OpenBLAS VS blaze

Compare OpenBLAS vs blaze and see what are their differences.

OpenBLAS

OpenBLAS is an optimized BLAS library based on GotoBLAS2 1.13 BSD version. (by OpenMathLib)
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OpenBLAS blaze
22 -
5,952 -
2.4% -
9.8 -
1 day ago almost 8 years ago
C
BSD 3-clause "New" or "Revised" License -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

OpenBLAS

Posts with mentions or reviews of OpenBLAS. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-03-31.
  • LLaMA Now Goes Faster on CPUs
    16 projects | news.ycombinator.com | 31 Mar 2024
    The Fortran implementation is just a reference implementation. The goal of reference BLAS [0] is to provide relatively simple and easy to understand implementations which demonstrate the interface and are intended to give correct results to test against. Perhaps an exceptional Fortran compiler which doesn't yet exist could generate code which rivals hand (or automatically) tuned optimized BLAS libraries like OpenBLAS [1], MKL [2], ATLAS [3], and those based on BLIS [4], but in practice this is not observed.

    Justine observed that the threading model for LLaMA makes it impractical to integrate one of these optimized BLAS libraries, so she wrote her own hand-tuned implementations following the same principles they use.

    [0] https://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprogra...

    [1] https://github.com/OpenMathLib/OpenBLAS

    [2] https://www.intel.com/content/www/us/en/developer/tools/onea...

    [3] https://en.wikipedia.org/wiki/Automatically_Tuned_Linear_Alg...

    [4]https://en.wikipedia.org/wiki/BLIS_(software)

  • Assume I'm an idiot - oogabooga LLaMa.cpp??!
    4 projects | /r/LocalLLaMA | 23 Jun 2023
  • Learn x86-64 assembly by writing a GUI from scratch
    11 projects | news.ycombinator.com | 1 Jun 2023
    Yeah. I'm going to be helping to work on expanding CI for OpenBlas and have been diving into this stuff lately. See the discussion in this closed OpenBlas issue gh-1968 [0] for instance. OpenBlas's Skylake kernels do rely on intrinsics [1] for compilers that support them, but there's a wide range of architectures to support, and when hand-tuned assembly kernels work better, that's what are used. For example, [2].

    [0] https://github.com/xianyi/OpenBLAS/issues/1968

    [1] https://github.com/xianyi/OpenBLAS/blob/develop/kernel/x86_6...

    [2] https://github.com/xianyi/OpenBLAS/blob/23693f09a26ffd8b60eb...

  • AI’s compute fragmentation: what matrix multiplication teaches us
    4 projects | news.ycombinator.com | 23 Mar 2023
    We'll have to wait until part 2 to see what they are actually proposing, but they are trying to solve a real problem. To get a sense of things check out the handwritten assembly kernels in OpenBlas [0]. Note the level of granularity. There are micro-optimized implementations for specific chipsets.

    If progress in ML will be aided by a proliferation of hyper-specialized hardware, then there really is a scalability issue around developing optimized matmul routines for each specialized chip. To be able to develop a custom ASIC for a particular application and then easily generate the necessary matrix libraries without having to write hand-crafted assembly for each specific case seems like it could be very powerful.

    [0] https://github.com/xianyi/OpenBLAS/tree/develop/kernel

  • Trying downloading BCML
    1 project | /r/learnpython | 18 Jan 2023
    libraries mkl_rt not found in ['C:\python\lib', 'C:\', 'C:\python\libs'] ``` Install this and try again. Might need to reboot, never know with Windows https://www.openblas.net/
  • The Bitter Truth: Python 3.11 vs Cython vs C++ Performance for Simulations
    2 projects | /r/programming | 27 Dec 2022
    There isn't any fortran code in the repo there itself but numpy itself can be linked with several numeric libraries. If you look through the wheels for numpy available on pypi, all the latest ones are packaged with OpenBLAS which uses Fortran quite a bit: https://github.com/xianyi/OpenBLAS
  • Optimizing compilers reload vector constants needlessly
    7 projects | news.ycombinator.com | 6 Dec 2022
  • Just a quick question, can a programming language be as fast as C++ and efficient with as simple syntax like Python?
    4 projects | /r/learnpython | 11 Nov 2022
    Sure - write functions in another language, export C bindings, and then call those functions from Python. An example is NumPy - a lot of its linear algebra functions are implemented in C and Fortran.
  • OpenBLAS - optimized BLAS library based on GotoBLAS2 1.13 BSD version
    1 project | /r/github_trends | 12 Aug 2022
  • How to include external libraries?
    1 project | /r/C_Programming | 12 Jun 2022
    Read the official docs yet?

blaze

Posts with mentions or reviews of blaze. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning blaze yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing OpenBLAS and blaze you can also consider the following projects:

Eigen

GLM - OpenGL Mathematics (GLM)

cblas - Netlib's C BLAS wrapper: http://www.netlib.org/blas/#_cblas

LibTomMath - LibTomMath is a free open source portable number theoretic multiple-precision integer library written entirely in C.

Boost.Multiprecision - Boost.Multiprecision

Vc - SIMD Vector Classes for C++

ceres-solver - A large scale non-linear optimization library

NT2

CGal - The public CGAL repository, see the README below