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
| #!/usr/bin/env python3 | |
| """ | |
| License: MIT License | |
| Copyright (c) 2023 Miel Donkers | |
| Very simple HTTP server in python for logging requests | |
| Usage:: | |
| ./server.py [<port>] | |
| """ | |
| from http.server import BaseHTTPRequestHandler, HTTPServer |
| #!/usr/bin/env python | |
| """ | |
| How to use it: | |
| 1. Just `kill -2 PROCESS_ID` or `kill -15 PROCESS_ID`, | |
| The Tornado Web Server Will shutdown after process all the request. | |
| 2. When you run it behind Nginx, it can graceful reboot your production server. | |
| """ | |
| import time |
Hello, brethren :-)
As it turns out, the current version of FFmpeg (version 3.1 released earlier today) and libav (master branch) supports full H.264 and HEVC encode in VAAPI on supported hardware that works reliably well to be termed "production-ready".
| """ | |
| Implementations of: | |
| Probabilistic Matrix Factorization (PMF) [1], | |
| Bayesian PMF (BPMF) [2], | |
| Modified BPFM (mBPMF) | |
| using `pymc3`. mBPMF is, to my knowledge, my own creation. It is an attempt | |
| to circumvent the limitations of `pymc3` w/regards to the Wishart distribution: |
| """ | |
| License: BSD | |
| Author: Mathieu Blondel | |
| Implements three algorithms for projecting a vector onto the simplex: sort, pivot and bisection. | |
| For details and references, see the following paper: | |
| Large-scale Multiclass Support Vector Machine Training via Euclidean Projection onto the Simplex | |
| Mathieu Blondel, Akinori Fujino, and Naonori Ueda. |
| """l-bfgs-b L1-Logistic Regression solver""" | |
| # Author: Vlad Niculae <vlad@vene.ro> | |
| # Suggested by Mathieu Blondel | |
| from __future__ import division, print_function | |
| import numpy as np | |
| from scipy.optimize import fmin_l_bfgs_b |
This simple script will take a picture of a whiteboard and use parts of the ImageMagick library with sane defaults to clean it up tremendously.
The script is here:
#!/bin/bash
convert "$1" -morphology Convolve DoG:15,100,0 -negate -normalize -blur 0x1 -channel RBG -level 60%,91%,0.1 "$2"
| Copyright 2013 Robert T. McGibbon | |
| Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: | |
| The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. | |
| THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE O |
| /* Turn off features that will not work on Windows. | |
| */ | |
| #define NGETRUSAGE | |
| #define NALLSIGNALS |
