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06/16/2023
Sparq: A Custom RISC-V Vector Processor for Efficient Sub-Byte Quantized Inference
Convolutional Neural Networks (CNNs) are used in a wide range of applica...
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02/12/2023
Quark: An Integer RISC-V Vector Processor for Sub-Byte Quantized DNN Inference
In this paper, we present Quark, an integer RISC-V vector processor spec...
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12/31/2022
BARVINN: Arbitrary Precision DNN Accelerator Controlled by a RISC-V CPU
We present a DNN accelerator that allows inference at arbitrary precisio...
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06/24/2022
QReg: On Regularization Effects of Quantization
In this paper we study the effects of quantization in DNN training. We h...
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02/23/2020
PoET-BiN: Power Efficient Tiny Binary Neurons
The success of neural networks in image classification has inspired vari...
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08/02/2019
U-Net Fixed-Point Quantization for Medical Image Segmentation
Model quantization is leveraged to reduce the memory consumption and the...
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11/02/2015
BinaryConnect: Training Deep Neural Networks with binary weights during propagations
Deep Neural Networks (DNN) have achieved state-of-the-art results in a w...
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12/22/2014
