https://github.com/nschloe/python-vs-cpp

https://github.com/nschloe/python-vs-cpp

Last synced: 22 days ago
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• Host: GitHub
• URL: https://github.com/nschloe/python-vs-cpp
• Owner: nschloe
• License: mit
• Created: 2019-12-04T15:57:18.000Z (almost 5 years ago)
• Default Branch: master
• Last Pushed: 2020-08-11T18:05:37.000Z (over 4 years ago)
• Last Synced: 2024-10-10T09:26:34.374Z (about 1 month ago)
• Language: C++
• Size: 115 KB
• Stars: 13
• Watchers: 5
• Forks: 2
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt

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README

        
# Python vs. C++

It is an often reiterated statement that

> Interpreted code is always slower then compiled code. We need speed! That's why we're

> using C/C++ in our project.

This assumption is based on the correct observation that large loops like for a dot

product of two vectors `u`, `v`, are faster in C,

```c++

double out = 0.0

for (int k=0; k < n; k++) {

   out += u[k] * v[k];

}

```

than in Python:

```python

out = 0.0

for k in range(n):

    out[k] += u[k] * v[k]

```

If you care about speed, you wouldn't do either of the above loops, though. In Python,

most everyone does

```python

import numpy

out = numpy.dot(u, v)

```

anyway. For C/C++,

[Eigen](http://eigen.tuxfamily.org/index.php?title=Main_Page),

[CBLAS](http://www.netlib.org/blas/#_cblas), and [Boost](https://www.boost.org/) come to

mind.

This repository contains a comparison of some common costly numerical operations between

C++ and Python.

As always, comments and suggestions are welcome!

### Dot product of two vectors

 | 

:--------:|:--------:|

### Matrix-matrix product

 | 

:--------:|:--------:|

### Sum entries in a vector

 | 

:--------:|:--------:|

### Add two vectors

 | 

:--------:|:--------:|

### License

The code in this respository is published under the [MIT license](https://en.wikipedia.org/wiki/MIT_License).