mahinlma

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

metrics

Machine learning metrics for distributed, scalable PyTorch applications.

mahinlma/Accelerating-CNN-with-FPGA

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

mahinlma/Alveo-PYNQ

Introductory examples for using PYNQ with Alveo

mahinlma/audio

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

mahinlma/audio_ml

mahinlma/BaseKit-code-samples

mahinlma/benchmark

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

mahinlma/blinky

Example LED blinking project for your FPGA dev board of choice

mahinlma/brevitas

Quantization-aware training in Pytorch

mahinlma/metrics

Machine learning metrics for distributed, scalable PyTorch applications.

mahinlma/c5p_OpenCL_experiments

mahinlma/examples-1

TensorFlow examples

mahinlma/FFmpeg

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

mahinlma/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:

mahinlma/mlir

"Multi-Level Intermediate Representation" Compiler Infrastructure

mahinlma/netron

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

mahinlma/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.

mahinlma/oneAPI-samples

Samples for Intel oneAPI toolkits

mahinlma/onnxruntime

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

mahinlma/open_model_zoo

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

mahinlma/OpenVINO-Custom-Layers

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

mahinlma/optimum

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

mahinlma/ort_build

mahinlma/PYNQ-experiment

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

mahinlma/pytorch_quantization

Pytorch Model Quantization, Layer Fusion and Optimization

mahinlma/SDAccel_Examples

SDAccel Examples

mahinlma/spooNN

FPGA-based neural network inference project with an end-to-end approach (from training to implementation to deployment)

mahinlma/tune

mahinlma/Vitis_Accel_Examples

Vitis_Accel_Examples

mahinlma/Vitis_Libraries

Vitis Libraries

mahinlma/whisper