Vector-Aware Programming: Tips & Tricks to Streamline the Process on a Petascale System

The trend for today’s CPUs is core count … and lots of it. (Cases in point: 2nd Gen Intel® Xeon® Scalable processors scale up to 48 cores per CPU. And Intel® Xeon Phi™ processors have as many as 72!) In this environment, vectorizing your code is critical to delivering optimal application performance on core-rich nodes.

So how do you write vectorization-friendly code?

You start by identifying and removing barriers like those affecting memory access patterns and cache usage, and balancing multi-process programming (MPI) with multi-threaded programming (OpenMP).

This presentation is a deep dive on how to do both, demonstrated on Texas Advanced Computing Center’s newest petascale system, Frontera, powered by Intel Xeon Scalable processors.

Watch Ian Wang, HPC specialist from University of Texas, discuss these concepts, including:

  • The basics of vector-aware programming, dependency analysis, and optimization reports
  • Guidance in using vector units, the proper placement of tasks/threads, the efficient use of memory bandwidth, and the impact of frequency scaling
  • Software tools of the trade, including Intel® Math Kernel Library and Intel® C++ Compilers
  • Code samples and step-by-step instructions

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Ian Wang, Research Associate, HPC Performance & Architectures Group, University of Texas at Austin

Ian joined the Texas Advanced Computing Center (TACC) in 2018 as a Research Associate in the Performance and Architecture Group. Currently, he focuses on system performance analysis and industry standard benchmarking on HPC platforms. He also assists TACC users port, analyze and improve their research software. Prior to joining TACC, he held a position at the Center for Research in Extreme Scale Technologies (CREST) at Indiana University where he worked on asynchronous multi-tasking runtime system development and RDMA networking library integration. He also worked as a Research Geophysicist at the Indiana Geological and Water Survey where he involved the collaborative development of a science gateway for simulation and assessment of CO2 capture and storage technologies with Los Alamos National Lab and Pervasive Technology Institute. Ian holds a Ph.D. in Geophysics from Indiana University.

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