Rust Performance Pitfalls — Llogiq on stuff
01 June 2017 Overall, Rust is pretty good for performance. Write the most simple, naive stuff, and it will usually run within a factor of two from optimized C/C++ code, without any further performance work on the code. With some investment into optimizations, matching or exceeding C’s speed should be possible in most cases. However, Rust makes some tradeoffs for different reasons than sheer speed,
Open Source @ Jane Street
Writing Performance Sensitive OCaml Code 1) OCaml Performance The notes fall into the following categories: notes about the cost of commonly used OCaml constructs and general recommendations that might help speed up OCaml code notes on reading OCaml assembly code so that you may understand what your own OCaml programs do on the CPU. When possible we have tried to motivate these with snippets of as
VMware Workstation Pro Documentation
Welcome to VMware Workstation Pro™ documentation. Use the navigation on the left to browse through documentation for your release of VMware Workstation Pro. We update the online documentation with the latest point release information. For example, version 17 contains all the updates for 17.x releases. All our documentation comes in PDF format, which you can access by selecting the PDF download ico
Exploring Kotlin’s hidden costs — Part 1
In 2016, Jake Wharton gave a series of interesting talks about Java’s hidden costs. Around the same period he also started advocating the use of the Kotlin language for Android development but barely mentioned the hidden costs of that language, aside from recommending the use of inline functions. Now that Kotlin is officially supported by Google in Android Studio 3, I thought it would be a good id
TimeComplexity - Python Wiki
This page documents the time-complexity (aka "Big O" or "Big Oh") of various operations in current CPython. Other Python implementations (or older or still-under development versions of CPython) may have slightly different performance characteristics. However, it is generally safe to assume that they are not slower by more than a factor of O(log n). Generally, 'n' is the number of elements current
ThreadScope - HaskellWiki
ThreadScope is a tool for performance profiling of parallel Haskell programs. The ThreadScope program allows us to debug the parallel performance of Haskell programs. Using ThreadScope we can check to see that work is well balanced across the available processors and spot performance issues relating to garbage collection or poor load balancing. Getting Started Have gtk on your machine? (Note that
Making Efficient use of memory in Haskell | Pusher blog
A summary of various techniques to make efficient use of memory in Haskell. In part two of my series on Haskell we spoke about identifying memory leaks and tuning the GC to improve performance. In part three we’ll be looking at a number of other techniques and libraries we have found that maximise efficient use of memory in Haskell when writing performance critical code. So without further ado. La
High-Performance Haskell
Functional programming with haskellfaradjpour610 views•49 slides Functional Programming by Examples using Haskellgoncharenko4.9K views•73 slides
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https://kb.vmware.com/s/article/2092664?language=en_US
http://www.lihaoyi.com/post/slides/Taming-the-Java-Virtual-Machine.pdf
http://blog.ezyang.com/2011/05/space-leak-zoo/