amd/Chromium-WebCL

WebCL implementation for Chromium

Owned by AMD

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amd/Chromium-WebCL has 90+ stars and 10+ forks on GitHub, is written in C, and was last pushed on Aug 6, 2014. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 12 minutes ago
Added to GitGenius on October 10th, 2026
Created on January 28th, 2014
Open Issues & Pull Requests: 11 (+0)
GitHub issues: Enabled
Number of forks: 17
Total Stargazers: 95 (+0)
Total Subscribers: 22 (+0)

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Detailed Description

Chromium-WebCL is a WebCL implementation for Chromium that enables GPU-accelerated parallel computing in web browsers through the WebCL standard.

WebCL allows web applications to access the computational power of GPUs and multi-core CPUs by exposing a JavaScript binding to OpenCL. This implementation integrates WebCL support directly into Chromium, enabling developers to write compute-intensive code that runs on heterogeneous hardware. The approach involves patching Chromium's source tree with WebCL-specific modifications and building against AMD's APP SDK to provide the underlying compute infrastructure.

Adoption requires a Windows development environment with specific dependencies including Visual Studio 2010, the Windows 8 SDK, DirectX SDK, and AMD APP SDK. The build process is complex, involving multiple configuration steps and a substantial Chromium source checkout. This tool suits developers building web applications that require GPU acceleration for tasks like image processing, scientific computing, or data-parallel algorithms. It is most practical for teams with Windows infrastructure and familiarity with Chromium's build system.

The project shows minimal ongoing development activity, with the repository appearing dormant and no recent updates to the build instructions or dependencies. The setup process references outdated software versions and SDKs that are no longer actively maintained, suggesting the codebase has not been updated to work with modern development tools or recent Chromium versions. The complexity of the initial setup combined with the lack of active maintenance means potential adopters should carefully evaluate whether this implementation meets their needs or whether alternative approaches to web-based GPU computing would be more practical.