A deep technical dive into CUDA kernel execution: from source code to GPU warps
By
mezark
Summary
This article provides an in-depth technical walkthrough of what happens when a CUDA kernel (specifically a vector-add kernel) is executed. It traces the journey from the CUDA source code (nvcc compilation) all the way down to the hardware level where warps execute on GPU cores. The piece covers GPU architecture concepts like thread blocks, warps, memory hierarchy, and the CUDA execution model in meticulous detail.
Source
Hacker NewsA deep technical dive into CUDA kernel execution: from source code to GPU warpsfergusfinn.comKey quotes
· 3 pulledHere's a simple CUDA program. It adds two vectors.
__global__ void vadd(const float* a, const float* b, float* c, int n) { int i = blockIdx.x * blockDim.x + threadIdx.x; if (i < n) c[i] = a[i] + b[i]; }
Tracing one vector-add kernel from nvcc all the way down to the warps that execute it.
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