ck
Thrust
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ck | Thrust | |
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7 | 4 | |
2,293 | 4,839 | |
0.9% | - | |
6.9 | 6.9 | |
10 days ago | 3 months ago | |
C | C++ | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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ck
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Falsehoods programmers believe about undefined behavior
Maybe I'm missing something, but x is not volatile and the compiler is free to assume that it is not modified concurrently outside the bounds of C's memory model. Compilers can and do hoist out loop invariants, and https://github.com/concurrencykit/ck/commit/b54ae5c4ace9b94442bbb46858449069f566d269 seems like an example of compilers doing what you say they don't. What am I missing?
- Concurrency Kit
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A portable, license-free, lock-free data structure library written in C.
Recommend checking out http://concurrencykit.org instead.
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Does a thread have a better chance of acquiring a mutex if it's just in time? Or if it's been in the queue? Neither?
If you're interested in how other approaches work, or how one achieves concurrency on shared mutable state without mutual exclusion, would recommend checking out concurrency kit.
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Libdill: Structured Concurrency for C (2016)
There are plenty of practical solutions to the safe memory reclamation problem in C. The language just doesn't force one on you.
From epoch-based reclamation (https://github.com/concurrencykit/ck/blob/master/include/ck_..., especially with the multiplexing extension to Fraser's classic scheme), to quiescence schemes (https://liburcu.org/), or hazard pointers (https://github.com/facebook/folly/blob/master/folly/synchron..., or https://pvk.ca/Blog/2020/07/07/flatter-wait-free-hazard-poin...)... or even simple using a type-stable (https://www.usenix.org/legacy/publications/library/proceedin...) memory allocator.
In my experience, it's easier to write code that is resilient to hiccups in C than in Java. Solving SMR with GC only offers something close to lock-freedom when you can guarantee global GC pauses are short enough... and common techniques to bound pauses, like explicitly managed freelists land you back in the same problem space as C.
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C Deep
ck - Concurrency primitives, safe memory reclamation mechanisms and non-blocking data structures. BSD-2-Clause
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Super-expressive – Write regex in natural language
Indeed they do, https://github.com/concurrencykit/ck
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?
libcds - A C++ library of Concurrent Data Structures
CUB - THIS REPOSITORY HAS MOVED TO github.com/nvidia/cub, WHICH IS AUTOMATICALLY MIRRORED HERE.
libdill - Structured concurrency in C
ArrayFire - ArrayFire: a general purpose GPU library.
moodycamel - A fast multi-producer, multi-consumer lock-free concurrent queue for C++11
Boost.Compute - A C++ GPU Computing Library for OpenCL
HPX - The C++ Standard Library for Parallelism and Concurrency
laugh - Laughably simple yet effective Actor concurrency framework for C++20
Taskflow - A General-purpose Parallel and Heterogeneous Task Programming System