Intel Software's repositories
ue4-parallel
Demo of parallel-for flocking algorithm on Unreal4
AIGamedevToolkit
Foundation layer for AI Gamedev Toolkit which can be built upon by dev community
OpenGLBestPracticesfor6thGenIntelProcessor
Game developers often use OpenGL to handle the rendering chores for graphics-intensive games. OpenGL is an application programming interface for efficiently rendering two- and three-dimensional vector graphics. The code samples are a series from Grahics API developer guide for for 6th generation Intel® Core™ processor (https://software.intel.com/en-us/articles/6th-gen-graphics-api-dev-guide) that demonstrates how to get the most out of OpenGL 4.4 and higher.
Machine-Learning-using-oneAPI
Machine Learning using oneAPI. Explores Intel Extensions for scikit-learn* and NumPy, SciPy, Pandas powered by oneAPI
Tutorial-Password-Manager-with-Intel-SGX
This sample code demonstrates a password manager utilizing Intel SGX.
ForestFirePrediction
Forest fire prediction using finetuning on CPU with MODIS and NAIP aerial photos and resnet with acceleration using Intel Extensions for PyTorch
aigamedevtoolkit-starter-demos
Demos intended to be run with AI GameDev Toolkit (separate download)
Python-Loop-Replacement-with-NumPy-and-PyTorch
Python Loop Replacement with NumPy and PyTorch - Fancy Slicing, UFuncs and equivalent, Aggregations, Sorting and more
Introduction_to_Machine_Learning
Introduction to Machine Learning with focus on Scikit-learn* algorithms and how to accelerate those algorithms with a couple of line of code on CPU using Intel Extensions for Scikit-learn
NumPy_Optimizations
Exercises to replace loops with NumPy function equivalents to gain 10X to 100sX acceleration over simple minded python loop access
PyTorch_Optimizations
Describe how Intel SIMD and Cache optimization provided by Intel oneMKL-DNN as well as the Intel Extensions for PyTorch can accelerate your pytorch workloads especially prior to training loop or during post processing. Also explore how to use Intel Extensions to PyTorch and how to access Intel GPU for PyTorch
scikit-learn_essentials
Course demonstrating how to using SYCL context and Intel(R) Extensions for scikit-learn* to optimize selected sklearn algorithms and target them for gpu
DL-using-oneAPI
Focus will be on Deep Learning optimizations using oneAPI
Intel_oneAPI_MKL_Training
This is a series of sample exercises demonstrating how to use oneMKL