7 citations · 15 across the 9 of their papers we have counts for
3 papers · 1 filter
Sparq: A Custom RISC-V Vector Processor for Efficient Sub-Byte Quantized Inference
Théo Dupuis, Yoan Fournier, MohammadHossein AskariHemmat +4
Convolutional Neural Networks (CNNs) are used in a wide range of applications, with full-precision CNNs achieving high accuracy at the expense of portability. Recent progress in qu…
Quark: An Integer RISC-V Vector Processor for Sub-Byte Quantized DNN Inference
MohammadHossein AskariHemmat, Theo Dupuis, Yoan Fournier +8
In this paper, we present Quark, an integer RISC-V vector processor specifically tailored for sub-byte DNN inference. Quark is implemented in GlobalFoundries' 22FDX FD-SOI technolo…
BARVINN: Arbitrary Precision DNN Accelerator Controlled by a RISC-V CPU
Mohammadhossein Askarihemmat, Sean Wagner, Olexa Bilaniuk +3
We present a DNN accelerator that allows inference at arbitrary precision with dedicated processing elements that are configurable at the bit level. Our DNN accelerator has 8 Proce…