In this webinar, James Reinders, will cover the essential knowledge needed for effectively utilizing the extraordinary parallelism in the new Intel® Xeon Phi™ processor (code named Knights Landing)
Check out the new commercial IoT website, find out more about Embree ray tracing, and read about a long-lived game studio.
Intel® Parallel Studio XE is a very popular product from Intel that includes the Intel® Compilers, Intel® Performance Libraries, tools for analysis, debugging and tuning, tools for MPI and the Intel® MPI Library. Did you know that some of these are available for free? Here is a guide to “what is available free” from the Intel Parallel Studio XE suites.
Learn how to write an MPI program in Python*, and take advantage of Intel® multicore architectures using OpenMP threads and Intel® AVX512 instructions.
Visual Bag-Of-Words in Python*: Speed Advantage of Intel® Data Analytics Acceleration Library (Intel® DAAL) over Scikit-learn*Image recognition with machine learning techniques has achieved significant growth due to advances in recent years in both algorithmic efficiency and hardware performance. Even with these advances, image pre-processing of raw images remains a critical step, especially in larger datasets.
Analytics Speed with Ease: Visual Bag-Of-Words in Python* with Intel® Data Analytics Acceleration Library (Intel® DAAL) High Level APIIn the companion article, we concluded that Intel® Data Analytics Acceleration Library (DAAL) efficiently utilizes all resources of your machine to perform faster analytics. Now we will show you how to take advantage of these faster analytics methods with simpler Python* commands, namely with Daal4py interface.
This case study compares the performance of Intel® Distribution for Python* to that of non-optimized Python using a breast cancer classification. This comparison was done using machine learning algorithms from the scikit-learn* package in Python.