Title :
petaPar: A Scalable Petascale Framework for Meshfree/Particle Simulation
Author :
Leisheng Li ; Yingrui Wang ; Zhitao Ma ; Rong Tian
Author_Institution :
State Key Lab. of Comput. Archit., Inst. of Comput. Technol., Beijing, China
Abstract :
Since high performance computing sustained petaflops in 2008, numerical simulation entered a new era to use 10K to 100K processor cores in one single run of parallel computing. In pursuit of petascale computing, the challenges of scalability must be addressed. Petapar is a highly scalable simulation framework which implements two popular meshfree/particle methods, the smoothed particle hydrodynamics (SPH) and the material point method (MPM). The parallelization starts from the regular-grid-based domain decomposition. The scalability of the code is assured by fully overlapping of communication and computation, and a dynamic load balancing strategy. Petapar supports both flat MPI and MPI+Pthreads hybrid parallelization. The code is tested on Titan, which ranked first on the Top500 supercomputer list when our research work has been done in November 2012. Experiment results show that petaPar linearly scales up to 260K CPU cores with an excellent parallel efficiency of 100% and 96% for the SPH and MPM, respectively.
Keywords :
grid computing; message passing; multi-threading; numerical analysis; parallel processing; physics computing; resource allocation; MPI+Pthreads hybrid parallelization; MPM; SPH; Titan; Top500 supercomputer list; code scalability; dynamic load balancing strategy; flat MPI; high performance computing; material point method; meshfree/particle simulation; numerical simulation; parallel computing; petaPar; petaflops; petascale computing; processor cores; regular-grid-based domain decomposition; scalable petascale framework; smoothed particle hydrodynamics; Abstracts; Computational modeling; Distributed processing; Load management; Load modeling; Scalability; MPI+Pthreads; dynamic load balancing; meshfree/particle simulation; overlap of communication and compuation; petascale computing; scalability;
Conference_Titel :
Parallel and Distributed Processing with Applications (ISPA), 2014 IEEE International Symposium on
Conference_Location :
Milan
DOI :
10.1109/ISPA.2014.16