VecMeter: Measuring Vectorization on the Xeon Phi
Joshua Peraza, Ananta Tiwari, William A. Ward, Roy Campbell, Laura Carrington
Abstract
Joshua Peraza, Ananta Tiwari, William A. Ward, Roy Campbell, Laura Carrington
Abstract
Wide vector units in Intel's Xeon Phi accelerator cards can significantly boost application performance when used effectively. However, there is a lack of performance tools that provide programmers accurate information about the level of vectorization in their codes. This paper presents VecMeter, an easy-to-use tool to measure vectorization on the Xeon Phi. VecMeter utilizes binary instrumentation and therefore does not require source code modifications. This paper describes the design of VecMeter, demonstrates its accuracy, defines a metric for quantifying vectorization, and provides an example where the tool can guide code optimization to improve performance by up to 33%.
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Wide vector units in Intel's Xeon Phi accelerator cards can significantly boost application performance when used effectively. However, there is a lack of performance tools that provide programmers accurate information about the level of vectorization in their codes. This paper presents VecMeter, an easy-to-use tool to measure vectorization on the Xeon Phi. VecMeter utilizes binary instrumentation and therefore does not require source code modifications. This paper describes the design of VecMeter, demonstrates its accuracy, defines a metric for quantifying vectorization, and provides an example where the tool can guide code optimization to improve performance by up to 33%.
Key concepts: Vectorization (mathematics), Xeon Phi, Computer science, Code (set theory), Parallel computing, Metric (unit), Source code, Instrumentation (computer programming)