NDLI: Increasing efficiency of Monte Carlo particle-fluid collision calculations on GPU

Content Provider	IEEE Xplore Digital Library
Author	Bardel, C. Verboncoeur, J.
Copyright Year	2013
Description	Author affiliation: Electr. & Comput. Eng., Michigan State Univ., East Lansing, MI, USA (Bardel, C.; Verboncoeur, J.)
Abstract	Summary form only given. Monte Carlo particle collision calculations can be very computationally expensive for particle-in-cell codes. In the case of background fluid collisional calculations, where each particle calculation is totally independent of other collisions, the calculations can be setup as highly parallel. Porting to GPU platforms has shown two orders of magnitude decrease compared to single processor performance. One approach is to simply apply a function to every particle which involves computing the particle energy, a square root to obtain the speed, and either interpolation of tabled cross sections or computation of a curve fit for each process for every particle [1]. Then, based on this probability of collision the collisional dynamics code might be executed. For collisional probabilities, 1 this is inefficient for finding particles to collide and load imbalanced for the collisional dynamics on the vector architecture (Single-Instruction Multiple-Data SIMD) like capabilities available on the GPU[2]. The alternative approach is to use the null collision method[1] where particles selected for collision are selected at random using the total collision probability, which is independent of particle energy and position. However, this sparse random access of particles in the particle array, as needed for the null collision method[1], has drawbacks on the GPU due to SIMD architecture. GPU threads that are grouped in hardware are called warps. Each warp can only issue one computational or memory instruction. However, when two memory instructions are located with 128 bytes[2] of each other they can be 'coalesced' into one instruction. Using the data structure and algorithm presented in [3] for efficient particle to grid charge accumulation on the GPU, which ensures that all particles contained within a cell are contiguous in memory, this paper examines the effect of selecting particles for colliding that are contiguous in that same list. This setup would capitalize on the null collision method's not needing to calculate the energy of each particle and optimize the memory bandwidth through the GPU. The key point under investigation is whether the particle sort algorithm retains enough entropy in the particle list gained from particle cell crossings in the algorithm in [3]. This will be examined by varying the size of the contiguous particle block and measuring the thermal equilibration time.
Starting Page	1
Ending Page	1
File Size	49367
Page Count	1
File Format	PDF
ISBN	9781467351713
ISSN	07309244
DOI	10.1109/PLASMA.2013.6634961
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Graphics processing units Computer architecture Monte Carlo methods Microprocessors Computers Educational institutions Buildings
Content Type	Text
Resource Type	Article
Subject	Atomic and Molecular Physics, and Optics Condensed Matter Physics Electrical and Electronic Engineering

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2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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