Auto-Vectorization with the Intel Compilers: is Your Code Ready for Sandy Bridge and Knights Corner?

by Andrey Vladimirov 12. March 2012 13:01

Complete paper:  Colfax_Sandy_Bridge_AVX.pdf (632.23 kb)

One of the features of Intel’s Sandy Bridge-E processor released this month is the support for the Advanced Vector Extensions (AVX) instruction set. Codes suitable for efficient auto-vectorization by the compiler will be able to take advantage of AVX without any code modification, with only re-compilation.

This paper explains the guidelines for code design suitable for auto-vectorization by the compiler (elimination of vector dependence, implementation of unit-stride data access and proper address alignment) and walks the reader through a practical example of code development with auto-vectorization. The resulting code is compiled and executed on two computer systems: a Westmere CPU-based system with SSE 4.2 support, and a Sandy Bridge-based system with AVX support. The benefit of vectorization is more significant in the AVX version, if the code is designed efficiently. An ‘elegant’, but inefficient solution is also provided and discussed.

In addition, the paper provides a comparative benchmark of the Sandy Bridge and Westmere systems, based on the discussed algorithm. Implications of auto-vectorization methods for Intel’s future Many Integrated Core technology based on the Knights Corner chip are discussed at the end.

Complete paper:  Colfax_Sandy_Bridge_AVX.pdf (632.23 kb)

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Colfax International provides an arsenal of novel computational tools, which need to be leveraged in order to harness their full power. We are collaborating with researchers in science and industry, including our customers, to produce case studies, white papers, and develop a wide knowledge base of the applications of current and future computational technologies.

This blog will contain a variety of information, from hardware benchmarks and HPC news highlights, to discussions of programming issues and reports on research projects carried out in our collaborations. In addition to our in-house research, we will present contributions from authors in the academia, industry and finance, as well as software developers. Our hope is that this information will be useful to a wide audience interested in innovative computing technologies and their applications.

Author Profiles

Andrey Vladimirov, PhD, is a physicist with a longstanding interest in high performance computing. His research topics include computer simulations of cosmic ray production and propagation and collisionless plasma modeling. Andrey is a postdoctoral scholar at Stanford University.

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Author Profiles

Vadim Karpusenko, PhD, is a Research Associate at Colfax International. His research interests are in the area of physical modeling with HPC clusters, highly parallel architectures, and code optimization. Vadim holds a PhD in Physics from North Carolina State University for his computational research of the free energy and stability of helical secondary structures of proteins.

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