Kernels
nwchem-tce-triples-kernels
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| Kernels | nwchem-tce-triples-kernels | |
|---|---|---|
| 6 | 1 | |
| 401 | 11 | |
| 0.5% | - | |
| 7.2 | 6.8 | |
| 13 days ago | 4 months ago | |
| C | C | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
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Kernels
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Can you give me some proof that storing multidimansional data into a 1d array is the standard and best way to do it?
https://github.com/ParRes/Kernels/tree/default/C1z has some examples I’ve tested in the past. 2d is in the filenames of the relevant ones.
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Fortran on GPU
I've evaluated all of these against each other. One presentation is https://www.nvidia.com/en-us/on-demand/session/gtcspring22-s41620/ (sorry, you have to register - it's not my preference). The performance numbers there are based on code derived from https://github.com/ParRes/Kernels/tree/default/FORTRAN (the code differences are not interesting). Another comparison is found in https://github.com/jeffhammond/nwchem-tce-triples-kernels, which is more complicated in some ways.
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Cross Platform Computing Framework?
If you want to learn by viewing code side by side, https://github.com/ParRes/Kernels/tree/default/Cxx11 might be useful. I haven’t kept up with my RAJA ports because they kept making breaking changes in the API a few years ago (should be stable now).
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Co-Array MPI issue.
Try https://github.com/ParRes/Kernels/tree/default/FORTRAN coarray programs. Those were written by people who know what they’re doing and have been proven to execute correctly before. That might help you understand if your implementation is broken.
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I am in grad school and starting a CFD class soon. I am proficient in Python and Matlab, but the course requires Fortran. How rough of a time will I have coding difficult concepts in a new language? I’m hoping my logic skills will overcome any syntax issues I run into, but wanted to ask
https://github.com/ParRes/Kernels has examples of the same thing written in Fortran, MATLAB/Octave and Numpy, if it helps.
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Small Open Source HPC Code Recommendations
You absolutely went to take a look at the Parallel Research Kernels (PRK) repo at https://github.com/ParRes/Kernels .
nwchem-tce-triples-kernels
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Fortran on GPU
I've evaluated all of these against each other. One presentation is https://www.nvidia.com/en-us/on-demand/session/gtcspring22-s41620/ (sorry, you have to register - it's not my preference). The performance numbers there are based on code derived from https://github.com/ParRes/Kernels/tree/default/FORTRAN (the code differences are not interesting). Another comparison is found in https://github.com/jeffhammond/nwchem-tce-triples-kernels, which is more complicated in some ways.
What are some alternatives?
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analisis-numerico-computo-cientifico - Análisis numérico y cómputo científico
miniWeather - A parallel programming training mini app simulating weather-like flows
miniMD - MiniMD Molecular Dynamics Mini-App
ompi - Open MPI main development repository
john - John the Ripper jumbo - advanced offline password cracker, which supports hundreds of hash and cipher types, and runs on many operating systems, CPUs, GPUs, and even some FPGAs
computecpp-sdk - Collection of samples and utilities for using ComputeCpp, Codeplay's SYCL implementation
JohnTheRipper - John the Ripper jumbo - advanced offline password cracker, which supports hundreds of hash and cipher types, and runs on many operating systems, CPUs, GPUs, and even some FPGAs [Moved to: https://github.com/openwall/john]
Shareaza - Shareaza is a peer-to-peer client for Windows that allows you to download any file-type found on several popular P2P networks.