Understanding how your application is using the GPU is crucial to identifying opportunities for performance optimization. Performance analysis tools are also great for identifying performance bottlenecks in your CPU code that can be eliminated by moving computationally intensive algorithms to the GPU.
The performance analysis tools listed below will help you optimize your GPU-accelerated applications:
|NVIDIA® Nsight™ is the ultimate development platform for heterogeneous computing. Work with powerful debugging and profiling tools that enable you to fully optimize the performance of the CPU and GPU. Find out about the new Ecilipse Edition and the graphics debugging enabled Visual Studio Edition.|
|NVIDIA Visual Profiler is a cross-platform performance profiling tool that delivers developers vital feedback for optimizing CUDA C/C++ applications. First introduced in 2008, Visual Profiler supports all CUDA capable NVIDIA GPUs shipped since 2006 on Linux, Mac OS X, and Windows.|
|TAU Performance System® is a profiling and tracing toolkit for performance analysis of hybrid parallel programs written in CUDA, and pyCUDA., and HMPP. TAU gathers performance information of GPU computations and integrates it with other application performance data, through instrumentation of functions, methods, basic blocks, and statements.|
|VampirTrace performance monitor comes with CUDA, and PyCUDA support to give detailed insight into the runtime behavior of accelerators. This enables an extensive performance analysis and optimization of hybrid programs.|
|The PAPI CUDA Component is a hardware performance counter measurement technology for the NVIDIA CUDA platform which provides access to the hardware counters inside the GPU. PAPI CUDA Component can provide detailed performance counter information regarding the execution of GPU kernels.|
|The NVIDIA CUDA Profiling Tools Interface (CUPTI) provides performance analysis tools with detailed information about how applications are using the GPUs in a system. CUPTI is used by performance analysis tools such as the NVIDIA Visual Profiler, TAU and Vampir Trace.|
Looking for expert advice on optimizing your GPU code or identifying opportunities for GPU acceleration in your application?
Try reviewing the documentation and educational materials below or get in touch with industry experts and NVIDIA engineers on the CUDA Developer forums
Check out the rest of the CUDA Tools and Ecosystem