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GPGPU – Assignment #1: The Big Dot Solved
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The dot product of two vectors π‘Ž = (π‘Ž$, π‘Žβ€™, …, π‘Ž()’ ) and 𝑏 = (𝑏$, 𝑏’, …, 𝑏()’ ), written π‘Ž βˆ™ 𝑏, is simply the sum of the component-by-component products:
π‘Ž βˆ™ 𝑏 = βˆ‘(-/)$’ π‘Ž- Γ— 𝑏-
Dot products are used extensively in computing and have a wide range of applications. For instance, in 3D graphics (n = 3), we often make use of the fact that π‘Ž βˆ™ 𝑏 = |π‘Ž||𝑏|π‘π‘œπ‘ πœƒ, where | | denotes vector length and πœƒ is the angle between the two vectors. In this assignment, you are expected to:
1. Write CUDA code to compute in parallel the dot product of two (possibly large N = 100,000, or N = 1024*1024) random single precision floating point vectors;
2. Write two functions to compute the results on the CPU and GPU, and compare the two results to check for correctness (1.0e-6);
β€’ float *CPU_big_dot(float *A, float *B, int N);
β€’ float *GPU_big_dot(float *A, float *B, int N);
3. Print performance statistics with timer function;
β€’ CPU: Tcpu = Total computation time for CPU_big_dot();
β€’ GPU: Tgpu = Total computation time for GPU_big_dot();
β€’ Memory allocation and data transfer from CPU to GPU time
β€’ Kernel execution time
β€’ Data transfer from GPU to CPU time
β€’ Speedup = CPU/GPU
4. Analyze the performance results in a few sentences.
β€’ Which one runs faster?
β€’ What’s the reason for that? Problem size, overhead, etc.

Timer functions #include <sys/time.h> long long start_timer() { struct timeval tv; gettimeofday(&tv, NULL); return tv.tv_sec * 1000000 + tv.tv_usec;
}

long long stop_timer(long long start_time, char *name) { struct timeval tv; gettimeofday(&tv, NULL);
long long end_time = tv.tv_sec * 1000000 + tv.tv_usec;
Printf(β€œ%s: %.5f sec ”, name, ((float) (end_time – start_time)) /
(1000 * 1000)); return end_time – start_time;
}

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