Parallel computing: Difference between revisions
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(Created page with "= Resources = * https://github.com/FNLCR-Bioinformatics/ProgrammersCorner-Parallelization/blob/master/parallelization_eb2018.pdf Parallelization Strategies] by Eckart Bindewal...") |
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= Resources = | = Resources = | ||
* https://github.com/FNLCR-Bioinformatics/ProgrammersCorner-Parallelization/blob/master/parallelization_eb2018.pdf Parallelization Strategies] by Eckart Bindewald | * [https://github.com/FNLCR-Bioinformatics/ProgrammersCorner-Parallelization/blob/master/parallelization_eb2018.pdf Parallelization Strategies] by Eckart Bindewald | ||
** OpenMP (C++ & Fortran 90) | ** OpenMP (C++ & Fortran 90) | ||
** Threading in Java | ** Threading in Java | ||
| Line 6: | Line 6: | ||
** C++ Intel Threading Blocks | ** C++ Intel Threading Blocks | ||
** GPU | ** GPU | ||
* [https://en.wikipedia.org/wiki/Concurrent_computing Concurrent computing] | |||
** [https://en.wikipedia.org/wiki/Linearizability Atomic operations] - Atomic operations in concurrent programming are program operations that run completely independently of any other processes. | |||
* [https://cran.r-project.org/web/packages/GPUmatrix/index.html GPUmatrix]: Basic Linear Algebra with GPU | |||
Latest revision as of 18:35, 27 May 2023
Resources
- Parallelization Strategies by Eckart Bindewald
- OpenMP (C++ & Fortran 90)
- Threading in Java
- Threading in R (mclapply)
- C++ Intel Threading Blocks
- GPU
- Concurrent computing
- Atomic operations - Atomic operations in concurrent programming are program operations that run completely independently of any other processes.
- GPUmatrix: Basic Linear Algebra with GPU