Profiling and Optimizing CUDA Kernel Code with NVIDIA Nsight Visual Studio Edition 3.0
Discover how the the analysis features of NVIDIA Nsight Visual Studio Edition can guide you in improving the performance of your CUDA application and your CUDA kernels. Using examples of various code patterns and kernel samples, we will discuss ways to spot common performance bottlenecks and implement code optimizations based on measured profiling data. Nsight's new Source-Level Experiments will be used to further dive into analyzing CUDA-C kernel source code - allowing to evaluate performance characteristics from individual CUDA-C source code lines down to each executed assembly instruction.
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