# Experiences with different parallel programming paradigms for Monte Carlo particle transport leads to a portable toolkit for parallel Monte Carlo

## Abstract

Monte Carlo particle transport is easy to implement on massively parallel computers relative to other methods of transport simulation. This paper describes experiences of implementing a realistic demonstration Monte Carlo code on a variety of parallel architectures. Our pool of tasks'' technique, which allows reproducibility from run to run regardless of the number of processors, is discussed. We present detailed timing studies of simulations performed on the 128 processor BBN-ACI TC2000 and preliminary timing results for the 32 processor Kendall Square Research KSR-1. Given sufficient workload to distribute across many computational nodes, the BBN achieves nearly linear speedup for a large number of nodes. The KSR, with which we have had less experience, performs poorly with more than ten processors. A simple model incorporating known causes of overhead accurately predicts observed behavior. A general-purpose communication and control package to facilitate the implementation of existing Monte Carlo packages is described together with timings on the BBN. This package adds insignificantly to the computational costs of parallel simulations.

- Authors:

- (Michigan Univ., Ann Arbor, MI (United States). Dept. of Nuclear Engineering)
- (Lawrence Livermore National Lab., CA (United States))
- (Phillips Academy, Andover, MA (United States))

- Publication Date:

- Research Org.:
- Lawrence Livermore National Lab., CA (United States)

- Sponsoring Org.:
- DOE; NSF; USDOE, Washington, DC (United States); National Science Foundation, Washington, DC (United States)

- OSTI Identifier:
- 6585922

- Alternate Identifier(s):
- OSTI ID: 6585922; Legacy ID: DE93009061

- Report Number(s):
- UCRL-JC-111846; CONF-930404--12

ON: DE93009061; CNN: ECS-9107725

- DOE Contract Number:
- W-7405-ENG-48; FG02-92ER75709

- Resource Type:
- Conference

- Resource Relation:
- Conference: International topical meeting on mathematical methods and supercomputing in nuclear applications (M C+SNA '93), Karlsruhe (Germany), 19-23 Apr 1993

- Country of Publication:
- United States

- Language:
- English

- Subject:
- 73 NUCLEAR PHYSICS AND RADIATION PHYSICS; 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; MONTE CARLO METHOD; PARALLEL PROCESSING; RADIATION TRANSPORT; ALGORITHMS; ARRAY PROCESSORS; CALCULATION METHODS; MATHEMATICAL LOGIC; PROGRAMMING 663600* -- Radiation Physics-- (1992-); 990200 -- Mathematics & Computers

### Citation Formats

```
Martin, W.R., Majumdar, A., Rathkopf, J.A., and Litvin, M.
```*Experiences with different parallel programming paradigms for Monte Carlo particle transport leads to a portable toolkit for parallel Monte Carlo*. United States: N. p., 1993.
Web.

```
Martin, W.R., Majumdar, A., Rathkopf, J.A., & Litvin, M.
```*Experiences with different parallel programming paradigms for Monte Carlo particle transport leads to a portable toolkit for parallel Monte Carlo*. United States.

```
Martin, W.R., Majumdar, A., Rathkopf, J.A., and Litvin, M. Thu .
"Experiences with different parallel programming paradigms for Monte Carlo particle transport leads to a portable toolkit for parallel Monte Carlo". United States.
```

```
@article{osti_6585922,
```

title = {Experiences with different parallel programming paradigms for Monte Carlo particle transport leads to a portable toolkit for parallel Monte Carlo},

author = {Martin, W.R. and Majumdar, A. and Rathkopf, J.A. and Litvin, M.},

abstractNote = {Monte Carlo particle transport is easy to implement on massively parallel computers relative to other methods of transport simulation. This paper describes experiences of implementing a realistic demonstration Monte Carlo code on a variety of parallel architectures. Our pool of tasks'' technique, which allows reproducibility from run to run regardless of the number of processors, is discussed. We present detailed timing studies of simulations performed on the 128 processor BBN-ACI TC2000 and preliminary timing results for the 32 processor Kendall Square Research KSR-1. Given sufficient workload to distribute across many computational nodes, the BBN achieves nearly linear speedup for a large number of nodes. The KSR, with which we have had less experience, performs poorly with more than ten processors. A simple model incorporating known causes of overhead accurately predicts observed behavior. A general-purpose communication and control package to facilitate the implementation of existing Monte Carlo packages is described together with timings on the BBN. This package adds insignificantly to the computational costs of parallel simulations.},

doi = {},

journal = {},

number = ,

volume = ,

place = {United States},

year = {1993},

month = {4}

}