mkl4deb | Intel MKL to a Debian / Ubuntu system via one simple script

 by   eddelbuettel Shell Version: Current License: No License

kandi X-RAY | mkl4deb Summary

kandi X-RAY | mkl4deb Summary

mkl4deb is a Shell library. mkl4deb has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

This post describes how to easily install the Intel Math Kernel Library (MKL) on a Debian or Ubuntu system. Very good basic documentation is provided by Intel at their site. The discussion here is more narrow as it focusses just on the Math Kernel Library (MKL).
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              mkl4deb has a low active ecosystem.
              It has 198 star(s) with 39 fork(s). There are 15 watchers for this library.
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              It had no major release in the last 6 months.
              There are 0 open issues and 16 have been closed. On average issues are closed in 177 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of mkl4deb is current.

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              mkl4deb has 0 bugs and 0 code smells.

            kandi-Security Security

              mkl4deb has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              mkl4deb code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              mkl4deb does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
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              Without a license, all rights are reserved, and you cannot use the library in your applications.

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              mkl4deb releases are not available. You will need to build from source code and install.
              Installation instructions, examples and code snippets are available.

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            mkl4deb Key Features

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            mkl4deb Examples and Code Snippets

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            Community Discussions

            Trending Discussions on mkl4deb

            QUESTION

            Matrix inversion and transpose R vs c++
            Asked 2018-Oct-12 at 16:27

            I have calculating power flow across a network. However, I have found that for larger networks the calculation is slow. I tried to implement the algorithm using RcppArmadillo. The Rcpp function is several times faster for small networks/matrices but becomes just as slow for larger ones. The speed of the operation is affecting the usefulness of functions further on. Am I writing the functions badly or is this just the options I have?

            The R code below gives and example of the executions times for a matrix of 10, 100, 1000.

            ...

            ANSWER

            Answered 2018-Oct-11 at 09:04

            I have tried your code on a dual core laptop running Debian Linux and R 3.5.1 linked to OpenBLAS. In addition, I have also used RcppArrayFire to do these calculations using the GPU (nothing fancy, just in-build graphics). Here the benchmark results:

            Source https://stackoverflow.com/questions/52741610

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

            Vulnerabilities

            No vulnerabilities reported

            Install mkl4deb

            Now that we have everything set up, installing the MKL is as simple as:. This picks the 64-bit only variant of the (currently) most recent builds. There is a slight cost: a 500mb download of 39 packages which install to 1.9 gb! Other than that it is easy: one command! Compare that with the days of yore when we fetched shar archives of NETLIB...

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            https://github.com/eddelbuettel/mkl4deb.git

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            gh repo clone eddelbuettel/mkl4deb

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            git@github.com:eddelbuettel/mkl4deb.git

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