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DAC2023顶会

AutoDCIM: An Automated Digital CIM Compiler

Jia Chen, Fengbin Tu, Kunming Shao, Fengshi Tian, Xiao Huo, Chi-Ying Tsui, Kwang-Ting Cheng

2023年份
24被引次数
2顶会引用

摘要

Digital Computing-in-Memory (DCIM) is an emerging architecture that integrates digital logic into memory for efficient AI computing. However, current DCIM designs heavily rely on manual efforts. This increases DCIM design time and limits the optimization space, making it challenging to satisfy the user specifications of diverse AI applications. This paper presents AutoDCIM, the first automated DCIM compiler. Au-toDCIM takes the user specifications as inputs and generates a DCIM macro architecture with an optimized layout. AutoDCIM’s template-based generation balances handcrafted cell design and agile macro development. AutoDCIM’s layout exploration loop analyzes diverse DCIM array partitioning schemes to satisfy user specifications. The auto-generated DCIM macros present competitive efficiency results in comparison with state-of-the-art silicon-verified DCIM macros.

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