Learn how to write an MPI program in Python*, and take advantage of Intel® multicore architectures using OpenMP threads and Intel® AVX512 instructions.
In this tutorial, we demonstrate some possible ways to optimize an application to run on the Intel® Xeon Phi™ processor
Cython* is a superset of Python* that additionally supports C functions and C types on variable and class attributes. Cython generates C extension modules, which can be used by the main Python program using the import statement.
Learn techniques for vectorizing code, adding thread-level parallelism, and enabling memory optimization.
Matrix multiplication (MM) of two matrices is one of the most fundamental operations in linear algebra. The algorithm for MM is very simple, it could be easily implemented in any programming language. This paper shows that performance significantly improves when different optimization techniques are applied.
This paper examines software performance optimization for an implementation of a non-library version of DGEMM executing on the Intel® Xeon Phi™ processor (code-named Knights Landing, with acronym K
Exercise in performance optimization on Intel Architecture, including Intel® Xeon Phi™ processors.
Code Sample included: Learn how to use MPI-3 shared memory feature using the corresponding APIs on the Intel® Xeon Phi™ processor.