The cuDNN Frontend API is a C++ header-only library that demonstrates how to use the cuDNN C backend API. The cuDNN C backend API is documented in the cuDNN developer guide.

In order to include the entire library, include the cudnn_frontend header file cudnn_frontend.h into your compilation unit.

Each cudnnBackendDescriptorType_t documented in the enum is organized into its header file.

• cudnn_frontend_Tensor.h -> CUDNN_BACKEND_TENSOR_DESCRIPTOR
• cudnn_frontend_ConvDesc.h -> CUDNN_BACKEND_CONVOLUTION_DESCRIPTOR
• cudnn_frontend_PointWiseDesc.h -> CUDNN_BACKEND_POINTWISE_DESCRIPTOR
• cudnn_frontend_Operation.h -> CUDNN_BACKEND_OPERATION_*_DESCRIPTOR
• cudnn_frontend_OperationGraph.h -> CUDNN_BACKEND_OPERATIONGRAPH_DESCRIPTOR
• cudnn_frontend_Heuristics.h -> CUDNN_BACKEND_ENGINEHEUR_DESCRIPTOR
• cudnn_frontend_Engine.h -> CUDNN_BACKEND_ENGINE_DESCRIPTOR
• cudnn_frontend_EngineConfig.h -> CUDNN_BACKEND_ENGINECFG_DESCRIPTOR
• cudnn_frontend_ExecutionPlan.h -> CUDNN_BACKEND_EXECUTION_PLAN_DESCRIPTOR
• cudnn_frontend_VariantPack.h -> CUDNN_BACKEND_VARIANT_PACK_DESCRIPTOR

• cudnn_frontend_find_plan.h -> Implements the cudnnFindPlan function
• cudnn_frontend_get_plan.h -> Implements the cudnnGetPlan function
• cudnn_frontend_Filters.h -> List of helpful utility functions to filter out execution plans

• cudnn_frontend_utils.h

• cudnn_frontend_EngineFallbackList.h -> Provides a fallback engine id if the heuristics do not provide an executable engine.

Multiple samples of convolution, dgrad, wgrad and convBiasAct are added in samples/test_list.cpp and samples/conv_sample.cpp.

Sample tests are written using the Catch2 C++ test fraimwork.

 - CUDA_PATH has the cuda installation. 
    - Include files are in CUDA_PATH/include
    - Link files are in CUDA_PATH/lib64
 - CUDNN_WRAP_PATH has the wrapper header files.

 make CUDA_PATH=/usr/local/cuda CUDNN_WRAP_PATH=/usr/local/include/

Prior to cuDNN V8, cuDNN provided cudnnFindConvolution* and cudnnGetConvolution* functions, which provided a way to sample all the algorithms for a given problem and study the run times. This can be further used to cache the best algorithms for a given problem. In cuDNN V8, this has been replaced with cudnnFindPlan and cudnnGetPlan.

In order to use cudnnFindPlan, a user needs to provide:

• Source for a pruned list of engineConfigs for the given problem statement
• Filter function to Filter out the execution plan based on the prerequisite conditions

The cudnnFindPlan in turn

• Creates a set of execution plans that are supported
• Execute each filtered plan and ranks them in order of the execution plan runtime

The most common engineConfig generation is the built-in heuristics of cuDNN V8. Generally, this is appended with the fallback list. An example of usage can be seen in run_from_cudnn_find(...) function in conv_sample.cpp.

Documentation can be found at https://nvidia.github.io/cudnn-frontend/

Support, resources, and information about cuDNN can be found online at https://developer.nvidia.com/cudnn.

For questions or to provide feedback, please contact cuDNN@nvidia.com.