RelaxCIM: A Power- and Area-Efficient RxO-based Readout Cell for ADC-less CIM Accelerators
Year: 2025
Type: conference-paper
Abstract: Compute-In-Memory (CIM) architectures are becoming standard solutions for accelerating AI workloads. Yet, the performance of analog CIM cores is generally constrained by the quantization resolution and energy consumption of the readout stage, typically dominated by Analog-to-Digital Converters (ADCs). To address this issue, we present RelaxCIM, a compact, low-power readout approach that replaces traditional resource-intensive ADCs with a Relaxation Oscillator (RxO) and a digital counter for current-based CIM accelerators. Implemented in 65 nm CMOS, each RxO-based cell occupies $0.0015 \mathrm{~mm}^{2}$, consumes an average power of 0.21 mW, and achieves a resolution of 100 nA per Least-Significant Bit (LSB) at a 100 MHz counting frequency. This fine resolution is particularly beneficial for large neural networks mapped onto small CIM arrays employing time-multiplexed Vector-Matrix Multiplication (VMM) and partialsum operations, effectively reducing quantization errors and finite-precision limitations.
Institution: Aalto University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Funder: Academy of Finland
OpenAlex ID: W4415399850
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