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accelerating-cnn-with-fpga

This project accelerates CNN computation with the help of FPGA, for more than 50x speed-up compared with CPU.

alveo-pynq

Introductory examples for using PYNQ with Alveo

audio

Data manipulation and transformation for audio signal processing, powered by PyTorch

audio_ml

augmented-neural-odes

Pytorch implementation of Augmented Neural ODEs :sunflower:

basekit-code-samples

benchmark

TorchBench is a collection of open source benchmarks used to evaluate PyTorch performance.

blinky

Example LED blinking project for your FPGA dev board of choice

brevitas

Quantization-aware training in Pytorch

c5p_opencl_experiments

digital-design-lab

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

examples-1

TensorFlow examples

ffmpeg

Mirror of git://source.ffmpeg.org/ffmpeg.git

fpga-devcloud

Get started using Intel® FPGA tools on the Devcloud with tutorials, workshops, advanced courses, and sample projects built specifically for students, researchers, and developers. Visit our official Intel® FPGA Devcloud website:

leflow

Enabling Flexible FPGA High-Level Synthesis of Tensorflow Deep Neural Networks

metrics

Machine learning metrics for distributed, scalable PyTorch applications.

ml-suite_tensorflow_quantization

Getting Started with Xilinx ML Suite

mlir

"Multi-Level Intermediate Representation" Compiler Infrastructure

netron

Visualizer for neural network, deep learning, and machine learning models

olive

OLive, meaning ONNX Runtime(ORT) Go Live, is a python package that automates the process of accelerating models with ONNX Runtime(ORT). It contains two parts including model conversion to ONNX with correctness checking and auto performance tuning with ORT. Users can run these two together through a single pipeline or run them independently as needed.

oneapi-samples

Samples for Intel oneAPI toolkits

onnxruntime

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

open_model_zoo

Pre-trained Deep Learning models and samples (high quality and extremely fast)

openvino-custom-layers

Tutorial for Using Custom Layers with OpenVINO (Intel Deep Learning Toolkit)

openvino_training_extensions

Trainable models and NN optimization tools

optimum

🏎️ Accelerate training and inference of 🤗 Transformers with easy to use hardware optimization tools

ort_build

plotneuralnet

Latex code for making neural networks diagrams

pynq-experiment

This repository contains a "Hello World" introduction application to the Xilinx PYNQ framework.