luDecomposition | LU decomposition of a large matrix using OpenMP and MPI | GPU library

by adilansari C Version: Current License: No License

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kandi X-RAY | luDecomposition Summary

luDecomposition is a C library typically used in Hardware, GPU applications. luDecomposition has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Parallel Implementation of LU decomposition.

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luDecomposition has a low active ecosystem.

It has 12 star(s) with 4 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

luDecomposition has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of luDecomposition is current.

Quality

luDecomposition has no bugs reported.

Security

luDecomposition has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

luDecomposition does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

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luDecomposition releases are not available. You will need to build from source code and install.

Installation instructions are not available. Examples and code snippets are available.

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luDecomposition Examples and Code Snippets

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Community Discussions

Trending Discussions on luDecomposition

How do I find the pseudo-inverse from Apache Commons Math - Java library

Divide by Zero Warning in LU Decomposition- Doolittle Algorithm working

How to parallelize for loop in java?

How to convert primitive double array to Double array

QUESTION

How do I find the pseudo-inverse from Apache Commons Math - Java library

Asked 2020-May-18 at 20:54

According to this code. It can finding the pseudo-inverse by using Apache Commons Math library.

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ANSWER

Answered 2020-May-18 at 20:54

So I'm not sure where you got the idea that the solver from the LUDecomposition yields the pseudoinverse. In fact if you look at the code, you can see that this only works if a solution exists "in exact linear sense".

Instead, you should first create a SingularValueDecomposition with

Source https://stackoverflow.com/questions/61774858

QUESTION

Divide by Zero Warning in LU Decomposition- Doolittle Algorithm working

Asked 2020-May-09 at 02:33

I have implemented the standard equations/algorithm of LU Decomposition of a Matrix by following this link: (1) and (2) This returns the LU decomposition of a square matrix like below perfectly. My problem is, however- it also gives a Divide by Zero warning.

Code here:

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ANSWER

Answered 2020-May-09 at 02:33

It seems that you may have made some indentation errors regarding the first inner level for loops: U must be evaluated before L ; you also didn't correctly compute the summation term acc and didn't properly set the diagonal terms of L to 1. Following some other syntax modifications, you may rewrite your function as follows:

Source https://stackoverflow.com/questions/61522143

QUESTION

How to parallelize for loop in java?

Asked 2019-Jan-30 at 19:24

I have sequential code for LU matrix decomposition in java. My question is, how to easily make decompose function parallel? Is there any similar techniques like OpenMP or Parallel.for in c#?

I think, that It's possible to paralellize for loop but I don't know how to easily achieve this in Java.

Here is my code:

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ANSWER

Answered 2019-Jan-30 at 19:20

If you replace your for loops with Int Streams, it is very easy to make it run in parallel:

Example:

Source https://stackoverflow.com/questions/54447834

QUESTION

How to convert primitive double array to Double array

Asked 2018-Jul-11 at 11:09

With the Apache common math library I get back a primitive double array.

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ANSWER

Answered 2018-Jul-10 at 19:55

If you are using Java 8+ you can use :

Source https://stackoverflow.com/questions/51272989

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

Vulnerabilities

No vulnerabilities reported

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You can download it from GitHub.

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