Article

Code Sample: Exploring MPI for Python* on Intel® Xeon Phi™ Processor

Learn how to write an MPI program in Python*, and take advantage of Intel® multicore architectures using OpenMP threads and Intel® AVX512 instructions.
Authored by Nguyen, Loc Q (Intel) Last updated on 07/06/2019 - 16:30
Article

Process and Thread Affinity for Intel® Xeon Phi™ Processors

The Intel® MPI Library and OpenMP* runtime libraries can create affinities between processes or threads, and hardware resources. This affinity keeps an MPI process or OpenMP thread from migrating to a different hardware resource, which can have a dramatic effect on the execution speed of a program.
Authored by Gregg S. (Intel) Last updated on 07/29/2019 - 08:05
Article

Scale-Up Implementation of a Transportation Network Using Ant Colony Optimization (ACO)

In this article an OpenMP* based implementation of the Ant Colony Optimization algorithm was analyzed for bottlenecks with Intel® VTune™ Amplifier XE 2016 together with improvements using hybrid MPI-OpenMP and Intel® Threading Building Blocks were introduced to achieve efficient scaling across a four-socket Intel® Xeon® processor E7-8890 v4 processor-based system.
Authored by Sunny G. (Intel) Last updated on 07/05/2019 - 19:10
Article

Hybrid Parallelism: Parallel Distributed Memory and Shared Memory Computing

There are two principal methods of parallel computing: distributed memory computing and shared memory computing. As more processor cores are dedicated to large clusters solving scientific and engineering problems, hybrid programming techniques combining the best of distributed and shared memory programs are becoming more popular.
Authored by David M. Last updated on 07/12/2019 - 08:31
Article

Choosing the right threading framework

This is the second article in a series of articles about High Performance Computing with the Intel Xeon Phi.

Authored by Last updated on 07/06/2019 - 16:30
Article

Understanding NUMA for 3D Isotropic Finite Difference (3DFD) Wave Equation Code

This article demonstrates techniques that software developers can use to identify and fix NUMA-related performance issues in their applications.
Authored by Sunny G. (Intel) Last updated on 07/05/2019 - 20:12
Blog post

Applying Intel® Threading Building Blocks Observers for Thread Affinity on Intel® Xeon Phi™ Coprocessors

In spite of the fact that the Intel® Threading Building Blocks (Intel® TBB) library [1] [2] provides high-level task based parallelism intended to hide sof

Authored by Alex (Intel) Last updated on 08/01/2019 - 09:30
Article

Optimizing Memory Bandwidth on Stream Triad

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Authored by Karthik Raman (Intel) Last updated on 07/06/2019 - 16:40
Article

Putting Your Data and Code in Order: Data and layout - Part 2

Apply the concepts of parallelism and distributed memory computing to your code to improve software performance. This paper expands on concepts discussed in Part 1, to consider parallelism, both vectorization (single instruction multiple data SIMD) as well as shared memory parallelism (threading), and distributed memory computing.
Authored by David M. Last updated on 07/06/2019 - 16:40
Article

Performance of Classic Matrix Multiplication Algorithm on Intel® Xeon Phi™ Processor System

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.
Authored by Last updated on 06/14/2019 - 11:50