starpu
This is a mirror of https://gitlab.inria.fr/starpu/starpu where our development happens, but contributions are welcome here too!
Science Score: 26.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (11.3%) to scientific vocabulary
Keywords
Repository
This is a mirror of https://gitlab.inria.fr/starpu/starpu where our development happens, but contributions are welcome here too!
Basic Info
- Host: GitHub
- Owner: starpu-runtime
- License: lgpl-2.1
- Language: C
- Default Branch: master
- Homepage: https://starpu.gitlabpages.inria.fr/
- Size: 78.5 MB
Statistics
- Stars: 76
- Watchers: 7
- Forks: 16
- Open Issues: 16
- Releases: 0
Topics
Metadata Files
README.md
StarPU: A Unified Runtime System for Heterogeneous Multicore Architectures
Please consult https://starpu.gitlabpages.inria.fr for informations.
What is StarPU?
StarPU is a runtime system that offers support for heterogeneous multicore machines. While many efforts are devoted to design efficient computation kernels for those architectures (e.g. to implement BLAS kernels on GPUs), StarPU not only takes care of offloading such kernels (and implementing data coherency across the machine), but it also makes sure the kernels are executed as efficiently as possible.
What StarPU is not
StarPU is not a new language, and it does not extend existing languages either. StarPU does not help to write computation kernels.
(How) Could StarPU help me?
While StarPU will not make it easier to write computation kernels, it does simplify their actual offloading as StarPU handle most low level aspects transparently.
Obviously, it is crucial to have efficient kernels, but it must be noted that the way those kernels are mapped and scheduled onto the computational resources also affect the overall performance to a great extent.
StarPU is especially helpful when considering multiple heterogeneous processing resources: statically mapping and synchronizing tasks in such a heterogeneous environment is already very difficult, making it in a portable way is virtually impossible. On the other hand, the scheduling capabilities of StarPU makes it possible to easily exploit all processors at the same time while taking advantage of their specificities in a portable fashion.
Requirements
makegcc(version >= 4.1)- if
CUDAsupport is enabledCUDA(version >= 2.2)CUBLAS(version >= 2.2)
- if
OpenCLsupport is enabledAMDSDK >= 2.3 ifAMDdriver is usedCUDA>= 3.2 ifNVIDIAdriver is used
- extra requirements for the
gitversion (we usually use the Debian testing versions)autoconf(version >= 2.60)automakemakeinfolibtool(version >= 2)
Remark: It is strongly recommended that you also install the hwloc library before installing StarPU. This permits StarPU to actually map the processing units according to the machine topology. For more details on hwloc, see http://www.open-mpi.org/projects/hwloc/ .
Getting StarPU
StarPU is available on https://gitlab.inria.fr/starpu/starpu
The GIT repository access can be checked out with the following command.
shell
$ git clone https://gitlab.inria.fr/starpu/starpu.git
Building and Installing
For git version only
Please skip this step if you are building from a tarball.
shell
$ ./autogen.sh
For all versions
shell
$ mkdir build && cd build
$ ../configure
$ make
$ make install
If building fails
Please post the commands you used to build, your whole build log, and the obtained config.log in the bug report.
Windows build
StarPU can be built using MinGW or Cygwin. To avoid the cygwin dependency,
we provide MinGW-built binaries. The build process produces libstarpu.dll,
libstarpu.def, and libstarpu.lib, which should be enough to use it from e.g.
Microsoft Visual Studio.
Update the video drivers to the latest stable release available for your hardware. Old ATI drivers (< 2.3) contain bugs that cause OpenCL support in StarPU to hang or exhibit incorrect behaviour.
For details on the Windows build process, see the INSTALL file.
Running StarPU Applications on Microsoft Visual C
Batch files are provided to run StarPU applications under Microsoft
Visual C. They are installed in path_to_starpu/bin/msvc.
To execute a StarPU application, you first need to set the environment
variable STARPU_PATH.
shell
c:\....> cd c:\cygwin\home\ci\starpu\
c:\....> set STARPU_PATH=c:\cygwin\home\ci\starpu\
c:\....> cd bin\msvc
c:\....> starpu_open.bat starpu_simple.c
The batch script will run Microsoft Visual C with a basic project file to run the given application.
The batch script starpu_clean.bat can be used to delete all
compilation generated files.
The batch script starpu_exec.bat can be used to compile and execute a
StarPU application from the command prompt.
```shell c:....> cd c:\cygwin\home\ci\starpu\ c:....> set STARPUPATH=c:\cygwin\home\ci\starpu\ c:....> cd bin\msvc c:....> starpuexec.bat ........\examples\basicexamples\helloworld.c
MSVC StarPU Execution ... /out:hello_world.exe ... Hello world (params = {1, 2.00000}) Callback function got argument 0000042 c:....> ```
Documentation
Doxygen documentation is available in doc/doxygen. If the doxygen
tools are available on the machine, pdf and html documentation can be
generated by running
shell
$ make -C doc
The documentation for the latest StarPU release is available, as well as the documentation for the StarPU master branch.
Trying
Some examples ready to run are installed into $prefix/lib/starpu/{examples,mpi}
Upgrade
To upgrade your source code from older version (there were quite a few
renamings), use the tools/dev/rename.sh script.
Contribute
Contributions are welcome! Both on the main StarPU repository and on the github StarPU mirror
Please see our contribution page for details.
Contact
For any questions regarding StarPU, please contact the starpu-devel mailing-list at starpu-devel@inria.fr or browse the StarPU website.
CodeMeta (codemeta.json)
{
"@context": "https://doi.org/10.5063/schema/codemeta-2.0",
"@type": "SoftwareSourceCode",
"license": "https://spdx.org/licenses/LGPL-2.1",
"codeRepository": "https://gitlab.inria.fr/starpu/starpu.git",
"contIntegration": "https://ci.inria.fr/starpu/",
"dateCreated": "2009-03-01",
"datePublished": "2009-04-02",
"version": "1.4.2",
"dateModified": "2023-11-23",
"downloadUrl": "https://files.inria.fr/starpu/starpu-1.4.2/starpu-1.4.2.tar.gz",
"issueTracker": "https://github.com/starpu-runtime/starpu/issues",
"name": "StarPU",
"description": "StarPU is a task-based runtime system for heterogeneous platforms coupling a performance modeling scheduler with a distributed shared-memory manager. It provides a framework for task scheduling on heterogeneous, accelerated platforms, together with an API for implementing various classes of scheduling algorithms. This scheduling framework jointly works with a distributed shared-memory manager to optimize task mappings and data transfers, and to overlap communications with computations.",
"codemeta:isSourceCodeOf": {
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},
"applicationCategory": "HPC",
"developmentStatus": "active",
"referencePublication": [
"https://dx.doi.org/10.1002/cpe.1631",
"https://tel.archives-ouvertes.fr/tel-00777154",
"https://hal.inria.fr/tel-01959127",
"https://hal.inria.fr/tel-03105625"
],
"releaseNotes": "https://files.inria.fr/starpu/starpu-1.4.2/log.txt",
"keywords": [
"HPC High-Performance Computing",
"Task Paradigm",
"GPU"
],
"programmingLanguage": [
"C",
"C++",
"Fortran",
"Python"
],
"operatingSystem": [
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"author": [
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"@id": "https://orcid.org/0000-0002-5406-8743",
"givenName": "Olivier",
"familyName": "Aumage",
"email": "olivier.aumage@inria.fr",
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"name": "INRIA"
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"givenName": "Samuel",
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"affiliation": {
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"softwareHelp": "https://starpu.gitlabpages.inria.fr/doc.html",
"installURL": [
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"url": "https://gitlab.inria.fr/guix-hpc/guix-hpc/-/blob/master/inria/storm.scm"
},
{
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"url": "https://github.com/spack/spack-packages/tree/develop/repos/spack_repo/builtin/packages/starpu/package.py"
}
],
"softwareSuggestions": "https://discord.gg/vKVJsuHB8U"
}
GitHub Events
Total
- Issues event: 5
- Watch event: 12
- Issue comment event: 11
- Push event: 162
- Pull request review event: 9
- Pull request review comment event: 10
- Pull request event: 4
- Fork event: 5
- Create event: 1
Last Year
- Issues event: 5
- Watch event: 12
- Issue comment event: 11
- Push event: 162
- Pull request review event: 9
- Pull request review comment event: 10
- Pull request event: 4
- Fork event: 5
- Create event: 1
Issues and Pull Requests
Last synced: 11 months ago
All Time
- Total issues: 4
- Total pull requests: 1
- Average time to close issues: 4 months
- Average time to close pull requests: 7 months
- Total issue authors: 3
- Total pull request authors: 1
- Average comments per issue: 0.75
- Average comments per pull request: 1.0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 4
- Pull requests: 1
- Average time to close issues: 4 months
- Average time to close pull requests: 7 months
- Issue authors: 3
- Pull request authors: 1
- Average comments per issue: 0.75
- Average comments per pull request: 1.0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- Muxas (8)
- devreal (5)
- WwwwwYyyy (2)
- athas (1)
- daskol (1)
- grisuthedragon (1)
- SulleyZhou (1)
- yulikdaniel (1)
- brucedevil (1)
- JieRen98 (1)
- costeastefan (1)
- lavar3l (1)
- jacobwilliams (1)
Pull Request Authors
- Muxas (1)
- JieRen98 (1)
- Blixodus (1)
Top Labels
Issue Labels
Pull Request Labels
Dependencies
- org.apache.commons:commons-math3 3.6.1 provided
- org.apache.hadoop:hadoop-client 2.8.0 provided
- org.apache.hadoop:hadoop-common 2.8.0 provided
- org.apache.hadoop:hadoop-hdfs 2.8.0 provided
- junit:junit 4.11 test
- actions/checkout v3 composite
- actions/upload-artifact v2 composite