Parallel time integration using Batched BLAS (Basic Linear Algebra Subprograms) routines
We present an approach for integrating the time evolution of quantum systems. We leverage the computation power of graphics processing units (GPUs) to perform the integration of all time steps in parallel. The performance boost is especially prominent for small to medium-sized quantum systems. The d...
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| Vydáno v: | Computer physics communications Ročník 270; s. 108181 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier B.V
01.01.2022
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| ISSN: | 0010-4655, 1879-2944 |
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| Abstract | We present an approach for integrating the time evolution of quantum systems. We leverage the computation power of graphics processing units (GPUs) to perform the integration of all time steps in parallel. The performance boost is especially prominent for small to medium-sized quantum systems. The devised algorithm can largely be implemented using the recently-specified batched versions of the BLAS routines, and can therefore be easily ported to a variety of platforms. Our PARAllelized Matrix Exponentiation for Numerical Time evolution (PARAMENT) implementation runs on CUDA-enabled graphics processing units.
Program Title: PARAMENT
CPC Library link to program files:https://doi.org/10.17632/zy5v4xs89d.1
Developer's repository link:https://github.com/parament-integrator/parament
Licensing provisions: Apache 2.0
Programming language: C / CUDA / Python
Nature of problem: Time-integration of the Schrödinger equation with a time-dependent Hamiltonian for quantum systems with a small Hilbert space but many time-steps.
Solution method: A 4th order Magnus integrator, highly parallelized on a GPU, implemented using a small subset of BLAS functions for improved portability. |
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| AbstractList | We present an approach for integrating the time evolution of quantum systems. We leverage the computation power of graphics processing units (GPUs) to perform the integration of all time steps in parallel. The performance boost is especially prominent for small to medium-sized quantum systems. The devised algorithm can largely be implemented using the recently-specified batched versions of the BLAS routines, and can therefore be easily ported to a variety of platforms. Our PARAllelized Matrix Exponentiation for Numerical Time evolution (PARAMENT) implementation runs on CUDA-enabled graphics processing units.
Program Title: PARAMENT
CPC Library link to program files:https://doi.org/10.17632/zy5v4xs89d.1
Developer's repository link:https://github.com/parament-integrator/parament
Licensing provisions: Apache 2.0
Programming language: C / CUDA / Python
Nature of problem: Time-integration of the Schrödinger equation with a time-dependent Hamiltonian for quantum systems with a small Hilbert space but many time-steps.
Solution method: A 4th order Magnus integrator, highly parallelized on a GPU, implemented using a small subset of BLAS functions for improved portability. |
| ArticleNumber | 108181 |
| Author | Welter, Pol Herb, Konstantin |
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| Cites_doi | 10.1016/j.cpc.2018.02.019 10.1090/S0025-5718-1955-0071856-0 10.1023/A:1022311628317 10.1016/j.cpc.2012.11.019 10.1016/j.jmr.2004.11.004 10.1016/j.procs.2017.05.138 10.1002/cpa.3160070404 10.1016/j.parco.2010.01.006 10.1016/j.jpdc.2004.03.021 10.1016/j.jcp.2011.04.006 10.1016/j.physrep.2008.11.001 10.1137/S00361445024180 10.1088/1361-6633/aa5170 10.1063/1.448136 10.1145/322217.322232 |
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| Keywords | GPU programming Batched BLAS Magnus integrators Parallel time integration Schrödinger equation Exponential integrators |
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| SubjectTerms | Batched BLAS Exponential integrators GPU programming Magnus integrators Parallel time integration Schrödinger equation |
| Title | Parallel time integration using Batched BLAS (Basic Linear Algebra Subprograms) routines |
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