Difficulty: Medium
Category: Code Analysis
Practice quant interview questions from top firms including Jane Street, Citadel, Two Sigma, DE Shaw, and other leading quantitative finance companies.
Topics: python, multiprocessing, threading, GIL, concurrency, parallelism
You're developing a Python-based Monte Carlo simulation to price exotic options. The simulation is computationally intensive (CPU-bound). You initially implemented parallelization using Python's threading module, but observed no significant performance improvement compared to the single-threaded version. After switching to Python's multiprocessing module, you see a substantial speedup, closely aligning with the number of CPU cores available. Why did multiprocessing provide a performance boost wh
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