Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.
| #!/bin/bash | |
| ########################################## | |
| ## SELECT EITHER tkc@a100 OR tkc@v100 ## | |
| ########################################## | |
| #SBATCH --account glc@a100 | |
| ########################################## | |
| #SBATCH --job-name=ProfParticle-Mesh # nom du job | |
| # Il est possible d'utiliser une autre partition que celle par default | |
| # en activant l'une des 5 directives suivantes : | |
| ########################################## |
| [Unit] | |
| Description=Set NVIDIA power limit above default | |
| [Service] | |
| Type=oneshot | |
| ExecStartPre=/usr/bin/nvidia-smi -pm 1 | |
| ExecStart=/usr/bin/nvidia-smi -pl 275 |
| #!/usr/bin/awk -f | |
| # This program is a copy of guff, a plot device. https://github.com/silentbicycle/guff | |
| # My copy here is written in awk instead of C, has no compelling benefit. | |
| # Public domain. @thingskatedid | |
| # Run as awk -v x=xyz ... or env variables for stuff? | |
| # Assumptions: the data is evenly spaced along the x-axis | |
| # TODO: moving average |
This is a short post that explains how to write a high-performance matrix multiplication program on modern processors. In this tutorial I will use a single core of the Skylake-client CPU with AVX2, but the principles in this post also apply to other processors with different instruction sets (such as AVX512).
Matrix multiplication is a mathematical operation that defines the product of
These are some simple bash functions and scripts for making CSV/TSV files prettier on the command line
see http://stefaanlippens.net/pretty-csv.html for more information.