators

TL;DR

CAMASim is a comprehensive simulation framework that facilitates the design, analysis, and optimization of CAM-based accelerators across various applications, addressing challenges in accuracy, hardware cost, and versatility.

Contribution

It introduces CAMASim, a modular and flexible simulation framework that models CAM accelerators at circuit level, enabling detailed design space exploration and performance prediction.

Findings

Establishes detailed design space for CAM accelerators

Automates functional simulation for accuracy assessment

Predicts hardware performance using circuit-level modeling

Abstract

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.