OpenGCRAM: An Open-Source Gain Cell Compiler Enabling Design-Space Exploration for AI Workloads

TL;DR

OpenGCRAM is an open-source compiler that streamlines the design and optimization of GCRAM memory systems, enabling rapid, customizable, and process-compliant memory block generation for AI accelerators.

Contribution

It introduces a comprehensive GCRAM compiler that automates circuit design, layout, and simulation, significantly reducing design time and enhancing customization for diverse workloads.

Findings

Automates GCRAM circuit and layout generation

Provides accurate area, delay, and power estimations

Ensures process compliance and design flexibility

Abstract

Gain Cell memory (GCRAM) offers higher density and lower power than SRAM, making it a promising candidate for on-chip memory in domain-specific accelerators. To support workloads with varying traffic and lifetime metrics, GCRAM also offers high bandwidth, ultra low leakage power and a wide range of retention times, which can be adjusted through transistor design (like threshold voltage and channel material) and on-the-fly by changing the operating voltage. However, designing and optimizing GCRAM sub-systems can be time-consuming. In this paper, we present OpenGCRAM, an open-source GCRAM compiler capable of generating GCRAM bank circuit designs and DRC- and LVS-clean layouts for commercially available foundry CMOS, while also providing area, delay, and power simulations based on user-specified configurations (e.g., word size and number of words). OpenGCRAM enables fast, accurate, customizable, and optimized GCRAM block generation, reduces design time, ensure process compliance, and delivers performance-tailored memory blocks that meet diverse application requirements.