I wrote a Ruby Performance Checklist. Since then, I have seen the performance panel at RailsConf. Richard Schneeman (@schneems) then wrote an article on back-end performance, which starts by memory profiling tools like scout or rack-mini-profiler.
I like his article. My checklist started by Ruby code complexity. If you refactor well your code and make it simpler, it is actually the same strategy as advised by @schneems.
This begs the question: why do we always always discuss Ruby performance?
I shipped many applications, using a variety of frameworks, through my current 1 year challenge or startups. Ruby issues include low performance, such as servers needing more RAM, not able to sustain large traffic, or slow rendering. Since this is a recurring issue, here is a checklist to help developers get their Ruby app faster:
Code complexity Ruby’s simplicity and ease of use allows beginners and experienced developers alike to ship features in record time.
Part I - Apple’s Craftmanship I have used the original macbook, the 13” MacBook Air, the 13” Macbook pro, and 15” Macbook pros.
I loved the white plastic of the original macbook. It was better than any other computer I’ve used before, worked out of the box, and iMovie amazed me. Drag, drop, and five minutes later, you have a video.
I thought this is what computing should be.
Upon hearing about Facebook and Microsoft efforts to deploy bot platforms, a friend reacted:
So bots are a thing now? I programmed bots 20 years ago
He is a successful technology entrepreneur and has developed systems on many platforms. I can understand him. There were tutorials in kids’ magazines on writing a “Hello World” bot on MS-DOS 20 years ago. More impressive were the Artificial Intelligence (A.I.) found in games like Warcraft 3 or Command & Conquer.
In six months I have shipped many apps, as an entrepreneur or as a freelancer. I have also contributed to open source projects and advised other projects. Yet I’m educated as an electrical engineer, not as a software engineer and consider myself largely self-taught in the area of programming.
Jeff Atwood : Geeks went from being social outsiders, outcasts, and rejects to.. part of the 1% power structure, with all that implies.
Bonjour!
Nous offrons une expertise technique pour un résultat de qualité dans le développement de plateformes transactionnelles, de financement, de médias:
Étude et conception fonctionnelle et technique
Développement de solutions front, middle ou back-office
Développement d’applications iOS ou Android
Conduite de projet sur les technologies Ruby, Javascript, Lua, et plateformes mobiles; utilisation de base de données MySQL, Postgresql, ou redis, mongodb, ElasticSearch, Solr
Audit de code, de qualité et de performance des applications
NVIDIA graphic cards can be used to accelerate scientific computing, neural networks, video games and occasionally bitcoin computing.
Video editing and post-production also benefit greatly from NVIDIA cards with Adobe’s Mercury Engine or BMD’s Davinci resolve.
In the case of scientific computing, performance is directly proportional to the number of cuda cores. As long as cpu speed is > 2GHz and you have as much RAM as you have GPU RAM, you are all good.