Exploring denser on-chip AI memory with two-transistor gain cells

Researchers submitted a paper to arXiv on 24 Feb 2026 introducing OpenGCRAM, a memory compiler that supports both SRAM and Gain Cell RAM (GCRAM) and generates macro-level designs and layouts for commercial CMOS processes. The compiler characterizes area, delay, and power across user-defined configurations, enabling systematic identification of optimal heterogeneous on-chip memory configurations for AI tasks. GCRAM offers higher density, lower power, and tunable retention, expanding the design space beyond conventional SRAM as memory increasingly dominates system cost and energy.

Computer Science Hardware Architecture Submitted on 24 Feb 2026 Title:Heterogeneous Memory Design Exploration for AI Accelerators with a Gain Cell Memory Compiler View PDF /pdf/2602.21278 HTML experimental https://arxiv.org/html/2602.21278v1 Abstract:As memory increasingly dominates system cost and energy, heterogeneous on-chip memory systems that combine technologies with complementary characteristics are becoming essential. Gain Cell RAM GCRAM offers higher density, lower power, and tunable retention, expanding the design space beyond conventional SRAM. To this end, we create an OpenGCRAM compiler supporting both SRAM and GCRAM. It generates macro-level designs and layouts for commercial CMOS processes and characterizes area, delay, and power across user-defined configurations. The tool enables systematic identification of optimal heterogeneous memory configurations for AI tasks under specified performance metrics. Current browse context: cs.AR References & Citations Loading... Bibliographic and Citation Tools Bibliographic Explorer What is the Explorer? https://info.arxiv.org/labs/showcase.html arxiv-bibliographic-explorer Connected Papers What is Connected Papers? https://www.connectedpapers.com/about Litmaps What is Litmaps? https://www.litmaps.co/ scite Smart Citations What are Smart Citations? https://www.scite.ai/ Code, Data and Media Associated with this Article alphaXiv What is alphaXiv? https://alphaxiv.org/ CatalyzeX Code Finder for Papers What is CatalyzeX? https://www.catalyzex.com DagsHub What is DagsHub? https://dagshub.com/ Gotit.pub What is GotitPub? http://gotit.pub/faq Hugging Face What is Huggingface? https://huggingface.co/huggingface ScienceCast What is ScienceCast? https://sciencecast.org/welcome Demos Recommenders and Search Tools Influence Flower What are Influence Flowers? https://influencemap.cmlab.dev/ CORE Recommender What is CORE? https://core.ac.uk/services/recommender arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs https://info.arxiv.org/labs/index.html .