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| #!/bin/bash | |
| ### steps #### | |
| # verify the system has a cuda-capable gpu | |
| # download and install the nvidia cuda toolkit and cudnn | |
| # setup environmental variables | |
| # verify the installation | |
| ### | |
| ### to verify your gpu is cuda enable check |
// ~~~~~~~~~~~~~~~~~~~~~~ Optlam.js ~~~~~~~~~~~~~~~~~~~~~~
// An optimal Ξ»-calculus normalizer written in JavaScript.
// ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
// Optlam.js is a simple, optimal (in Levy's sense) Ξ»-calculus evaluator using
// interaction nets. It is, currently, as far as I know, the fastest
// implementation of functions in the world. It uses Lamping's Abstract
// Algorithm - that is, the so called (and problematic) "oracle" is avoided
So I was reading Hacker News and decided to read the comments in the thread about H.265 being approved. Pretty close to the top was this comment about VP9, Google's future video format. I have some words of my own about it and other future formats at the bottom of this post, but what jumped out from the comment to me was this part:
Many have already implemented VP8 (which is also slightly better than h.264 at this point)
The comparison linked to back up that statement is faulty for several reasons, such as not providing the source material used (hell, he doesn't even name the source material), exact encoding settings used (no, some random profiles are not enough), not providing the resulting encodes, only providing a
Install, build and debug a react native app in WSL2 (Windows Subsystem for Linux) and Ubuntu.
| sudo yum update | |
| sudo yum install ruby | |
| sudo yum install wget | |
| wget https://{bucket-name}.s3.amazonaws.com/latest/install | |
| chmod +x ./install | |
| sudo ./install auto | |
| ## bucket-name represents one of the following: | |
| ## aws-codedeploy-us-east-1 for instances in the US East (N. Virginia) region | |
| ## aws-codedeploy-us-west-1 for instances in the US West (N. California) region |
| #!/usr/bin/env python3 | |
| from pymavlink import mavutil, mavlink | |
| class CourseAverager: | |
| MSG_TYPE = 'GLOBAL_POSITION_INT' | |
| def __init__(self, mavlink_connection, request_rate=1, decay_rate=0.95, initial_course=(0, 0)): | |
| self.master = mavlink_connection | |
| self.request_message(request_rate) |
| // Package main is a sample macOS-app-bundling program to demonstrate how to | |
| // automate the process described in this tutorial: | |
| // | |
| // https://medium.com/@mattholt/packaging-a-go-application-for-macos-f7084b00f6b5 | |
| // | |
| // Bundling the .app is the first thing it does, and creating the DMG is the | |
| // second. Making the DMG is optional, and is only done if you provide | |
| // the template DMG file, which you have to create beforehand. | |
| // | |
| // Example use: |
Note that this script will try to auto install OpenFoam from souce (which means will download source code) and then compile on local machine. This script is primarily targated at installing old-releases of OpenFOAM which do not have binary installation packages pre-compiled on APT.
The entire installation time cost approximately 2-6 hours depends on network bandwidth and CPU memory power.
