ON VECTORIZATION FOR LATTICE BASED SIMULATIONS

Aniruddha G. Shet (), K. Siddharth (), Shahajhan H. Sorathiya (), Anand M. Deshpande (), Sunil D. Sherlekar (), Bharat Kaul () and Santosh Ansumali ()
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Aniruddha G. Shet: Parallel Computing Lab, Intel Labs, Bangalore-560103, India
K. Siddharth: Engineering Mechanics Unit, JNCASR, Bangalore-560064, India
Shahajhan H. Sorathiya: Engineering Mechanics Unit, JNCASR, Bangalore-560064, India
Anand M. Deshpande: Parallel Computing Lab, Intel Labs, Bangalore-560103, India
Sunil D. Sherlekar: Parallel Computing Lab, Intel Labs, Bangalore-560103, India
Bharat Kaul: Parallel Computing Lab, Intel Labs, Bangalore-560103, India
Santosh Ansumali: Engineering Mechanics Unit, JNCASR, Bangalore-560064, India

International Journal of Modern Physics C (IJMPC), 2013, vol. 24, issue 12, 1-12

Abstract: We present a vector-friendly blocked computing strategy for the lattice Boltzmann method (LBM). This strategy, along with a recently developed data structure, Structure of Arrays of Structures (SoAoS), is implemented for multi-relaxation type lattice Boltzmann (LB). The proposed methodology enables optimal memory bandwidth utilization in the advection step and high compute efficiency in the collision step of LB implementation. In a dense computing environment, current performance optimization framework for LBM is able to achieve high single-core efficiency.

Keywords: Lattice Boltzmann; performance optimization; vectorization; SIMD; 11.25.Hf; 123.1K (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1142/S0129183113400111

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