analisis-numerico-computo-cientifico
Kernels
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| analisis-numerico-computo-cientifico | Kernels | |
|---|---|---|
| 1 | 6 | |
| 44 | 401 | |
| - | 0.5% | |
| 0.0 | 7.2 | |
| over 1 year ago | 9 days ago | |
| Jupyter Notebook | C | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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analisis-numerico-computo-cientifico
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 .
What are some alternatives?
osmnx-examples - Gallery of OSMnx tutorials, usage examples, and feature demonstations.
grbl-L-Mega - An open source, embedded, high performance g-code-parser and CNC milling controller written in optimized C that will run on an Arduino Mega2560. Forked from GRBL modified for use on a lathe with spindle sync threading
docker-curriculum - :dolphin: A comprehensive tutorial on getting started with Docker!
miniMD - MiniMD Molecular Dynamics Mini-App
DeepLearning - Contains all my works, references for deep learning
ompi - Open MPI main development repository
vqgan-clip-generator - Implements VQGAN+CLIP for image and video generation, and style transfers, based on text and image prompts. Emphasis on ease-of-use, documentation, and smooth video creation.
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
laser - The HPC toolbox: fused matrix multiplication, convolution, data-parallel strided tensor primitives, OpenMP facilities, SIMD, JIT Assembler, CPU detection, state-of-the-art vectorized BLAS for floats and integers
computecpp-sdk - Collection of samples and utilities for using ComputeCpp, Codeplay's SYCL implementation
cocp - Source code for the examples accompanying the paper "Learning convex optimization control policies."
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]