Parallel Computing in the Search for New Physics at LHC

by Andrey Vladimirov 2. December 2013 15:35

Manuscript of Publication: PDF logo http://arxiv.org/pdf/1310.7556 (submitted to JINST)

Feature in International Journal of Innovation: PDF logo p36-38_Valerie_Halyo-LR.pdf (724.08 kb)

In the past few months we have had the pleasure of collaborating with Prof. Valerie Halyo of Princeton University on modernization of a high energy physics application for the needs of the Large Hadron Collider (LHC). The objective of our project is to improve the performance of the trigger at LHC, so as to enable real-time detection of exotic collision event products, such as black holes or jets.

For the numerical algorithm of the new trigger software, the Hough transform was chosen. This method allows fast detection of straight or curved tracks in a set of points (detector hits), which could be the traces of new exotic particles. The nature of the numerical Hough transform is highly parallelizable, however, existing implementations did not use hardware parallelism or used it sub-optimally.

Colfax's role in the project was to optimize a thread-parallel implementation of the Hough transform for multi-core processors. The result of our involvement was a code capable of detecting 5000 tracks in a synthetic dataset 250x faster than prior art, on a multi-core desktop CPU. By benchmarking the application on a server based on multi-core Intel Xeon E5 processors, we obtained a yet 5x greater performance. The techniques used for optimization, briefly discussed in the report paper (see below), are featured in our book on parallel programming and in our developer training program. They focus on code portability across multi- and many-core platforms, with the emphasis on future-proofing the optimized application.

Our results are reported in a publication submitted for peer review to JINST (see link at the top and bottom of this post). Prof. Halyo's work was also featured in an article in International Journal of Innovation, available for download here (courtesy of Prof. Halyo).

Manuscript of Publication: PDF logo http://arxiv.org/pdf/1310.7556 (submitted to JINST)

Feature in International Journal of Innovation: PDF logo p36-38_Valerie_Halyo-LR.pdf (724.08 kb)

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About Colfax Research

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 the Head of HPC Research at Colfax International. His primary research interest is the application of modern computing technologies to computationally demanding scientific problems. Prior to joining Colfax, Andrey was involved in theoretical astrophysics research at the Ioffe Institute (Russia), North Carolina State University, and Stanford University (USA), where he studied cosmic rays, collisionless plasmas and the interstellar medium using computer simulations. 

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Author Profiles

Vadim Karpusenko, PhD, is a Principal HPC Research Engineer 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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