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Kernels Alternatives
Similar projects and alternatives to Kernels
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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
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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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
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computecpp-sdk
Discontinued Collection of samples and utilities for using ComputeCpp, Codeplay's SYCL implementation
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nwchem-tce-triples-kernels
NWChem TCE CCSD(T) loop-driven kernels for performance optimization experiments
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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JohnTheRipper
Discontinued 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]
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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better Kernels alternative or higher similarity.
Kernels reviews and mentions
Posts with mentions or reviews of Kernels.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-10-21.
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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 .
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A note from our sponsor - SaaSHub
www.saashub.com | 26 Apr 2024
Stats
Basic Kernels repo stats
6
401
7.2
11 days ago
ParRes/Kernels is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
The primary programming language of Kernels is C.
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