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ue4-parallel
Demo of parallel-for flocking algorithm on Unreal4AIGamedevToolkit
Foundation layer for AI Gamedev Toolkit which can be built upon by dev communityOpenGLBestPracticesfor6thGenIntelProcessor
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 oneAPITutorial-Password-Manager-with-Intel-SGX
This sample code demonstrates a password manager utilizing Intel SGX.unity-parallel-gpu
Jurassic
JurassicForestFirePrediction
Forest fire prediction using finetuning on CPU with MODIS and NAIP aerial photos and resnet with acceleration using Intel Extensions for PyTorchIntel-Extensions-for-Scikit-learn-Essentials-for-Machine-Learning
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 moreunity-parallel-cpu
particle_fountain_vulkan_gpu
PC-Skills-Framework
Numba_DPPY_Essentials
Data Parallel PythonIntroduction_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-learnparticle_fountain_vulkan_cpu
NumPy_Optimizations
Exercises to replace loops with NumPy function equivalents to gain 10X to 100sX acceleration over simple minded python loop accessscikit-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 gpuDL-using-oneAPI
Focus will be on Deep Learning optimizations using oneAPIFinetuning
Use Finetuning in PyTorch to derive GIS based model predictors using CPU with few iterationsIntel_oneAPI_MKL_Training
This is a series of sample exercises demonstrating how to use oneMKLIntel_AI_2022_Webinar_Series
sd_ws
Material for the Diffusers Workshop on ITDCAI-PC_Notebooks
SYCL_101
From zero to oneAPI HeroGPU-Occupancy-Calculator
Intel GPU Occupancy Calculator for HPC Application DevelopmentLove Open Source and this site? Check out how you can help us