Optimal size of the block in block GMRES on GPUs: computational model and experiments
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Center for Computing Research
- Temple Univ., Philadelphia, PA (United States)
The block version of GMRES (BGMRES) is most advantageous over the single right hand side (RHS) counterpart when the cost of communication is high while the cost of floating point operations is not. This is the particular case on modern graphics processing units (GPUs), while it is generally not the case on traditional central processing units (CPUs). Here, in this paper, experiments on both GPUs and CPUs are shown that compare the performance of BGMRES against GMRES as the number of RHS increases, with a particular focus on GPU performance. The experiments indicate that there are many cases in which BGMRES is slower than GMRES on CPUs, but faster on GPUs. Furthermore, when varying the number of RHS on the GPU, there is an optimal number of RHS where BGMRES is clearly most advantageous over GMRES. A computational model for the GPU is developed using hardware specific parameters, providing insight towards how the qualitative behavior of BGMRES changes as the number of RHS increase, and this model also helps explain the phenomena observed in the experiments.
- Research Organization:
- Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
- Grant/Contract Number:
- NA0003525
- OSTI ID:
- 2311786
- Report Number(s):
- SAND--2023-10797J
- Journal Information:
- Numerical Algorithms, Journal Name: Numerical Algorithms Vol. 92; ISSN 1017-1398
- Publisher:
- SpringerCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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