# Computational Particle Dynamic Simulations on Multicore Processors (CPDMu) Final Report Phase I

## Abstract

Statement of Problem - Department of Energy has many legacy codes for simulation of computational particle dynamics and computational fluid dynamics applications that are designed to run on sequential processors and are not easily parallelized. Emerging high-performance computing architectures employ massively parallel multicore architectures (e.g., graphics processing units) to increase throughput. Parallelization of legacy simulation codes is a high priority, to achieve compatibility, efficiency, accuracy, and extensibility. General Statement of Solution - A legacy simulation application designed for implementation on mainly-sequential processors has been represented as a graph G. Mathematical transformations, applied to G, produce a graph representation {und G} for a high-performance architecture. Key computational and data movement kernels of the application were analyzed/optimized for parallel execution using the mapping G {yields} {und G}, which can be performed semi-automatically. This approach is widely applicable to many types of high-performance computing systems, such as graphics processing units or clusters comprised of nodes that contain one or more such units. Phase I Accomplishments - Phase I research decomposed/profiled computational particle dynamics simulation code for rocket fuel combustion into low and high computational cost regions (respectively, mainly sequential and mainly parallel kernels), with analysis of space and time complexity. Using the researchmore »

- Authors:

- Publication Date:

- Research Org.:
- Ultrahinet, LLC

- Sponsoring Org.:
- Office of Science (SBIR)

- OSTI Identifier:
- 1019271

- Report Number(s):
- UHN-2011-001

TRN: US201213%%184

- DOE Contract Number:
- SC0004211

- Resource Type:
- Technical Report

- Country of Publication:
- United States

- Language:
- English

- Subject:
- 97 MATHEMATICAL METHODS AND COMPUTING; ACCURACY; COMBUSTION; COMMERCIAL SECTOR; COMPATIBILITY; COMPUTER ARCHITECTURE; COMPUTER CODES; COMPUTERIZED SIMULATION; EFFICIENCY; FLUID MECHANICS; IMPLEMENTATION; KERNELS; OPTIMIZATION; PARALLEL PROCESSING; ROCKETS; SIMULATION; TRANSFORMATIONS; High-performance Computing, Graphic Processing Unit, Fluid/Particle Simulation

### Citation Formats

```
Schmalz, Mark S.
```*Computational Particle Dynamic Simulations on Multicore Processors (CPDMu) Final Report Phase I*. United States: N. p., 2011.
Web. doi:10.2172/1019271.

```
Schmalz, Mark S.
```*Computational Particle Dynamic Simulations on Multicore Processors (CPDMu) Final Report Phase I*. United States. doi:10.2172/1019271.

```
Schmalz, Mark S. Sun .
"Computational Particle Dynamic Simulations on Multicore Processors (CPDMu) Final Report Phase I". United States. doi:10.2172/1019271. https://www.osti.gov/servlets/purl/1019271.
```

```
@article{osti_1019271,
```

title = {Computational Particle Dynamic Simulations on Multicore Processors (CPDMu) Final Report Phase I},

author = {Schmalz, Mark S},

abstractNote = {Statement of Problem - Department of Energy has many legacy codes for simulation of computational particle dynamics and computational fluid dynamics applications that are designed to run on sequential processors and are not easily parallelized. Emerging high-performance computing architectures employ massively parallel multicore architectures (e.g., graphics processing units) to increase throughput. Parallelization of legacy simulation codes is a high priority, to achieve compatibility, efficiency, accuracy, and extensibility. General Statement of Solution - A legacy simulation application designed for implementation on mainly-sequential processors has been represented as a graph G. Mathematical transformations, applied to G, produce a graph representation {und G} for a high-performance architecture. Key computational and data movement kernels of the application were analyzed/optimized for parallel execution using the mapping G {yields} {und G}, which can be performed semi-automatically. This approach is widely applicable to many types of high-performance computing systems, such as graphics processing units or clusters comprised of nodes that contain one or more such units. Phase I Accomplishments - Phase I research decomposed/profiled computational particle dynamics simulation code for rocket fuel combustion into low and high computational cost regions (respectively, mainly sequential and mainly parallel kernels), with analysis of space and time complexity. Using the research team's expertise in algorithm-to-architecture mappings, the high-cost kernels were transformed, parallelized, and implemented on Nvidia Fermi GPUs. Measured speedups (GPU with respect to single-core CPU) were approximately 20-32X for realistic model parameters, without final optimization. Error analysis showed no loss of computational accuracy. Commercial Applications and Other Benefits - The proposed research will constitute a breakthrough in solution of problems related to efficient parallel computation of particle and fluid dynamics simulations. These problems occur throughout DOE, military and commercial sectors: the potential payoff is high. We plan to license or sell the solution to contractors for military and domestic applications such as disaster simulation (aerodynamic and hydrodynamic), Government agencies (hydrological and environmental simulations), and medical applications (e.g., in tomographic image reconstruction). Keywords - High-performance Computing, Graphic Processing Unit, Fluid/Particle Simulation. Summary for Members of Congress - Department of Energy has many simulation codes that must compute faster, to be effective. The Phase I research parallelized particle/fluid simulations for rocket combustion, for high-performance computing systems.},

doi = {10.2172/1019271},

journal = {},

number = ,

volume = ,

place = {United States},

year = {2011},

month = {7}

}