#Every Single Option Under The Sun
- optimization level options
- automatic crashing options
- debug info options
- swift internal options
- swift debug/development internal options
- linker-specific options
- mode options
#Every Single Option Under The Sun
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Putting cryptographic primitives together is a lot like putting a jigsaw puzzle together, where all the pieces are cut exactly the same way, but there is only one correct solution. Thankfully, there are some projects out there that are working hard to make sure developers are getting it right.
The following advice comes from years of research from leading security researchers, developers, and cryptographers. This Gist was [forked from Thomas Ptacek's Gist][1] to be more readable. Additions have been added from
Author: Chris Lattner
by "scientificninja" (Josh Petrie?)
To begin with, the term "engine" (specifically as it related to the game development world) has no strict definition. Therefore, in the interests of keeping everybody on the same page, I'll define the term as I intend to use it in this article. An "engine" is a collection of robust, reusable software subsystems (possibly including both code libraries and tools) designed to facilitate the development of actual games by addressing specific requirements. The requirements tend to be broadly-defined: rendering, audio, physics, et cetera. Particularly ambitious engines that address multiple broad requirement groups tend be to known as "game engines" rather than just "graphics engines" or "physics engines."
Now that that's out of the way, let's turn to the real issue: how to build engines, and more specifically, if you should even bother.
For any number of reasons, many neophyte game developers (and even some moderately experienced ones) seem to t
Concurrency is a domain I have wanted to explore for a long time because the locks and the race conditions have always intimidated me. I recall somebody suggesting concurrency patterns in golang because they said "you share the data and not the variables".
Amused by that, I searched for "concurrency in golang" and bumped into this awesome slide by Rob Pike: https://talks.golang.org/2012/waza.slide#1 which does a great job of explaining channels, concurrency patterns and a mini-architecture of load-balancer (also explains the above one-liner).
Let's dig in:
I was talking to a coworker recently about general techniques that almost always form the core of any effort to write very fast, down-to-the-metal hot path code on the JVM, and they pointed out that there really isn't a particularly good place to go for this information. It occurred to me that, really, I had more or less picked up all of it by word of mouth and experience, and there just aren't any good reference sources on the topic. So… here's my word of mouth.
This is by no means a comprehensive gist. It's also important to understand that the techniques that I outline in here are not 100% absolute either. Performance on the JVM is an incredibly complicated subject, and while there are rules that almost always hold true, the "almost" remains very salient. Also, for many or even most applications, there will be other techniques that I'm not mentioning which will have a greater impact. JMH, Java Flight Recorder, and a good profiler are your very best friend! Mea
--[[ | |
Original Author: https://github.com/Leandros | |
Updated Author: https://github.com/jakebesworth | |
MIT License | |
Copyright (c) 2018 Jake Besworth | |
Original Gist: https://gist.github.com/Leandros/98624b9b9d9d26df18c4 | |
Love.run 11.X: https://love2d.org/wiki/love.run | |
Original Article, 4th algorithm: https://gafferongames.com/post/fix_your_timestep/ | |
Forum Discussion: https://love2d.org/forums/viewtopic.php?f=3&t=85166&start=10 |