Thread-Safe Kernel Counter

What this thread-safe counter problem tests

This is an easy Python concurrency problem common in systems roles at firms like Nvidia that work with GPUs and parallel compute. It checks whether you understand the fundamentals of race conditions and can apply a synchronization primitive (lock, mutex, or equivalent) correctly to protect shared mutable state.

The core challenge is recognizing that a simple read-modify-write sequence is not atomic: two threads can both read the same value, increment it, and write back, causing one increment to be lost. The solution requires choosing an appropriate locking mechanism and ensuring it guards every access path to the counter. Interviewers often follow up by asking about contention, fairness, or whether there are lock-free alternatives.

• Critical sections and mutual exclusion
• Python threading module and synchronization primitives
• Testing for race conditions and correctness under load