fib accelerate

Sure, I can help you with that. To accelerate the calculation of Fibonacci numbers, you can use memoization or dynamic programming techniques. Memoization involves storing the results of expensive function calls and returning the cached result when the same inputs occur again. Dynamic programming breaks down the problem into smaller subproblems and solves them iteratively.

Here's an example of how you can accelerate Fibonacci calculation using dynamic programming in Python:

def fibonacci(n):
    if n <= 1:
        return n

    fib = [0] * (n + 1)
    fib[1] = 1

    for i in range(2, n + 1):
        fib[i] = fib[i - 1] + fib[i - 2]

    return fib[n]

By utilizing dynamic programming, this implementation avoids redundant calculations and significantly speeds up Fibonacci number calculations.