TY - GEN
T1 - Efficient GPU implementation for particle in cell algorithm
AU - Joseph, Rejith George
AU - Ravunnikutty, Girish
AU - Ranka, Sanjay
AU - D'Azevedo, Eduardo
AU - Klasky, Scott
PY - 2011
Y1 - 2011
N2 - Particle in cell (PIC) algorithm is a widely used method in plasma physics to study the trajectories of charged particles under electromagnetic fields. The PIC algorithm is computationally intensive and its time requirements are proportional to the number of charged particles involved in the simulation. The focus of the paper is to parallelize the PIC algorithm on Graphics Processing Unit (GPU). We present several performance trade-offs related to small shared memory and atomic operations on the GPU to achieve high performance.
AB - Particle in cell (PIC) algorithm is a widely used method in plasma physics to study the trajectories of charged particles under electromagnetic fields. The PIC algorithm is computationally intensive and its time requirements are proportional to the number of charged particles involved in the simulation. The focus of the paper is to parallelize the PIC algorithm on Graphics Processing Unit (GPU). We present several performance trade-offs related to small shared memory and atomic operations on the GPU to achieve high performance.
KW - CUDA
KW - GPU
KW - Particle in cell
UR - http://www.scopus.com/inward/record.url?scp=80053316886&partnerID=8YFLogxK
U2 - 10.1109/IPDPS.2011.46
DO - 10.1109/IPDPS.2011.46
M3 - Conference contribution
AN - SCOPUS:80053316886
SN - 9780769543857
T3 - Proceedings - 25th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2011
SP - 395
EP - 406
BT - Proceedings - 25th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2011
T2 - 25th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2011
Y2 - 16 May 2011 through 20 May 2011
ER -