Introduction to CUDA C/C++

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Vec<strong>to</strong>r Addition on the Device __global__ void add(int *a, int *b, int *c) { } c[blockIdx.x] = a[blockIdx.x] + b[blockIdx.x]; • On the device, each block can execute in parallel: Block 0 Block 1 c[0] = a[0] + b[0]; c[1] = a[1] + b[1]; Block 2 Block 3 c[2] = a[2] + b[2]; c[3] = a[3] + b[3]; © NVIDIA Corporation 2011
Vec<strong>to</strong>r Addition on the Device: main() #define N 512 int main(void) { int *a, *b, *c; int *d_a, *d_b, *d_c; int size = N * sizeof(int); // host copies of a, b, c // device copies of a, b, c // Alloc space for device copies of a, b, c cudaMalloc((void **)&d_a, size); cudaMalloc((void **)&d_b, size); cudaMalloc((void **)&d_c, size); // Alloc space for host copies of a, b, c and setup input values a = (int *)malloc(size); random_ints(a, N); b = (int *)malloc(size); random_ints(b, N); c = (int *)malloc(size); © NVIDIA Corporation 2011
Page 1 and 2: An Introduction to GPU Computing an
Page 3 and 4: What is CUDA? • CUDA Architecture
Page 5 and 6: Prerequisites • You (probably) ne
Page 7 and 8: CONCEPTS Heterogeneous Computing Bl
Page 9 and 10: Heterogeneous Computing #include #
Page 11 and 12: Simple Processing Flow PCI Bus 1. C
Page 13 and 14: Hello World! int main(void) { print
Page 15 and 16: Hello World! with Device Code __glo
Page 17 and 18: Hello World! with Device Code __glo
Page 19 and 20: Addition on the Device • A simple
Page 21 and 22: Memory Management • Host and devi
Page 23 and 24: Addition on the Device: main() int
Page 27: Vector Addition on the Device • W
Page 31 and 32: Review (1 of 2) • Difference betw
Page 37 and 38: Indexing Arrays with Blocks and Thr
Page 39 and 40: Addition with Blocks and Threads: m
Page 41 and 42: Handling Arbitrary Vector Sizes •
Page 45 and 46: Implementing Within a Block • Eac
Page 47 and 48: Implementing With Shared Memory •
Page 49 and 50: Stencil Kernel // Apply the stencil
Page 51 and 52: __syncthreads() • void __syncthre
Page 53 and 54: Stencil Kernel // Apply the stencil
Page 55 and 56: Review (2 of 2) • Use __shared__
Page 57 and 58: Coordinating Host & Device • Kern
Page 59 and 60: Device Management • Application c
Page 61 and 62: Resources • We skipped some detai

Introduction to CUDA C/C++

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