研究目的
To improve the performance of a plasma physics simulation program called PCell by parallelizing it using OpenMP to reduce execution time and increase the temporal and spatial scales of simulations, enabling more detailed and longer studies of plasma phenomena.
研究成果
The parallelized PCell program achieved a significant speedup of nearly 42x with 128 threads, demonstrating efficient utilization of multi-core processors. It showed almost linear scalability with increases in spatial and temporal dimensions, enabling larger and more detailed plasma simulations. This improvement facilitates better study of plasma phenomena, such as magnetic reconnection, over extended periods and finer spatial granularities. Future work could involve combining OpenMP with MPI for cluster computing and optimizing for vectorization capabilities.
研究不足
The parallelization is limited to spatial domain calculations within each time step due to temporal dependencies; it does not parallelize across time steps. The study was conducted on a specific Intel Xeon Phi KNL architecture, which may limit generalizability to other hardware. The MHD model simplifies plasma physics and may not capture small-scale or non-Maxwellian particle behaviors.
1：Experimental Design and Method Selection:
The study involved parallelizing the PCell program using OpenMP to implement multithreaded execution for spatial domain calculations, focusing on the convection function which consumes most of the execution time. The methodology included analyzing the code for parallelizable sections, adding OpenMP directives, and optimizing variable declarations for thread safety.
2：Sample Selection and Data Sources:
The experiments used synthetic data generated by the PCell program based on user-defined parameters such as grid size, time steps, magnetic Reynolds number, and plasma velocity. No external datasets were used.
3：List of Experimental Equipment and Materials:
An Intel Xeon Phi KNL server with 64 cores @ 1.3 GHz and 96 GB RAM, configured in quadrant clustering mode. Software included the PCell program, OpenMP API, and compilers like GCC or ICC.
4：3 GHz and 96 GB RAM, configured in quadrant clustering mode. Software included the PCell program, OpenMP API, and compilers like GCC or ICC.
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: The program was executed with varying numbers of OpenMP threads (1 to 128), spatial grid sizes (from 100x100 to 1000x1000), and temporal iterations (1000 to 5000). Each test was run 20 times for statistical relevance, and execution times were measured and averaged.
5：0). Each test was run 20 times for statistical relevance, and execution times were measured and averaged.
Data Analysis Methods:
5. Data Analysis Methods: Speedup was calculated as the ratio of sequential execution time to parallel execution time. Scalability was assessed by plotting execution time against grid size and time steps, using linear and exponential trend analyses.
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