There are 49 repositories under fpga-accelerator topic.
Research and Materials on Hardware implementation of Transformer Model
Convolutional accelerator kernel, target ASIC & FPGA
Open Source Specialized Computing Stack for Accelerating Deep Neural Networks.
Small-scale Tensor Processing Unit built on an FPGA
Squeezenet V1.1 on Cyclone V SoC-FPGA at 450ms/image, 20x faster than ARM A9 processor alone. A project for 2017 Innovate FPGA design contest.
BARVINN: A Barrel RISC-V Neural Network Accelerator: https://barvinn.readthedocs.io/en/latest/
OpenCL HLS based CNN Accelerator on Intel DE10 Nano FPGA.
OPAE porting to Xilinx FPGA devices.
Basic OpenGL 1.x implementation for small FPGAs (like iCE40UP5K)
Lenet for MNIST handwritten digit recognition using Vivado hls tool
This project implements a convolution kernel based on vivado HLS on zcu104
Synthesizeable VHDL and Verilog implementation of 64-point FFT/IFFT Processor with Q4.12 Fixed Point Data Format.
FPGA-based hardware acceleration for dropout-based Bayesian Neural Networks.
Accelerating a Classic 3D Video Game (The DOOM) on Heterogeneous Reconfigurable MPSoCs
A crypto accelerator written for HLS to an FPGA that actually makes it slower than running it on your computer
An FPGA design for simulating biological neurons
FPGA with Xilinx Vitis HLS, Vivado, Vitis, and ZYNQ board. Working with HLS, Matrix Multiplier with HLS
Hardware-accelerated sorting algorithm
Includes the SVD-based approximation algorithms for compressing deep learning models and the FPGA accelerators exploiting such approximation mechanism, as described in the paper Mapping multiple LSTM models on FPGAs.
Co-processor for whole genome alignment
HLS-based framework to accelerate the implementation of 2-D DP kernels on FPGA
This repository contains the design and implementation of a Spiking Neural Network (SNN) Processor. Spiking Neural Networks are a biologically-inspired class of artificial neural networks, where neurons communicate by sending discrete spikes.
📈 Welcome to the repository that powers the future of stock market analysis with lightning-fast hardware acceleration on FPGA! ⚡️
EXPERIMENTAL Verilog (and HLS, C++, Python, OpenCL) implementation of the RC4 stream cipher.
Visual System Integrator - Accelerate your embedded development
UltraZed Development
FPGA based design
University of Pittsburgh ECE 1195