Intel® End-to-End AI Optimization Kit release v0.2
Intel® End-to-End AI Optimization Kit is a composable toolkits for E2E AI optimization to deliver high performance, lightweight networks/models efficiently on commodity HW like CPU, intending to make E2E AI pipelines faster, easier and more accessible.
Highlights
This release introduced 4 new deeply optimized End to End AI workflows including Computer Vision model ResNet, Speech Recognition model RNN-T, NLP model BERT and Reinforcement Learning model MiniGo that delivers optimized performance on CPU. The major optimizations are: improves scale-out capabilities on distributed CPU nodes, and built-in model optimization and auto hyperparameter tuning with Smart Democratization Advisor (SDA).
This release provides following highlighted features:
- Single click AI solution deployment in distributed CPU clusters
- Enhanced Smart Democratization Advisor (SDA)
- Optimized popular models Resnet, RNN-T, Bert, MiniGo on CPU.
Improvements
- Easy clustering deployment script
- Click-to-run optimized AI pipelines
- Updated data processing with RecDP for DLRM
- Step by Step guides and demos
Versions and Components
- Tensorflow 2.5, 2.10
- Pytorch 1.10
- Horovod 0.23, 0.26
- Spark 3.1
- Python 3.x
Links
Full Changelog: https://github.com/intel/e2eAIOK/commits/v0.2