Development of an equation-based parallelization method for multiphase particle-in-cell simulations
نویسندگان
چکیده
Manufacturers have been developing new graphics processing unit (GPU) nodes with large capacity, high bandwidth memory and very intra-node interconnects. This enables moving amounts of data between GPUs on the same node at low cost. However, small packet bandwidths latencies not decreased, which makes global dot products expensive. These characteristics favor a kind problem decomposition called “equation decomposition” rather than traditional domain decomposition. In this approach, each GPU is assigned one equation set to solve in parallel so that frequent expensive product synchronization points distributed linear solvers are eliminated. exchange, method involves infrequent movement state variables over bandwidth, To test theory, our flagship code Multiphase Flow Interphase eXchanges (MFiX) was ported TensorFlow. known as MFiX-AI can produce near identical results original version MFiX significant acceleration multiphase particle-in-cell (MP-PIC) simulations. The performance single 4 NVIDIA A100s connected NVLINK 2.0 shown be competitive 1000 CPU cores (25 nodes) JOULE supercomputer, leading an energy savings up 90%. substantial benefit for small- intermediate-sized problems. expected grow become more powerful. Further, poised accept native artificial intelligence/machine learning models further development.
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ژورنال
عنوان ژورنال: Engineering With Computers
سال: 2022
ISSN: ['0177-0667', '1435-5663']
DOI: https://doi.org/10.1007/s00366-022-01768-6