The impact of multi-threading on function performance: Thread creation/destruction overhead: consuming system resources and affecting performance. Thread synchronization: avoids data corruption, but increases overhead. Context switching overhead: The system incurs when switching between threads. Practical case: Fibonacci sequence calculation, multi-threaded parallel computing can improve performance.
The impact of the multi-threading mechanism in C on function performance
Multi-threading refers to running multiple program fragments at the same time Ability. In C, multithreading is implemented through the std::thread
class.
When a function is run in a multi-threaded environment, its performance may be affected by the following factors:
Practical case:
Consider the following function that calculates the Fibonacci sequence:int fibonacci(int n) { if (n <= 1) { return n; } else { return fibonacci(n - 1) + fibonacci(n - 2); } }
n increases. This is because the function calls itself recursively, causing a lot of context switching overhead.
#include <thread> int fibonacci_thread(int n) { if (n <= 1) { return n; } else { std::thread t1(fibonacci_thread, n - 1); std::thread t2(fibonacci_thread, n - 2); t1.join(); t2.join(); return t1.get() + t2.get(); } }
fibonacci(n - 1) and
fibonacci(n - 2 ). This reduces the number of recursive calls, thereby reducing context switching overhead.
n values are large.
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