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swiftshader
C++2017–2023
google / swiftshader

swiftshader

SwiftShader is a high-performance CPU-based implementation of the Vulkan graphics API. Its goal is to provide hardware independence for advanced 3D graphics.

Creative & MediaHardware & Embedded
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6Distinct people
7Mentions
0Explicit recommenders
2.6KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

SwiftShader is a high-performance CPU-based implementation of the Vulkan graphics API. Its goal is to provide hardware independence for advanced 3D graphics.

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, 3:56:07 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 year7 dated mentions

Observed mentions: 2017-12-06 02:59:22 UTC to 2023-09-28 18:08:05 UTC.

01232017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20172018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023

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
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC101
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC000
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC211
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC303
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC101

What Hacker News says

7 sources
modeless·Apr 18, 2020
> Vulkan and WebGPU will not fall back WebGL does automatically fall back to the CPU in Chrome, via SwiftShader[1]. WebGPU hasn't shipped yet but I think it's likely that a CPU backend with SwiftShader will be available eventually. And SwiftShader implements Vulkan now too, so while it's not automatic for Vulkan you can certainly have a fallback if you want it. [1] https://github.com/google/swiftshader
In A Taste of GPU Compute [video]
headlessclayton·Feb 9, 2020
Author here. Marl was originally written for SwiftShader¹ a pure-software implementation of the Vulkan graphics API, which needs to run on desktop and embedded devices, with CPUs ranging from 2 to many cores. SwiftShader executes a number of parallel rasterization tasks which have complex blocking dependencies on one another. Marl attempts to simplify the problem of running and synchronizing tasks. It shamelessly borrows quite a few concepts from golang, simplifying fan-out, fan-in style problems. The main reason of why not just use pthreads / std::thread really comes down to blocking tasks. Using regular threads, you either need to know your dependency graph ahead of time to ensure tasks are executed in dependency order (blockless), or you likely end up spinning up many more threads than you actually need to allow things to block and wai
Read the rest
t on others to complete. SwiftShader has tight requirements on the number of threads we're allowed to create, so Marl was our solution. Marl is even capable of running single-threaded with no code changes to the tasks. It's worth mentioning we also evaluated other scheduler solutions using completion callbacks, but "callback hell" was something we were keen to avoid. I'm still looking into Marl optimizations, but it is already pretty fast. Fiber switching is notably faster than OS context switching for many of the benchmarks we've done. ¹ https://github.com/google/swiftshader
In A hybrid thread / fiber task scheduler written in C++ 11
Mathnerd314·Oct 25, 2019
CUDA is proprietary to NVidia, and is pretty much the standard for GPU computing. AMD's been chipping away with OpenCL, Vulkan/GLSL, https://github.com/RadeonOpenCompute/hcc/wiki, etc. but not much luck so far. I wouldn't say AMD's been "sticking with" OpenCL, if anything it seems like they will deprecate it in a few years, as the plan is to fold OpenCL into Vulkan. I guess it is possible to use OpenCL on the CPU as well, but it seems to be intended mostly for testing purposes. The Crysis software renderer uses threads: https://github.com/google/swiftshader/blob/master/src/Common...
In Beating C with Futhark Running on GPU

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