Difference between revisions of "MKL"
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{{software info | {{software info | ||
|description=efficient mathematics library | |description=efficient mathematics library | ||
| − | |license= | + | |license=site license |
| − | |fields= | + | |fields=System tool |
}} | }} | ||
| − | [http://software.intel.com/en-us/articles/intel-mkl/ {{PAGENAME}}] ( | + | [http://software.intel.com/en-us/articles/intel-mkl/ {{PAGENAME}}] (math kernel library) is an {{#show: {{PAGENAME}} |?description}}, which many softwares can be compiled against for increased efficiency. |
== Availability == | == Availability == | ||
{{list resources for software}} | {{list resources for software}} | ||
| − | MKL is actually included as a component in the latest release of the [[Intel compiler suite]], and may therefore be available on further resources than indicated here. Please contact [[Support|centre support]] for details. | + | MKL is actually included as a component in the latest release of the [[Intel compiler suite]], and may therefore be available on further resources than indicated here. Please contact [[Support|centre support]] for details. Much of the functionality of MKL is also offered by [[ACML]] from AMD. In particular on architectures utilising AMD processors, it is often worthwhile to assess whether MKL or ACML offer better performance for the given software. |
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{{show license}} | {{show license}} | ||
| − | [[NSC]] | + | [[NSC]] and [[PDC]] have a site license for this software. |
== Experts == | == Experts == | ||
Latest revision as of 15:54, 1 October 2013
MKL (math kernel library) is an efficient mathematics library, which many softwares can be compiled against for increased efficiency.
Contents
Availability
| Resource | Centre | Description |
|---|---|---|
| Abisko | HPC2N | capability resource of 153 TFLOPS with full bisectional infiniband interconnect |
| Akka | HPC2N | capability cluster resource of 54 TFLOPS with infiniband interconnect |
| Alarik | LUNARC | throughput cluster resource of 40 TFLOPS |
| Aurora | LUNARC | throughput/general purpose cluster resource |
| Kappa | NSC | throughput cluster resource of 26 TFLOPS |
| Lindgren | PDC | Cray XE6 capability cluster with 305 TFLOPS peak performance |
| Matter | NSC | cluster resource of 37 TFLOPS dedicated to materials science |
| Triolith | NSC | Capability cluster with 338 TFLOPS peak and 1:2 Infiniband fat-tree |
| Zorn | PDC | GPU cluster |
MKL is actually included as a component in the latest release of the Intel compiler suite, and may therefore be available on further resources than indicated here. Please contact centre support for details. Much of the functionality of MKL is also offered by ACML from AMD. In particular on architectures utilising AMD processors, it is often worthwhile to assess whether MKL or ACML offer better performance for the given software.
License
License: Site license.
NSC and PDC have a site license for this software.
Experts
No experts have currently registered expertise on this specific subject. List of registered field experts:
| Field | AE FTE | General activities | ||
|---|---|---|---|---|
| Anders Hast (UPPMAX) | UPPMAX | Visualisation, Digital Humanities | 30 | Software and usability for projects in digital humanities |
| Anders Sjölander (UPPMAX) | UPPMAX | Bioinformatics | 100 | Bioinformatics support and training, job efficiency monitoring, project management |
| Anders Sjöström (LUNARC) | LUNARC | GPU computing MATLAB General programming Technical acoustics | 50 | Helps users with MATLAB, General programming, Image processing, Usage of clusters |
| Birgitte Brydsö (HPC2N) | HPC2N | Parallel programming HPC | Training, general support | |
| Björn Claremar (UPPMAX) | UPPMAX | Meteorology, Geoscience | 100 | Support for geosciences, Matlab |
| Björn Viklund (UPPMAX) | UPPMAX | Bioinformatics Containers | 100 | Bioinformatics, containers, software installs at UPPMAX |
| Chandan Basu (NSC) | NSC | Computational science | 100 | EU projects IS-ENES and PRACE. Working on climate and weather codes |
| Diana Iusan (UPPMAX) | UPPMAX | Computational materials science Performance tuning | 50 | Compilation, performance optimization, and best practice usage of electronic structure codes. |
| Frank Bramkamp (NSC) | NSC | Computational fluid dynamics | 100 | Installation and support of computational fluid dynamics software. |
| Hamish Struthers (NSC) | NSC | Climate research | 80 | Users support focused on weather and climate codes. |
| Henric Zazzi (PDC) | PDC | Bioinformatics | 100 | Bioinformatics Application support |
| Jens Larsson (NSC) | NSC | Swestore | ||
| Jerry Eriksson (HPC2N) | HPC2N | Parallel programming HPC | HPC, Parallel programming | |
| Joachim Hein (LUNARC) | LUNARC | Parallel programming Performance optimisation | 85 | HPC training Parallel programming support Performance optimisation |
| Johan Hellsvik | PDC | Materialvetenskap | 30 | materials theory, modeling of organic magnetic materials, |
| Johan Raber (NSC) | NSC | Computational chemistry | 50 | |
| Jonas Lindemann (LUNARC) | LUNARC | Grid computing Desktop environments | 20 | Coordinating SNIC Emerging Technologies Developer of ARC Job Submission Tool Grid user documentation Leading the development of ARC Storage UI Lunarc Box Lunarc HPC Desktop |
| Krishnaveni Chitrapu (NSC) | NSC | Software development | ||
| Lars Eklund (UPPMAX) | UPPMAX | Chemistry Data management FAIR Sensitive data | 100 | Chemistry codes, databases at UPPMAX, sensitive data, PUBA agreements |
| Lars Viklund (HPC2N) | HPC2N | General programming HPC | HPC, General programming, installation of software, support, containers | |
| Lilit Axner (PDC) | PDC | Computational fluid dynamics | 50 | |
| Marcus Lundberg (UPPMAX) | UPPMAX | Computational science Parallel programming Performance tuning Sensitive data | 100 | I help users with productivity, program performance, and parallelisation. I also work with allocations and with sensitive data questions |
| Martin Dahlö (UPPMAX) | UPPMAX | Bioinformatics | 10 | Bioinformatic support |
| Matias Piqueras (UPPMAX) | UPPMAX | Humanities, Social sciences | 70 | Support for humanities and social sciences, machine learning |
| Mikael Djurfeldt (PDC) | PDC | Neuroinformatics | 100 | |
| Mirko Myllykoski (HPC2N) | HPC2N | Parallel programming GPU computing | Parallel programming, HPC, GPU programming, advanced support | |
| Pavlin Mitev (UPPMAX) | UPPMAX | Computational materials science | 100 | |
| Pedro Ojeda-May (HPC2N) | HPC2N | Molecular dynamics Machine learning Quantum Chemistry | Training, HPC, Quantum Chemistry, Molecular dynamics, R, advanced support | |
| Peter Kjellström (NSC) | NSC | Computational science | 100 | All types of HPC Support. |
| Peter Münger (NSC) | NSC | Computational science | 60 | Installation and support of MATLAB, Comsol, and Julia. |
| Rickard Armiento (NSC) | NSC | Computational materials science | 40 | Maintainer of the scientific software environment at NSC. |
| Szilard Pall | PDC | Molecular dynamics | 55 | Algorithms & methods for accelerating molecular dynamics, Parallelization and acceleration of molecular dynamics on modern high performance computing architectures, High performance computing, manycore and heterogeneous architectures, GPU computing |
| Thomas Svedberg (C3SE) | C3SE | Solid mechanics | ||
| Torben Rasmussen (NSC) | NSC | Computational chemistry | 100 | Installation and support of computational chemistry software. |
| Wei Zhang (NSC) | NSC | Computational science Parallel programming Performance optimisation | code optimization, parallelization. | |
| Weine Olovsson (NSC) | NSC | Computational materials science | 90 | Application support, installation and help |
| Åke Sandgren (HPC2N) | HPC2N | Computational science | 50 | SGUSI |
