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NVIDIA
cub
Cuda2021–2024
NVIDIA / cub · Archived

cub

[ARCHIVED] Cooperative primitives for CUDA C++. See https://github.com/NVIDIA/cccl

2Distinct people
3Mentions
0Explicit recommenders
1.8KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

[ARCHIVED] Cooperative primitives for CUDA C++. See https://github.com/NVIDIA/cccl

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 12:54:37 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year3 dated mentions

Observed mentions: 2021-07-06 20:55:29 UTC to 2024-11-30 14:54:12 UTC.

012021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20212022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20222023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC101
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC101
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101

What Hacker News says

3 sources
OpenCL had a bit of a "second-mover curse" where instead of trying to solve one problem (GPGPU acceleration) it tried to solve everything (a generalized framework for heterogeneous dispatch) and it just kinda sucks to actually use. It's not that it's slower or faster, in principle it should be the same speed when dispatched to the hardware (+/- any C/C++ optimization gotchas of course), but it just requires an obscene amount of boilerplate to "draw the first triangle" (or, launch the first kernel), much like Vulkan, and their own solution is still a pretty clos HIP was supposed to rectify this, but now you're buying into AMD's custom language and its limitations... and there are limitations, things that CUDA can do that HIP can't (texture unit access was an early one - and texture units aren't just for texturing, they're for coalescing a
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ll kinds of 2d/3d/higher-dimensional memory access). And AMD has a history of abandoning these projects after a couple years and leaving them behind and unsupported... like their Thrust framework counterpart, Bolt, which hasn't been updated in 8 years now. https://github.com/HSA-Libraries/Bolt The old bit about "Vendor B" leaving behind a "trail of projects designed to pad resumes and show progress to middle managers" still reigns absolutely true with AMD. AMD has a big uphill climb in general to shake this reputation about being completely unserious with their software... and I'm not even talking about drivers here. This is even more the widespread community perception with their GPGPU/ML efforts than with their drivers. http://richg42.blogspot.com/2014/05/the-truth-on-opengl-driv... AMD doesn't have a library of warp-level/kernel-level/global "software primitives" like Cuda Unbound or Thrust either. So instead of writing your application, you are writing the primitives library, or writing your own poor implementation of them. https://github.com/NVIDIA/cub https://github.com/NVIDIA/thrust It's just a fractal problem of "the software doesn't exist and AMD would really rather you write it for them" all the way down and nobody wants to do that instead of doing their own work. AMD is the one who benefits from the rewrite, for everyone else it's a "best case scenario it works the same as what we've already got", so if AMD isn't gonna do it then pretty much nobody else is gonna leap on it. And then AMD has poor adoption and no software and the cycle continues. AMD really really just needs to get serious and hire a half dozen engineers to sit there and write this software, cause it's just not going to happen otherwise. It's a drop in the bucket vs the sales to be realized here even in the medium term, like one big ML sale would probably more than pay those salaries. They're not doing it because they're cheap or they're doing it because they're not really serious, take your pick, but, AMD is no longer that broke, they can afford it and it makes financial sense. Again, not a "nice" thing to say but it's the cold truth here. I feel like I've made some variation on this post about every 6 months for like 5 years now but it's still relevant. If you as a vendor don't care about writing good code for key features/libraries for your product, nobody else is either, and you'll never get uptake. It's the same thing with AMD/ATI not embedding developers with studios to get those optimizations for their architectures. Console lock-in will only get you so far. If you don't care about the product as a vendor, nobody else will either. It's remarkable how much flak Jensen got for "NVIDIA is a software company now" back in 2009, and how people still don't get it, AMD is not a software company and that's why they keep failing. Writing the framework that turns into StableDiffusion and sells a billion dollars of GPUs is the NVIDIA business model, AMD keeps trying to jump straight to the "sell a billion dollars of GPUs" part and keeps failing.
In Nvidia in the Valley
This is the first time I've heard of the term "decoupled look-back". But I see that it refers to CUB's implementation of device-wide scan. I briefly looked at the code, and came across: https://github.com/NVIDIA/cub/blob/main/cub/agent/agent_scan... I'm seeing lots of calls to "CTA_SYNC()", which ends up being just a "__syncthreads" (a simple thread-barrier). See: https://github.com/NVIDIA/cub/blob/a8910accebe74ce043a13026f... I admit that I'm looking rather quickly though, but... I'm not exactly seeing where this mysterious "spinlock" is that you're talking about. I haven't tried very hard yet but maybe you can point out what code exactly in this device_scan / decoupled look-back uses a spinlock? Cause I'm just not seeing it. ---------- And of course: a call to cub's "device scan" is innately ordered to kernel-start / kernel-end. So ther
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e's your synchronization mechanism right there and then.
In Programming Language Memory Models

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