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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.

read1 min views1 publishedSep 12, 2026
Exploring denser on-chip AI memory with two-transistor gain cells
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  [Submitted on 24 Feb 2026]


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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.

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