Intel® Nervana™ reference deep learning framework committed to best performance on all hardware

Fast inference engine for Transformer models

Fast implementation of BERT inference directly on NVIDIA (CUDA, CUBLAS) and Intel MKL

automatic color-grading

Julia bindings to the FFTW library for fast Fourier transforms

Using advanced control and computer vision techniques in an easy way for embedded

monolish: MONOlithic LInear equation Solvers for Highly-parallel architecture

A simple cross platform .NET API for Intel MKL

Frequency-domain photonic simulation and inverse design optimization for linear and nonlinear devices

A package for Multiple Kernel Learning in Python

Stepwise optimizations of DGEMM on CPU, reaching performance faster than Intel MKL eventually, even under multithreading.

Data Parallel Extension for NumPy

Archlinux PKGBUILDs for Data Science, Machine Learning, Deep Learning, NLP and Computer Vision

Fast Unit Root Tests and OLS regression in C++ with wrappers for R and Python

Redistribute Intel MKL as a crate

Python wrapper for Intel Math Kernel Library (MKL) matrix multiplication

Least squares adjustment software

Python hooks for Intel(R) Math Kernel Library runtime control settings.

“云上炼丹师”中的云

NumPy-based Python interface to Intel (R) MKL FFT functionality