Analog computing

PERCEL: A Re-Writable NVM CIM Incorporating a CTT-Based Per-Cell DAC

PERCEL: A Re-Writable NVM CIM Incorporating a CTT-Based Per-Cell DAC 150 150

Abstract:

Compute in memory (CiM) accelerators perform matrix vector multiplications (MVMs) directly inside memory arrays, reducing data movement and improving both energy efficiency and throughput for AI workloads. To reduce the number of conversions, recent designs use multi-bit compute cells. Nevertheless, practical multi-bit CiM still faces a tension between accuracy, efficiency, …

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AACIM: A 2785-TOPS/W, 161-TOP/mm2, <1.17%-RMSE, Analog-In Analog-Out Computing-In-Memory Macro in 28 nm

AACIM: A 2785-TOPS/W, 161-TOP/mm2, <1.17%-RMSE, Analog-In Analog-Out Computing-In-Memory Macro in 28 nm 150 150

Abstract:

This article presents an analog-in analog-out CIM macro (AACIM) for use in analog deep neural network (DNN) processors. Our macro receives analog inputs, performs a 64-by-32 vector–matrix multiplication (VMM) with a current-discharging computation mechanism, and produces analog outputs. It stores a 4-bit weight as an analog voltage in the …

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Fully Analog, Multi-Lag, RF Correlators for Code-Domain Radars Using Margin Propagation

Fully Analog, Multi-Lag, RF Correlators for Code-Domain Radars Using Margin Propagation 150 150

Abstract:

We present a fully analog, multiplier-free, sampled-domain RF correlator to achieve high energy efficiency for radar workloads. The RF correlator employs a split-source follower architecture that leverages the margin propagation (MP) computing paradigm in the sampled domain. As a proof of concept, we implement a $256 \times 256$ fully analog cross correlator …

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