Release 06 of Intel® oneAPI products is now live.
Highlights include support for the Intel® Stratix® 10 FPGA family, extensive new data science capabilities (Intel® Scalable Dataframe Compiler for high-performance Pandas), major deep-learning framework improvements (bfloat16 datatype support in TensorFlow and the addition of torchvision to PyTorch for higher performance), and new rendering capabilities (support of VDB volumes, new geometries, new light sources, and the option to use pre-trained models and retrain filter models for denoising).
* Select Intel® oneAPI tools now support the Intel Stratix 10 FPGA family via the Intel® FPGA Programmable Acceleration Card D5005. (Note, this is in addition to current support of the Intel® Arria® 10 family.) Supported tools are:
- Intel® oneAPI DPC++ Compiler
- Intel® oneAPI DPC++ Library
- Intel® Advisor
- Intel® VTune™ Profiler
* New DPC++ CPU and GPU function support in Intel® oneAPI Math Kernel Library (oneMKL) for BLAS, LAPACK, RNG, and FFT functions.
* New DPC++ code samples added and others improved, including a new Mandelbrot visualization sample
* Many improvements to the Intel® DPC++ Compatibility Tool, including improved CUDA code migration coverage for memory management and USM-enabled cuRAND API and DPC++ output code conciseness
* New data science capabilities including:
- Intel Scalable Dataframe Compiler in the Intel® Distribution for Python for high-performance Pandas on CPUs
- GPU-optimized functions for DBSCAN and SVM algorithms in the Intel® oneAPI Data Analytics Library (oneDAL,)
- uint8 support in XGBoost for reduced memory footprint
optimized implementations of random forest, AdaBoost, and gradient boosting classifiers in scikit-learn for high-performance ensemble learning
* Deep learning framework improvements include:
- Intel® Optimizations for TensorFlow upgraded to version 2.1 with bfloat16 data type support for improved DL training and inference performance
- Intel® Optimization for PyTorch adds TorchVision to provide efficient image transformations for computer vision use cases
* New rendering capabilities of Intel® oneAPI Rendering Toolkit, including:
- Intel® Open Volume Kernel Library now supports VDB volumes and volume observers
- Intel® OSPRay now enables easy rendering of clipping geometries, plane geometries, and new light sources for creating natural sun light and photometric indoor lighting
- Intel® Embree now includes round, linear curves featuring a new curve primitive for rendering hair quickly
- Intel® Open Image Denoise adds the option to use pre-trained models and retrain filter models with user-defined datasets to improve image quality for specific renderers and content
* Intel® System Debugger now supports Python 3 to run modern debug scripts. It also provides a new intuitive system debug interface for Intel® Processor Trace. The Intel® Debug Extensions for WinDbg now support Windows Core OS and efficient ACPI Machine Language debug.
Here is What's New in Intel® oneAPI AI Analytics Toolkit:
* Intel® Optimizations for Tensorflow upgraded to version 2.1 with bfloat16 data type support for improved DL training and inference performance.
Intel optimized Pytorch adds torchvision to provide efficient image transformations for computer vision usecases
* Enhanced Machine Learning capabilities with uint8 support in XGboost for reduced memory footprint and optimized implementations of Random forest, Adaboost and Gradient boosting classifiers in Scikit-learn for high performance ensemble learning.
Beta06 is available via web download, containers, repositories, and DevCloud.