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More Than Ever, Vectorization and Multithreading are Essential for Performance

Employing a hybrid of MPI across nodes in a cluster, multithreading with OpenMP* on each node, and vectorization of loops within each thread results in multiple performance gains. In fact, most application codes will run slower on the latest supercomputers if they run purely sequentially. This means that adding multithreading and vectorization to applications is now essential for running efficiently on the latest architectures.

Intel Advisor Roofline Analysis Finds New Opportunities for Optimizing Application Performance

Intel Advisor, an integral part of Intel Parallel Studio XE 2017, can help identify portions of code that could be good candidates for parallelization (both vectorization and threading). It can also help determine when it might not be appropriate to parallelize a section of code, depending on the platform, processor, and configuration it’s running on. Intel Advisor Roofline Analysis reveals the gap between an application’s performance and its expected performance.