Speed comparison with Project Euler: C vs Python vs Erlang vs Haskell

Speed comparison with Project Euler: C vs Python vs Erlang vs Haskell

Are you ready to dive into the world of programming languages and see how they perform when solving a challenging problem? In this blog post, we will compare the speed of different languages - C, Python, Erlang, and Haskell - when solving Problem #12 from Project Euler.

The Problem:

The original problem from Project Euler asks us to find the first triangle number with more than 500 divisors. However, for the sake of this comparison, we will search for the first triangle number with more than 1000 divisors.

The Results:

Let's take a look at the execution times for each language:

C:

842161320

real    0m11.074s
user    0m11.070s
sys 0m0.000s

Python:

842161320

real    1m16.632s
user    1m16.370s
sys 0m0.250s

Python with PyPy:

842161320

real    0m13.082s
user    0m13.050s
sys 0m0.020s

Erlang:

842161320

real    0m48.259s
user    0m48.070s
sys 0m0.020s

Haskell:

842161320

real    2m37.326s
user    2m37.240s
sys 0m0.080s

The Analysis:

From these results, we can see that C is the fastest language, followed by Erlang, Python, and finally Haskell. There are a few factors that might contribute to these differences in speed.

Question 1: One possible reason for the slower execution times in Python, Erlang, and Haskell could be the use of arbitrary length integers. These languages are known for their ability to handle large numbers, but this comes at a cost in terms of performance. However, for values less than the maximum integer value (MAXINT), the speed should not be significantly affected.

Question 2: Haskell stands out as the slowest language in this comparison. It is possible that there might be a compiler flag that can optimize the code and improve its performance. Alternatively, it could be due to the implementation of the algorithm in Haskell. Further investigation and experimentation might be needed to find a more optimized solution.

Question 3: If you're looking to optimize these implementations without changing the way you determine the factors, there are a few strategies you can try:

• C:

  • Consider using more efficient algorithms or data structures for factor counting.

  • Experiment with compiler optimizations and flags.

• Python:

  • Take advantage of libraries or modules that provide optimized functions for mathematical operations.

  • Optimize the factor counting algorithm to reduce execution time.

• Erlang:

  • Explore possible optimizations in the factor counting algorithm.

  • Consider using built-in Erlang libraries or modules that can improve performance.

• Haskell:

  • Investigate different algorithms or approaches that might offer faster execution times.

  • Look into compiler flags or optimizations specific to Haskell that can improve performance.

Remember, optimization is a process of trial and error, and what works for one language might not work for another. Experimentation and continuous improvement are key.

The Conclusion:

In this speed comparison, we have seen that different programming languages can have significantly different execution times when solving a complex problem. C emerged as the fastest language, while Haskell lagged behind. Python and Erlang fell somewhere in between.

If you're looking for the fastest execution times, C might be your best bet. However, keep in mind that each language has its own strengths and weaknesses, and choosing the right language for a specific task depends on various factors such as ease of development, community support, and available libraries and frameworks.

So, the next time you're faced with a programming challenge, consider your options and pick the language that best suits your needs.

Have you tried solving this problem in a different language?

We'd love to hear about your experience and results! Share your insights and join the conversation in the comments below. Let's geek out together!

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Happy coding! 🚀💻

References:

• Project Euler - Problem #12

• Project Euler