Computational Performance of Intel MIC, Sandy Bridge, and GPU Architectures: Implementation of a 1D c++/OpenMP Electrostatic Particle-In-Cell Code

Abstract

We present initial comparison performance results for Intel MIC, Sandy Bridge (SB), and GPU. A 1D explicit electrostatic particle-in-cell (PIC) code is used to simulate a two-stream instability in plasma. We compare the computation times for various number of cores/threads and compiler options. The parallelization is implemented via OpenMP with maximum thread number of 128. Parallelization and vectorization on the GPU is achieved with modifying the code syntax for compatibility with CUDA. We assess the speedup due to various auto-vectorization and optimization level compiler options. Our results show that the MIC is several times slower than SB for a single thread and it becomes faster than SB when the number of cores increases with vectorization switched on. The compute times for the GPU are consistently about 6-7 times faster than the ones for MIC. Compared to SB, the GPU is about 2 times faster for a single thread and about an order of magnitude faster for 128 threads. The net speedup, however, for MIC and GPU are almost the same. An initial attempt to offload parts of the code to the MIC co-processor shows that there is an optimal number of threads where the speedup reaches a maximum.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2014
Accession Number
ADA607056

Entities

People

  • A. Vapirev
  • Giovanni Lapenta
  • I. Hur
  • J. Cambier
  • J. Deca
  • S. Markidis

Organizations

  • Katholieke Universiteit Leuven - Universiteitsarchief

Tags

Communities of Interest

  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Algorithms
  • Central Processing Units
  • Compilers
  • Computations
  • Computer Programming
  • Computer Programs
  • Computers
  • Electric Fields
  • Equations
  • Equations Of Motion
  • Instability
  • Mathematics
  • Mobile Phones
  • Optimization
  • Particles
  • Personal Computers

Fields of Study

  • Computer science

Readers

  • Parallel and Distributed Computing.
  • Plasma Physics / Magnetohydrodynamics