monolish VS oneMKL

Compare monolish vs oneMKL and see what are their differences.

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monolish oneMKL
1 2
189 565
0.0% 3.7%
7.8 8.5
6 months ago 12 days ago
C++ C++
Apache License 2.0 Apache License 2.0
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.

monolish

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

oneMKL

Posts with mentions or reviews of oneMKL. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-12-21.

What are some alternatives?

When comparing monolish and oneMKL you can also consider the following projects:

fms_blas - Lightweight BLAS (and some LAPACK) wrapper.

oneDNN - oneAPI Deep Neural Network Library (oneDNN)

BitLib - Provides a bit-vector, an optimized replacement of the infamous std::vector<:b:ool>. In addition to the bit-vector, the library also provides implementations of STL algorithms tailored for bit-vectors.

kokkos-kernels - Kokkos C++ Performance Portability Programming Ecosystem: Math Kernels - Provides BLAS, Sparse BLAS and Graph Kernels

stdgpu - stdgpu: Efficient STL-like Data Structures on the GPU

peakperf - Achieve peak performance on x86 CPUs and NVIDIA GPUs

alpaka - Abstraction Library for Parallel Kernel Acceleration :llama:

nekRS - our next generation fast and scalable CFD code

Scalix - Scalix is a data parallel compute library that automatically scales to the available compute resources.

ArrayFire - ArrayFire: a general purpose GPU library.

matrix-sized - Generic matrix with statically known size and bindings to C++ linear algebra libraries (Eigen, Spectra).

LSQR-CUDA - This is a LSQR-CUDA implementation written by Lawrence Ayers under the supervision of Stefan Guthe of the GRIS institute at the Technische Universität Darmstadt. The LSQR library was authored Chris Paige and Michael Saunders.