An in-memory computing multiply-and-accumulate circuit based on ternary STT-MRAMs for convolutional neural networks. Guihua Zhao. 1. , Xing Jin. 1. , Huafeng Ye.
In this report, a multiply-and-accumulate (MAC) circuit based on ternary spin-torque transfer magnetic random access memory (STT-MRAM) is proposed, which allows ...
Bibliographic details on An in-memory computing multiply-and-accumulate circuit based on ternary STT-MRAMs for convolutional neural networks.
Aug 2, 2023 · The. 1.5-b multiply-and-accumulate (MAC) is implemented by VCM- based capacitor switching scheme, which inherently benefits from the reduced ...
Missing: STT- MRAMs
Jun 7, 2021 · In-memory computing may enable multiply-accumulate (MAC) operations, which are the primary calculations used in artificial intelligence (AI) ...
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Our accelerator, FAT, is an STT-MRAM based In-Memory- Computing (IMC) accelerator for Ternary Weight Neural Net- work (TWN) inference.
Jun 7, 2021 · In-memory computing may enable multiply-accumulate (MAC) operations, which are the primary calculations used in artificial intelligence (AI) ...
The macro is an SRAM module with the circuits embedded in bitcells and peripherals to perform hardware acceleration for neural networks with binarized ...
We present XNOR-SRAM, a mixed-signal in-memory computing (IMC) SRAM macro that computes ternary-XNOR-and-accumulate (XAC) operations in binary/ternary deep ...
An in-memory computing multiply-and-accumulate circuit based on ternary STT-MRAMs for convolutional neural networks · Zhao Guihua · Jin Xing · Ye Huafeng · Peng ...