https://www.youtube.com/playlist?list=PLKK11Ligqitg9MOX3-0tFT1Rmh3uJp7kA
| F.<x> = GF(2^8, modulus=GF(2^9).fetch_int((2^8) + 0x1b)) | |
| A = Matrix(F, 64, 64) | |
| v = [137, 110, 79, 199, 218, 137, 20, 176, 83, 199, 244, 109, 98, 39, 156, 116, 86, 219, 77, 125, 243, 0, 101, 85, 143, 123, 124, 37, 120, 223, 213, 198, 67, 193, 214, 169, 213, 35, 156, 16, 56, 210, 166, 58, 207, 215, 37, 78, 77, 204, 32, 205, 154, 92, 207, 79, 233, 97, 252, 86, 190, 25, 139, 240] | |
| matrix = [[16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79], [44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107], [29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56 |
| import requests | |
| import base64 | |
| import sys | |
| # Generates a Microsoft Symbol Server link from a filename and a file hash using VirusTotal. | |
| # Example: | |
| # microsoft-symbol-server-link-gen.py srv2.sys pD5a0dKSCg7Kc0g1yDyWEX8n8ogPj/niCIy4yUR7WvQ= | |
| # Details: | |
| # https://m417z.com/Introducing-Winbindex-the-Windows-Binaries-Index/ |
Lately I have been busy reading some new books on Domain Driven Design (DDD) and software architecture -- including a short yet eye-opening one in Python and a great one in F#. At the same time, it seems that more people in the Functional Programming world are looking at more formal approaches to modelling -- some examples here. This has brought some thought from the background of my brain about how we should model, organize, and architect software using the lessons we've learnt from functional programming.
Before moving on, let me be clear about this being just a dump of some thoughts, not always well-defined, definite
This article aims at explaining lambda calculus in a more approachable less 'mathy' manner.
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Memoization: Memoization is an optimization technique used primarily to speed up computer programs by caching the result of expensive function calls and returning the cached result when fed with the same input.
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Pure Function: A pure function is a function whose computation does not depend on globally declared variables, it does no I/O or mutations. All it does is return a value after doing a bunch of computations on the arguments it recieves. For a given set of arguments, a pure function will always return the same value. Thus, a pure function is one that is memoizable.
Archived. Please see https://www.sainnhe.dev/post/status-line-config
First of all, install a nerd font, and apply it: nerd font
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
| using System; | |
| using System.IO; | |
| using System.IO.Compression; | |
| using System.Text; | |
| using System.Collections.Generic; | |
| using System.Configuration.Install; | |
| using System.Runtime.InteropServices; | |
Once in a while, you may need to cleanup resources (containers, volumes, images, networks) ...
// see: https://github.com/chadoe/docker-cleanup-volumes
$ docker volume rm $(docker volume ls -qf dangling=true)
$ docker volume ls -qf dangling=true | xargs -r docker volume rm

