fast_io
Thrust
fast_io | Thrust | |
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2 | 4 | |
536 | 4,839 | |
6.5% | - | |
6.2 | 6.9 | |
7 days ago | 3 months ago | |
C++ | C++ | |
MIT License | GNU General Public License v3.0 or later |
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fast_io
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Is there a good cross-platform (Windows / Linux) C or C++ library for file I/O?
Are you asking fast_io ???
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Should I use platform dependent file IO instead of basic_fstream when performance matters
https://github.com/cppfastio/fast_io check it out
Thrust
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AMD's CDNA 3 Compute Architecture
this is frankly starting to sound a lot like the ridiculous "blue bubbles" discourse.
AMD's products have generally failed to catch traction because their implementations are halfassed and buggy and incomplete (despite promising more features, these are often paper features or career-oriented development from now-departed developers). all of the same "developer B" stuff from openGL really applies to openCL as well.
http://richg42.blogspot.com/2014/05/the-truth-on-opengl-driv...
AMD has left a trail of abandoned code and disappointed developers in their wake. These two repos are the same thing for AMD's ecosystem and NVIDIA's ecosystem, how do you think the support story compares?
https://github.com/HSA-Libraries/Bolt
https://github.com/NVIDIA/thrust
in the last few years they have (once again) dumped everything and started over, ROCm supported essentially no consumer cards and rotated support rapidly even in the CDNA world. It offers no binary compatibility support story, it has to be compiled for specific chips within a generation, not even just "RDNA3" but "Navi 31 specifically". Etc etc. And nobody with consumer cards could access it until like, six months ago, and that still is only on windows, consumer cards are not even supported on linux (!).
https://geohot.github.io/blog/jekyll/update/2023/06/07/a-div...
This is on top of the actual problems that still remain, as geohot found out. Installing ROCm is a several-hour process that will involve debugging the platform just to get it to install, and then you will probably find that the actual code demos segfault when you run them.
AMD's development processes are not really open, and actual development is silo'd inside the company with quarterly code dumps outside. The current code is not guaranteed to run on the actual driver itself, they do not test it even in the supported configurations.
it hasn't got traction because it's a low-quality product and nobody can even access it and run it anyway.
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Parallel Computations in C++: Where Do I Begin?
For a higher level GPU interface, Thrust provides "standard library"-like functions that run in parallel on the GPU (Nvidia only)
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What are some cool modern libraries you enjoy using?
For GPGPU, I like thrust. C++-idiomatic way of writing CUDA code, passing between host and device, etc.
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A vision of a multi-threaded Emacs
Users should work with higher level primitives like tasks, parallel loops, asynchronous functions etc. Think TBB, Thrust, Taskflow, lparallel for CL, etc.
What are some alternatives?
RapidJSON - A fast JSON parser/generator for C++ with both SAX/DOM style API
CUB - THIS REPOSITORY HAS MOVED TO github.com/nvidia/cub, WHICH IS AUTOMATICALLY MIRRORED HERE.
mio - Cross-platform C++11 header-only library for memory mapped file IO
ArrayFire - ArrayFire: a general purpose GPU library.
webxx - Declarative, composable, concise & fast HTML & CSS components in C++
Boost.Compute - A C++ GPU Computing Library for OpenCL
libuv - Cross-platform asynchronous I/O
HPX - The C++ Standard Library for Parallelism and Concurrency
llfio - P1031 low level file i/o and filesystem library for the C++ standard
moodycamel - A fast multi-producer, multi-consumer lock-free concurrent queue for C++11
Taskflow - A General-purpose Parallel and Heterogeneous Task Programming System
moderngpu - Patterns and behaviors for GPU computing