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Go with Intel® Data Analytics Acceleration Library and Go*

Use of the Go* programming language and it’s developer community has grown significantly since it’s official launch by Google in 2009. Like many popular programming languages (C and Java come to mind), Go started as an experiment to design a new programming language that would fix some of the common problems of other languages and yet stay true to the basic tenets of modern programming: be scalable, productive, readable, enable robust development environments, and support networking and multiprocessing.

Performance Gains Using Libraries

In many cases, applications that perform various simulations use some of the same math functions that many other applications use. Rather than each developer recoding the same math functions over and over, libraries, developed by experts can significantly speed up execution of the overall application. Since there can be many optimizations that experts who understand many of the nuances of the hardware would understand, it is important that developers be familiar with various libraries that are made available for HPC types of applications.

Diffusion Optimization on Intel Xeon Phi

“The next step is to look at using OpenMP directives to create multiple threads to distribute the work over many threads and cores. A key OpenMP directive, #pragma omp for collapse, will collapse the inner two loops into one. The developer can then set the number of threads and cores to use and return the application to determine the performance. In one test case, three threads per physical core shows the best performance, by quite a lot compared to just using one or two threads per core.”