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Author: Smit-create

content/blog/lpython_mvp.md

@@ -207,6 +207,8 @@ We compare JIT compilation of LPython to Numba on **summation of all the element
 | Python | 3.10.4 |
 
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 <!-- Add your systems like System - Linux, System - Windows, etc and then add the results for your System in the tables that follow -->
 
 **Summation of all the elements of a 1-D array**
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 | Compiler | Execution Time (s) | System | Relative |
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 | LPython | 0.013 | Apple M1 MBP 2020 | 1.00 |
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 | Numba | 0.048 | AMD Ryzen 5 2500U (Ubuntu 22.04) | 1.00 |
 
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 <!-- TODO: Write a summary of the results -->
 
 **Pointwise multiplication of two 1-D arrays**
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 | Compiler | Execution Time (s) | System | Relative |
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 | Numba | 0.041 | Apple M1 MBP 2020 | 1.00 |
@@ -347,6 +355,8 @@ test()
 | LPython | 0.21 | AMD Ryzen 5 2500U (Ubuntu 22.04) | 1.00 |
 
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 <!-- TODO: Write a summary of the results -->
 
 **Insertion sort on lists**
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 | Compiler | Execution Time (s) | System | Relative |
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 | LPython | 0.11 | Apple M1 MBP 2020 | 1.00 |
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 | Numba | 0.36 | AMD Ryzen 5 2500U (Ubuntu 22.04) | 3.60 |
 
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 <!-- TODO: Write a summary of the results -->
 
 **Quadratic-time implementation of the Dijkstra shortest-path algorithm on a fully connected graph**
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 | Compiler | Execution Time (s) | System | Relative |
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 | LPython | 0.23 | Apple M1 MBP 2020 | 1.00 |
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 | Numba | 1.95 | AMD Ryzen 5 2500U (Ubuntu 22.04) | 2.24 |
 
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 <!-- TODO: Write a summary of the results -->
 
 ### Ahead-of-Time (AoT) Compilation
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 **Quadratic-time implementation of the Dijkstra shortest-path algorithm on a fully connected graph**
 
 ```python
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 Note the optimization flags furnished to each compiler.
 
 | Compiler/Interpreter | Optimization flags used |
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 <!-- TODO: Write a summary of the results -->
 
 **Floyd-Warshall algorithm on array representation of graphs**
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 | Python | 440.588 | AMD Ryzen 5 2500U (Ubuntu 22.04) | 633.94 |
 
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 <!-- TODO: Remove above line if the following table looks good.-->
 
 Note the optimization flags furnished to each compiler.
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 | Python | - |
 
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 <!-- TODO: Write a summary of the results -->
 
 ### Interoperability with CPython