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A High Accuracy Low Power Convolution Operator with ...
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由 TS Oh 著作2021被引用 1 次 — 12T SRAM is a form of power gating on the conventional 10T SRAM. By using power gating, the inverter can be turned off. The new weight (0) can ...
A 12T SRAM in-Memory Computing differential current ...
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Mixed Signal Multiply and Adder Parallel Circuit for Deep Learning Convolution Operations · A High Accuracy Low Power Convolution Operator with 12T SRAM for CNN.
12T SRAM을 이용한 High Accuracy Convolution 연산기 | ...
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由 오태섭 著作2020 — Low Power Convolution 연산을 위한 SRAM이 포함된 PIM Architecture 설계 · Low Power Convolution Operator using 12T SRAM for CNN · 읽기 전력 감소를 위한 SRAM Cell ...
Low Power Convolution Operator using 12T SRAM for ...
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Various weight has to be stored in memory in order to obtain high accuracy. This paper shows Tri-state weight static random access memory. 12T SRAM which is ...
An Energy-efficient SRAM with Embedded Convolution ...
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Conv-RAM: An Energy-efficient SRAM with Embedded Convolution Computation for Low-power CNN based Machine Learning Applications. February 2018. Authors ...
convolution operator Latest Research Papers
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A High Accuracy Low Power Convolution Operator with 12T SRAM for CNN · 10.1109 ... convolution operator, we define the convolution layer, construct a convolution ...
A Low-Power Analog Processor-in-Memory-Based ...
MDPI
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由 SJ Byun 著作2022被引用 9 次 — This paper presents an on-chip implementation of an analog processor-in-memory (PIM)-based convolutional neural network (CNN) in a biosensor.
A Low Power In-DRAM Architecture for Quantized CNNs using ...
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由 MM Ghaffar 著作2020被引用 16 次 — Conv-RAM: An energy-efficient SRAM with embedded convolution computation for low-power CNN-based machine learning applications. In 2018 IEEE ...
Conv-RAM: An energy-efficient SRAM with embedded ...
ResearchGate
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SRAM. Conference Paper. Conv-RAM: An energy-efficient SRAM with embedded convolution computation for low-power CNN-based machine learning applications.
Analog Convolutional Operator Circuit for Low-Power ...
National Institutes of Health (NIH) (.gov)
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由 MS Asghar 著作2023被引用 2 次 — In this paper, we propose a compact and low-power mixed-signal approach to implementing convolutional operators that are often responsible for ...