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Thoughts on code
Taking out the garbage
https://jackmott.github.io/programming/2016/09/01/performance-in-the-large.html
Taking out the garbage. The cost of allocations. Sep 1, 2016. The Naive Approach, in C Sharp. Simple enough, and the approach above would and does work fine for many games. It isn’t completely dumb, it uses an array backed List to keep track of things, because arrays are fast, and it pre-allocates them to the proper size when it can to avoid wasting memory and cpu on growing the array. Modern computers are fast, so this shouldn’t be a problem! Some other troubling stats (collected with Perfmon) are clear:.
PVS-Studio C#
https://jackmott.github.io/programming/2016/11/01/PVS-Studio.html
Nov 1, 2016. Is a popular static analysis tool in the C world, and plenty of articles have been written about the kinds of bugs it can find in C projects, such as this entertaining one about the Unreal Engine. About year ago they added C# support, and have steadily been adding more C# analysis features since. Today I grabbed version 6.10 and ran it on my code base at work, which is a fairly large ASP/MVC web application. Here are some of the things it found:. Expression ‘result.Succes’ is always true.
When Big O Fools Ya
https://jackmott.github.io/programming/2016/08/20/when-bigo-foolsya.html
When Big O Fools Ya. An Array Love Story. Aug 20, 2016. Big O notation is a great tool. It allows one to quickly make smart choices among various data structures and algorithms. But sometimes a casual Big O analysis can fool us if we don’t think carefully about the impact of constant factors. One such example comes up very often when programming on modern CPUs, and that is when choosing between an Array, and a List, or Tree type structure. Memory, Slow Slow Memory. Linked List vs Array List. But, to know...
Think Before You Parallelize
https://jackmott.github.io/programming/2016/08/30/think-before-you-parallelize.html
Think Before You Parallelize. A tour of parallel abstractions. Aug 30, 2016. Don’t Parallelize when it is already Parallelized. What you forgot was that the web server was already parallelizing things at a higher level, using all 24 production cores to handle multiple requests simultaneously. When your paralellized function fires up, all the other cores are busy with other requests. So you take the hit of whatever overhead was required to parallelize the function with no benefit. This may only have 1 or ...
Adventures in F# Performance
https://jackmott.github.io/programming/2016/08/13/adventures-in-fsharp.html
Adventures in F# Performance. Aug 13, 2016. Apologies to functional programming enthusiasts, what follows is a lot of imperative code. What can I say, it is the array library after all! After working on an F# SIMD Array library. For a while, and learning about some nice bench marking tools for .NET thanks to Jared Hester. I got the idea to try contributing to the F# core libraries myself. I had been poking around in the official Microsoft F# repo. Overhead, when everything is filtered:. Suggested a solut...
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Code Thoughts
Nov 1, 2016. Sep 29, 2016. A useful gamedev library? Sep 1, 2016. Taking out the garbage. The cost of allocations. Aug 30, 2016. Think Before You Parallelize. A tour of parallel abstractions. Aug 20, 2016. When Big O Fools Ya. An Array Love Story. Aug 13, 2016. Adventures in F# Performance. Jul 22, 2016. Making the obvious code fast. A tour of Go, Java, C#, F#, Rust, Javascript and C. Jul 11, 2016. Jul 1, 2016.
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