compute-runtime | Intel® Graphics Compute Runtime for oneAPI Level Zero | GPU library

 by   intel C++ Version: 19.32.13826.1 License: MIT

kandi X-RAY | compute-runtime Summary

kandi X-RAY | compute-runtime Summary

compute-runtime is a C++ library typically used in Hardware, GPU applications. compute-runtime has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

The Intel(R) Graphics Compute Runtime for oneAPI Level Zero and OpenCL(TM) Driver is an open source project providing compute API support (Level Zero, OpenCL) for Intel graphics hardware architectures (HD Graphics, Xe).
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              compute-runtime has a medium active ecosystem.
              It has 939 star(s) with 220 fork(s). There are 76 watchers for this library.
              There were 2 major release(s) in the last 12 months.
              There are 47 open issues and 426 have been closed. On average issues are closed in 118 days. There are 6 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of compute-runtime is 19.32.13826.1

            kandi-Quality Quality

              compute-runtime has 0 bugs and 0 code smells.

            kandi-Security Security

              compute-runtime has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              compute-runtime code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              compute-runtime is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              compute-runtime releases are available to install and integrate.
              Installation instructions, examples and code snippets are available.
              It has 21 lines of code, 1 functions and 1 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

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            compute-runtime Key Features

            No Key Features are available at this moment for compute-runtime.

            compute-runtime Examples and Code Snippets

            No Code Snippets are available at this moment for compute-runtime.

            Community Discussions

            QUESTION

            Using OpenCV with OpenCL on Intel UHD Graphics 630 along with nvidia GPU
            Asked 2020-Oct-28 at 22:38

            I currently have a program running all the time using my Nvidia GPU. I would like to run another one aside, which would use OpenCV with OpenCL. I use Ubuntu 18.04 and my processor is an Intel i7-9750H (with UHD Graphics 630).

            I run this C++ code to detect the available devices:

            ...

            ANSWER

            Answered 2020-Oct-28 at 22:38

            This is a somewhat messy situation. There is a difference between using multiple OpenCL devices from a single platform and different platforms.

            Question 2: Each OpenCL implementation/SDK/Runtime you install will show up as a platform. The context class of OpenCV is bound to a single platform and can only work with the corresponding devices. The constructor only allows to specify a device type, so it probably queries OpenCL and uses the first platform with that device type (or just the first). That's why OpenCV only shows the Nvidia device.

            Question 1: Creating another context reflecting the Intel platform would be possible by using the OpenCL API directly and then calling OpenCV's fromHandle() or fromDevice() functions to create the OpenCV Context object (the clinfo source is an example for the required code). But, using different platforms means linking to different OpenCL libraries (indirectly at runtime through the compile-time linked libOpenCL). I.e. memory objects, etc. cannot be shared between the different contexts, so practical usability is rather limited unless you have independent problems that you'd like to compute in parallel on both devices.

            Bonus: Your clinfo output shows 3 platforms (Nvidia OpenCL 1.2, Intel GPU OpenCL 3.0, Intel CPU OpenCL 2.1), and you see the warning:

            Source https://stackoverflow.com/questions/64446808

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install compute-runtime

            To allow NEO access to GPU device make sure user has permissions to files /dev/dri/renderD*.
            .deb packages for Ubuntu are provided along with installation instructions and Release Notes on the release page.

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            CLONE
          • HTTPS

            https://github.com/intel/compute-runtime.git

          • CLI

            gh repo clone intel/compute-runtime

          • sshUrl

            git@github.com:intel/compute-runtime.git

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