What is a CPU-Bound Task?

A CPU-bound task is an operation where the program spends most of its time using the CPU for heavy computation, rather than waiting for input/output (I/O).

• CPU-bound tasks max out your processor’s power.

• Performance is limited by how fast the CPU can crunch numbers or run algorithms.

Examples of CPU-Bound Tasks in Python

1. Mathematical Computations

   # Calculating factorial recursively (CPU-intensive for large numbers)
   def factorial(n):
       return 1 if n == 0 else n * factorial(n-1)
   
   print(factorial(1000))
   

2. Image Processing

   from PIL import Image, ImageFilter
   img = Image.open("large_image.jpg")
   blurred = img.filter(ImageFilter.GaussianBlur(20))  # heavy pixel computation
   

3. Data Processing / Machine Learning

   # Sorting a huge list (O(n log n))
   numbers = list(range(10**7, 0, -1))
   numbers.sort()  # CPU is busy crunching
   

CPU-Bound vs I/O-Bound

Why It Matters

• For CPU-bound tasks, multithreading doesn’t help much in Python (due to the Global Interpreter Lock — GIL).

• Instead, you should use multiprocessing so that multiple CPU cores can work in parallel.

✅ Rule of Thumb:

• Use multiprocessing for CPU-bound tasks.

• Use multithreading/async for I/O-bound tasks.