PICO-RAM: A PVT-Insensitive Analog Compute-In-Memory SRAM Macro With In Situ Multi-Bit Charge Computing and 6T Thin-Cell-Compatible Layout
Analog compute-in-memory (CIM) in static random access memory (SRAM) is promising for accelerating deep learning inference by circumventing the memory wall and exploiting ultra-efficient analog low-precision arithmetic. Latest analog CIM designs attempt bit-parallel (BP) schemes for multi-bit analog matrix-vector multiplication (MVM), aiming at higher energy efficiency, throughput, and training simplicity and robustness over conventional bit-serial (BS) methods that digitally shift-and-add multiple partial analog computing results. However, BP operations require more complex analog computations and become more sensitive to well-known analog CIM challenges, including large cell areas, inefficient and inaccurate multi-bit analog operations, and vulnerability to PVT variations. This article presents PICO-RAM, a PVT-insensitive and compact CIM SRAM macro with charge-domain BP computation. It adopts a multi-bit thin-cell multiply-accumulate (MAC) unit that shares the same transistor layout as the most compact 6T SRAM cell. All analog computing modules, including digital-to-analog converters (DACs), MAC units, analog shift-and-add, and analog-to-digital converters (ADCs), reuse one set of local capacitors inside the array, performing in situ computation to save area and enhance accuracy. A compact 8.5-bit dual-threshold time-domain ADC power gates the main path most of the time, leading to a significant energy reduction. Our 65-nm prototype achieves the highest weight storage density of 559 Kb/mm2 and exceptional robustness to temperature and voltage variations (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${-} 40~^{\circ } $ </tex-math></inline-formula> C to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$105~{^{\circ }}$ </tex-math></inline-formula> C and 0.65 to 1.2 V) among SRAM-based analog CIM designs.
Authors
- Yubei Chen (ORCID: https://orcid.org/0000-0002-8930-3512)
- Wei-Chen Wei (ORCID: https://orcid.org/0000-0002-7642-3005)
- Akhil Pakala (ORCID: https://orcid.org/0000-0002-0570-4993)
- Yiwei Zou (ORCID: https://orcid.org/0009-0008-2949-5672)
- Zhiyu Chen (ORCID: https://orcid.org/0000-0002-1321-1793)
- Kaiyuan Yang (ORCID: https://orcid.org/0000-0001-7220-9389)
- Weier Wan (ORCID: https://orcid.org/0000-0003-3507-9014)
- Zihao Li (ORCID: https://orcid.org/0009-0009-1747-5735)
- Ziyuan Wen (ORCID: https://orcid.org/0000-0002-7081-0725)
Institutions
- Apple (United States) (US)
- Rice University (US)
Publication Details
- Journal
- IEEE Journal of Solid-State Circuits
- Published
- 2024-08-13
- DOI
- https://doi.org/10.1109/jssc.2024.3422826
- Citations
- 17
- Primary Topic
- Semiconductor materials and devices
- Type
- article
- Field-Weighted Citation Impact
- 3.55