xtensor
C++ tensors with broadcasting and lazy computing (by xtensor-stack)
nanobench
Simple, fast, accurate single-header microbenchmarking functionality for C++11/14/17/20 (by martinus)
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| xtensor | nanobench | |
|---|---|---|
| 8 | 13 | |
| 3,205 | 1,301 | |
| 1.7% | - | |
| 7.9 | 5.0 | |
| 8 days ago | 8 months ago | |
| C++ | C++ | |
| BSD 3-clause "New" or "Revised" License | MIT 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.
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.
xtensor
Posts with mentions or reviews of xtensor.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-07.
- Does anyone know any good open source project to optimize?
- Container slicing in c++
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Which is the best way to work with matrices and linear algebra using c++?
I use xtensor: https://github.com/xtensor-stack/xtensor
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Can you give an example of well-designed C++ code, and explain why you think it is so?
Currently, one of my current favorites is xtensor.
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Risk of valarray being deprecated?
xTensor natively supports tensors and multidimensional arrays - not just vectors and matrices. Is fast, but not always as fast as Eigen and Blaze - and compiles very slow. Has a nice syntax.
- Xtensor: multi-dimensional arrays with broadcasting and lazy computing
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Eigen: A C++ template library for linear algebra
I wonder how Eigen compares to xtensor, which was inspired by Numpy and has support for views, slicing, and broadcasting?
https://github.com/xtensor-stack/xtensor
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When researching and developing new algorithms to be used in the real-world production environment, what is your workflow and how do you usually do it? Do I have to prototype in Python, and then rewrite all code in C++/Rust?
You can try eigen (http://eigen.tuxfamily.org/), armadillo (http://arma.sourceforge.net/) which is based on LAPACK which is what numpy is based on and xtensor (https://github.com/QuantStack/xtensor) which I think is the closest thing to numpy you’re gonna find in c++
nanobench
Posts with mentions or reviews of nanobench.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-05-27.
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The issue of unit tests and performance measurements (Benchmark)
An alternative is tracking the number of instructions a test executes: https://github.com/martinus/nanobench
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how do you properly benchmark?
Nano bench is a great library with low overhead. https://github.com/martinus/nanobench
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Much Faster than std::string, fmt::format, std::to_chars, std::time and more?
I've done a relatively simple test of taking random doubles (between 0 and 1), converting them to a C string via std::to_chars and then converting that C string back to a double via std::from_chars vs his xeerx::chars_to and got the following results on my machine via nanobench:
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Can you give an example of well-designed C++ code, and explain why you think it is so?
I like https://nanobench.ankerl.com/
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Best accurate way to measure/compare elapsed time in C++
Of course, the best way to benchmark is nanobench: https://nanobench.ankerl.com/
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The 23 year-old C++ developers with three job offers over $500k
I've created robin-hood-hashing and nanobench, and recently made some contributions to Bitcoin and doxygen
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I don’t know which container to use (and at this point I’m too afraid to ask)
Right. Regex runtime construction is known to be slow, so ideally the state machinery construction is built at compile time (boost.xpressive, ctre). Also, boost.regex is faster than most of the std implementations if compile time isn’t possible. And if that’s no good rewrite without regex. Since it sounds like it’s all encapsulated at least it would be easy to measure the options. These days I use this one to compare https://nanobench.ankerl.com/
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I'm writing a microbenchmarking library called "precision" without any macros. What do you guys think of the API?
You can check the API of nanobench which also doesn't use macros, as far as I have used it.
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C++20 std::format is 2x slower than std::fstream?
I've tried again with your latest changes and decided to use https://github.com/martinus/nanobench for a better benchmark and got the following output:
- Nanobench: Fast, Accurate, Single-Header Microbenchmarking Functionality For C++
What are some alternatives?
When comparing xtensor and nanobench you can also consider the following projects:
Fastor - A lightweight high performance tensor algebra framework for modern C++
benchmark - A microbenchmark support library
EA Standard Template Library - EASTL stands for Electronic Arts Standard Template Library. It is an extensive and robust implementation that has an emphasis on high performance.
fast_io - C++20 Concepts IO library which is 10x faster than stdio and iostream
dynarray - A header-only library, VLA for C++ (≥C++14). Extended version of std::experimental::dynarray
robin-hood-hashing - Fast & memory efficient hashtable based on robin hood hashing for C++11/14/17/20
SwiftyWasmer - A Swift API for the Wasmer WebAssembly Runtime
curl4cpp - Single header cURL wrapper for C++ around libcURL
GLM - OpenGL Mathematics (GLM)
ut - C++20 μ(micro)/Unit Testing Framework
blis - BLAS-like Library Instantiation Software Framework
bench-rest - bench-rest - benchmark REST (HTTP/HTTPS) API's. node.js client module for easy load testing / benchmarking REST API's using a simple structure/DSL can create REST flows with setup and teardown and returns (measured) metrics.