100x Speedup: Garbage Collection and GPUs in Python
2025-03-25
This post details how the author achieved a 100x speedup of a Python program through simple code optimizations. The initial program used NumPy for parallel computation but was slow and memory-intensive due to poor memory management. By implementing a simple garbage collection mechanism to release unused intermediate variables, the author reduced runtime from 40 seconds to 10 seconds, significantly decreasing memory usage. Subsequently, using CuPy to offload computation to the GPU further reduced runtime to 1.5 seconds, demonstrating a dramatic performance improvement.
Development
Python Optimization