[CPU-OpenMP-questiоn-step1] We аim tо develоp а GPU performаnce projection based on the given CPU code, which is written in OpenMP. The CPU has 8 cores, each running at 1 GHz, and GPU has 128 SMs, each running at 1GHz. To predict the performance, various modeling methods are required. Please follow the instructions to simplify the problem: To estimate the execution time on the CPU, assume that each element requires 10 instructions on average for each loop iteration, and the CPU has an IPC 4 per each core. Please ignore the array initialization code, as it needs to be executed on the CPU anyway. Assume infinite computational speedup from running this code on the GPU, but take into account the data transfer overhead and kernel launch overhead. The CPU and GPU are connected via an external bus with a bandwidth of 16 GB/s, and each floating-point number is 4 bytes in size. Additionally, there is a 50 ns kernel launch overhead per kernel invocation. Given these conditions, determine the minimum array size N that will allow the GPU to outperform the CPU. Assume that the data sent to the GPU's global memory can remain there throughout the computation, and only the final results need to be transferred back to the CPU after computation. Choose the closest number . To help solve the problem, we break down the question into 5 parts. Please see the example OpenMP program below. #include #include #include #include #define N ? // Array size to be find out int main() { int i; float sum = 0.0; double product = 0.0; float max_element = 0.0; float arr[N]; // Seed the random number generator srand(time(NULL)); // Initialize the array with random values between 0 and 1 for (i = 0; i
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