What methods are used to optimize tasks limited by processor resources?

To optimize CPU-bound tasks, the following methods are used:

• Parallelism and multithreading: using threading or multiprocessing modules in Python to distribute load across multiple CPU cores.
• Asynchronous programming: if the task involves I/O, asyncio helps avoid blocking the CPU.
• Algorithm optimization: choosing more efficient algorithms and data structures to reduce computational complexity.
• Compilation of critical code sections: using Cython, Numba, or writing C extensions for acceleration.
• Profiling: using cProfile or line_profiler to identify bottlenecks and optimize them.

Example of using multiprocessing:

from multiprocessing import Pool

def f(x):
    return x*x

if __name__ == '__main__':
    with Pool(4) as p:
        print(p.map(f, [1, 2, 3, 4]))

This allows parallel computation across 4 cores.