Microbenchmarks | Micro benchmark comparison of Julia | Performance Testing library

 by   JuliaLang C Version: Current License: Non-SPDX

kandi X-RAY | Microbenchmarks Summary

kandi X-RAY | Microbenchmarks Summary

Microbenchmarks is a C library typically used in Testing, Performance Testing applications. Microbenchmarks has no bugs, it has no vulnerabilities and it has low support. However Microbenchmarks has a Non-SPDX License. You can download it from GitHub.

This is a collection of micro-benchmarks used to compare Julia's performance against that of other languages. It was formerly part of the Julia source tree. The results of these benchmarks are used to generate the performance graph on the Julia homepage and the table on the benchmarks page.
Support
    Quality
      Security
        License
          Reuse

            kandi-support Support

              Microbenchmarks has a low active ecosystem.
              It has 65 star(s) with 36 fork(s). There are 15 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 12 open issues and 11 have been closed. On average issues are closed in 9 days. There are 6 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of Microbenchmarks is current.

            kandi-Quality Quality

              Microbenchmarks has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              Microbenchmarks has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

            kandi-Reuse Reuse

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

            Top functions reviewed by kandi - BETA

            kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
            Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of Microbenchmarks
            Get all kandi verified functions for this library.

            Microbenchmarks Key Features

            No Key Features are available at this moment for Microbenchmarks.

            Microbenchmarks Examples and Code Snippets

            No Code Snippets are available at this moment for Microbenchmarks.

            Community Discussions

            QUESTION

            Extending Rcpp::as for custom classes depending on Rcpp.h
            Asked 2021-Apr-14 at 14:38

            I'm working on an Rcpp sparse matrix class that uses both Rcpp::IntegerVector (row/column pointers) and a templated std::vector. The rationale is that overhead in deep-copying the integer pointer vectors (@i, @p) in extremely large sparse-matrices can be avoided by simply leaving them as pointers to R objects, and consistently, microbenchmarks show that this approach takes almost exactly half the time as conversion to Eigen::SparseMatrix and arma::SpMat while using less memory.

            Bare-bones Rcpp sparse matrix class

            ...

            ANSWER

            Answered 2021-Apr-14 at 14:38

            It's actually quite simple to create an Rcpp SparseMatrix class! I was overthinking it.

            Source https://stackoverflow.com/questions/67091344

            QUESTION

            How am I able to run Tensor Core instructions without actually having Tensor Cores?
            Asked 2021-Mar-14 at 14:15

            I'm using CUDA's WMMA API to multiply fragments on the GTX 1660 Ti. This GPU doesn't have Tensor Cores, but when I look at the SASS generated for my code I see HMMA.1688.F32 instructions, which are Tensor Core instructions! How can that happen?

            Relevant information:

            ...

            ANSWER

            Answered 2021-Mar-14 at 14:15

            For code binary compatibility, the "non-tensor-core" members of the Turing family have hardware in the SM that will process tensor core instructions, albeit at a relatively low throughput, compared to a tensor core unit.

            Source https://stackoverflow.com/questions/66621753

            QUESTION

            Flutter unable to switch from master to dev channel
            Asked 2020-Nov-17 at 03:30

            I'm on the master channel, and want to switch to the dev. When I run

            ...

            ANSWER

            Answered 2020-Nov-17 at 03:30

            QUESTION

            Fast random string generator in Clojure
            Asked 2020-Sep-24 at 18:36

            I was wondering if there is a way to generate a fixed length random string in Clojure.

            A quick search resulted in:

            https://gist.github.com/rboyd/5053955

            ...

            ANSWER

            Answered 2020-Sep-23 at 19:21

            Let me answer my own question:

            Source https://stackoverflow.com/questions/64034761

            QUESTION

            Fastest way to keep only first occurence of true; set rest to false
            Asked 2020-Apr-18 at 11:41

            My question is basically what the title says. Given some vector x consisting of both TRUE and FALSE, keep only the first occurrence of TRUE and set the rest to FALSE.

            A small example:

            ...

            ANSWER

            Answered 2020-Apr-18 at 11:41

            This tweak of your vec_repl() gives a small speedup for larger examples:

            Source https://stackoverflow.com/questions/61276154

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

            Vulnerabilities

            No vulnerabilities reported

            Install Microbenchmarks

            You can download it from GitHub.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
            Find more information at:

            Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items

            Find more libraries
            CLONE
          • HTTPS

            https://github.com/JuliaLang/Microbenchmarks.git

          • CLI

            gh repo clone JuliaLang/Microbenchmarks

          • sshUrl

            git@github.com:JuliaLang/Microbenchmarks.git

          • Stay Updated

            Subscribe to our newsletter for trending solutions and developer bootcamps

            Agree to Sign up and Terms & Conditions

            Share this Page

            share link