This project accelerates CNN computation with the help of FPGA, for more than 50x speed-up compared with CPU.
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Updated
Dec 10, 2019 - C++
This project accelerates CNN computation with the help of FPGA, for more than 50x speed-up compared with CPU.
ML model optimization product to accelerate inference.
Deep Learning Accelerator Based on Eyeriss V2 Architecture with custom RISC-V extended instructions
TMMA: A Tiled Matrix Multiplication Accelerator for Self-Attention Projections in Transformer Models, optimized for edge deployment on Xilinx KV260.
Reusable and scalable verification framework for Deep Neural Network (DNN) accelerators using Pyuvm, Cocotb, and Portable Stimulus Standard (PSS). Supports generic layer-wise verification and automated multi-layer scenario generation.
A tutorial for getting started on running Tensorrt engine and Deep Learning Accelerator (DLA) models on threads
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