Questions tagged [cuda]

CUDA is Nvidia's parallel computing platform and programming model for GPUs (Graphics Processing Units). CUDA provides an interface to Nvidia GPUs through a variety of programming languages, libraries, and APIs. Before posting CUDA questions, please read "How to get Useful Answers to your CUDA Questions on Stack Overflow" below.

CUDA has an online documentation repository, updated with each release, including references for APIs and libraries; user guides for applications; and a detailed CUDA C/C++ Programming Guide.

The CUDA platform enables application development using several languages and associated APIs, including:

• CUDA C/C++
• Fortran
• OpenACC
• OpenCL
• DirectCompute
• JCUDA
• PyCUDA

There also exist third-party bindings for using CUDA in other languages and programming environments, such as Managed CUDA for .net languages (including C#).

You should ask questions about CUDA here on Stack Overflow, but if you have bugs to report you should discuss them on the CUDA forums or report them via the registered developer portal. You may want to cross-link to any discussion here on SO.

How to get Useful Answers to your CUDA questions on

Here are a number of suggestions to users new to CUDA. Follow these suggestions before asking your question and you are much more likely to get a satisfactory answer!

• Always check the result codes returned by CUDA API functions to ensure you are getting cudaSuccess. If you are not, and you don't know why, include the information about the error in your question. This includes checking for errors caused by the most recent kernel launch, which may not be available before you've called cudaDeviceSynchronize() or cudaStreamSynchronize(). More on checking for errors in CUDA in this question.
• If you are getting unspecified launch failure it is possible that your code is causing a segmentation fault, meaning the code is accessing memory that is not allocated for the code to use. Try to verify that the indexing is correct and check if the CUDA Compute Sanitizer (or cuda-memcheck) is reporting any errors.
• The debugger for CUDA, cuda-gdb, is also very useful when you are not really sure what you are doing. You can monitor resources by warp, thread, block, SM and grid level. You can follow your program's execution. If a segmentation fault occurs in your program, cuda-gdb can help you find where the crash occurred and see what the context is.
• If you are finding that you are getting syntax errors on CUDA keywords when compiling device code, make sure you are compiling using nvcc (or clang with CUDA support enabled) and that your source file has the expected .cu extension. If you find that CUDA device functions or feature namespaces you expect to work are not found (atomic functions, warp voting functions, half-precision arithmetic, cooperative groups, etc.), ensure that you are explicitly passing compilation arguments which enable architecture settings which support those features.

Books

• Professional CUDA C Programming

• The CUDA Handbook: A Comprehensive Guide to GPU Programming

• CUDA by Example: An Introduction to General-Purpose GPU Programming

• CUDA Programming: A Developer's Guide to Parallel Computing with GPUs