Highlights include * the introduction of Intel® Distribution for Modin with Omnisci backend for distributed data analytics preprocessing, * up to 4x improved rendering speed and particle volume support in the Intel® oneAPI Rendering Toolkit, * introduction of the Performance Snapshot profiling in Intel® VTune™ Profiler for quick initial analysis, * memory-level roofline analysis in Intel® Advisor, * H.265 and AV1 CPU software codecs in Intel® oneAPI Video Processing Library, and * NUMA optimization capabilities in Intel® oneAPI Threading Building Blocks.
Additional details * Intel® VTune™ Profiler continues to refine analysis for GPU accelerators with the addition of OpenMP offload pragma-aware metrics. It also adds a Performance Snapshot as a first profiling step to suggest the detailed analyses (memory, threading, etc.) that offer the most optimization opportunity
* Intel® Advisor adds memory-level Roofline analysis, that helps to pinpoint exact memory hierarchy bottlenecks (L1, L2, L3 or DRAM)
* Major Intel® oneAPI Video Processing Library update including H.265 & AV1 CPU software codecs and upward compatibility with Intel® Media SDK
* Major Intel® oneAPI Threading Building Blocks update including detailed NUMA affinity management capabilities and alignment with modern C++
* Improved Intel® oneAPI DPC++ Compiler code performance for CPU architectures
* Initial OpenMP 5.0 GPU offload support in the Intel® C++ Compiler
* Intel® AI Analytics Toolkit adds significant enhancements to data analytics workflows by introducing Intel® Distribution of Modin, released through the Anaconda channel. Seamlessly scale data preprocessing across multi nodes using this intelligent, distributed dataframe library with an identical API to pandas. In the backend, it is supported by Omnisci, a performant framework for end-to-end analytics that has been optimized to harness the computing power of existing and emerging Intel® hardware.
* Intel® AI Analytics Toolkit also upgrades to PyTorch 1.5 which includes support for Bfloat16 data type and latest 3rd Gen Intel Xeon Scalable Processors (code named Cooper Lake).
* The Intel® Distribution for Python introduces GPU support for Python/Numba code on Linux as well as the Python Data Parallel Processing Library (PyDPPL), a light weight Python wrapper for DPC++ and SYCL that provides a data parallel interface and abstractions to efficiently tap into device management features of Intel CPU's and GPU's.
* Intel® OSPRay and Intel® Open Volume Kernel both add support for particle volumes, while Intel OSPRay also adds support for Stereo 3D mode for panoramic camera and scalability of light sources.
* Performance improvements in Intel®Open Volume Kernel and Intel® Open Image Denoise improved rendering speeds by up to 4x and improved image quality.
* Photon mapping support added to Intel® Embree
* Intel Open Volume Kernel also adds support for configurable filter/reconstruction methods, stream-wide sampling and gradient API, Iterator allocation API and Strided data arrays.
* Intel® Open Image improved image quality by adding additional Feature Buffers. It also includes new XTraining Code features and improvements.
* macOS CPU support introduced for the Intel® oneAPI Rendering Toolkit as well as C++, and Fortran compilers, most of the libraries in the Intel® oneAPI Base Toolkit, and analysis tool results viewers.
* The Intel® System Debugger adds support for the 3rd Gen Intel® Xeon® Scalable Processors (formerly Cooper Lake-SP), 10th Gen Intel® Core® Processor (formerly Comet Lake S & H), and Intel Atom® Processor P-series (formerly Snow Ridge). The improved Target Connection Assistant makes it easier for developers to connect to a target platform.