Synergia CUDA: GPU-accelerated accelerator modeling package

Q. Lu, J. Amundson
Scientific Computing Division, Fermi National Accelerator Laboratory, P.O.Box 500, Batavia, Illinois 60510, U.S.
Journal of Physics: Conference Series, 513, 052021, 2014


   title={Synergia CUDA: GPU-accelerated accelerator modeling package},

   author={Lu, Q and Amundson, J},

   booktitle={Journal of Physics: Conference Series},





   organization={IOP Publishing}


Download Download (PDF)   View View   Source Source   Source codes Source codes




Synergia is a parallel, 3-dimensional space-charge particle-in-cell accelerator modeling code. We present our work porting the purely MPI-based version of the code to a hybrid of CPU and GPU computing kernels. The hybrid code uses the CUDA platform in the same framework as the pure MPI solution. We have implemented a lock-free collaborative charge-deposition algorithm for the GPU, as well as other optimizations, including local communication avoidance for GPUs, a customized FFT, and fine-tuned memory access patterns. On a small GPU cluster (up to 4 Tesla C1070 GPUs), our benchmarks exhibit both superior peak performance and better scaling than a CPU cluster with 16 nodes and 128 cores. We also compare the code performance on different GPU architectures, including C1070 Tesla and K20 Kepler.
No votes yet.
Please wait...

Recent source codes

* * *

* * *

HGPU group © 2010-2024 hgpu.org

All rights belong to the respective authors

Contact us: