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ai-pc_notebooks

aigamedevtoolkit

Foundation layer for AI Gamedev Toolkit which can be built upon by dev community

aigamedevtoolkit-starter-demos

Demos intended to be run with AI GameDev Toolkit (separate download)

dl-using-oneapi

Focus will be on Deep Learning optimizations using oneAPI

forestfireprediction

Forest fire prediction using finetuning on CPU with MODIS and NAIP aerial photos and resnet with acceleration using Intel Extensions for PyTorch

intel-extensions-for-scikit-learn-essentials-for-machine-learning

intel_oneapi_mkl_training

This is a series of sample exercises demonstrating how to use oneMKL

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

jurassic

Jurassic

machine-learning-using-oneapi

Machine Learning using oneAPI. Explores Intel Extensions for scikit-learn* and NumPy, SciPy, Pandas powered by oneAPI

numpy_optimizations

Exercises to replace loops with NumPy function equivalents to gain 10X to 100sX acceleration over simple minded python loop access

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.

particle_fountain_vulkan_cpu

particle_fountain_vulkan_gpu

pc-skills-framework

python-loop-replacement-with-numpy-and-pytorch

Python Loop Replacement with NumPy and PyTorch - Fancy Slicing, UFuncs and equivalent, Aggregations, Sorting and more

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

sd_ws

Material for the Diffusers Workshop on ITDC

sycl_101

From zero to oneAPI Hero

tutorial-password-manager-with-intel-sgx

This sample code demonstrates a password manager utilizing Intel SGX.

ue4-parallel

Demo of parallel-for flocking algorithm on Unreal4

unity-parallel-cpu

unity-parallel-gpu