NVidia has just released their new OpenCL Visual Profiler for Windows and Linux, offering key insights into OpenCL kernels for developers worldwide.
Key features include:
- Profiling of actual hardware signals, kernel efficiency, and instruction issue rate
- Timing of memory copies between system memory and GPU dedicated memory
- Customizable graphs to help developers focus in on problem areas
- Basic auto-analysis to reveal warp serialization problems
- Easy import/export to CSV for custom analysis
Also, they’ve released a good PDF on “OpenCL Best Practices” that you can download from their website. Get the links and the full press release after the break.
NVIDIA Releases Industry’s First OpenCL Performance Profiler for the GPU
New OpenCL Visual Profiler for Windows and Linux Now Available to Thousands of Developers
Leveraging the extensive performance instrumentation in NVIDIA’s OpenCL drivers and hardware performance signals designed into NVIDIA GPUs, the OpenCL Visual Profiler provides developers with insight into performance bottlenecks and opportunities for optimization.
Key features include:
- Profiling of actual hardware signals, kernel efficiency, and instruction issue rate
- Timing of memory copies between system memory and GPU dedicated memory
- Customizable graphs to help developers focus in on problem areas
- Basic auto-analysis to reveal warp serialization problems
- Easy import/export to CSV for custom analysis
NVIDIA has also prepared a helpful OpenCL Best Practices Guide designed to help OpenCL developers programming for the CUDA architecture implement high performance parallel algorithms and understand best practices for GPU Computing.
Chapters on the following topics and more are included in the guide:
- GPU Computing with OpenCL
- Performance Metrics
- Memory Optimizations
- NDRange Optimizations
- Instruction Optimizations
- Control Flow
- Performance Optimization Strategies
The OpenCL Visual Profiler is now available to all NVIDIA GPU Computing Registered developers, and will be included in the next public release of the CUDA Toolkit. The OpenCL Best Practices Guide is already publicly available at: http://www.nvidia.com/content/cudazone/CUDABrowser/downloads/papers/NVIDIA_OpenCL_BestPracticesGuide.pdfProfessional developers and researchers are invited to apply for the program at: http://developer.nvidia.com/page/registered_developer_program.html
