Provided by: nvidia-cuda-dev_7.5.18-0ubuntu1_amd64 bug

NAME

       Execution Control -

   Functions
       __cudart_builtin__ cudaError_t cudaFuncGetAttributes (struct cudaFuncAttributes *attr,
           const void *func)
           Find out attributes for a given function.
       cudaError_t cudaFuncSetCacheConfig (const void *func, enum cudaFuncCache cacheConfig)
           Sets the preferred cache configuration for a device function.
       cudaError_t cudaFuncSetSharedMemConfig (const void *func, enum cudaSharedMemConfig config)
           Sets the shared memory configuration for a device function.
       __device__ __cudart_builtin__ void * cudaGetParameterBuffer (size_t alignment, size_t
           size)
           Obtains a parameter buffer.
       __device__ __cudart_builtin__ void * cudaGetParameterBufferV2 (void *func, dim3
           gridDimension, dim3 blockDimension, unsigned int sharedMemSize)
           Launches a specified kernel.
       cudaError_t cudaLaunchKernel (const void *func, dim3 gridDim, dim3 blockDim, void **args,
           size_t sharedMem, cudaStream_t stream)
           Launches a device function.
       cudaError_t cudaSetDoubleForDevice (double *d)
           Converts a double argument to be executed on a device.
       cudaError_t cudaSetDoubleForHost (double *d)
           Converts a double argument after execution on a device.

Detailed Description

       \brief execution control functions of the CUDA runtime API (cuda_runtime_api.h)

       This section describes the execution control functions of the CUDA runtime application
       programming interface.

       Some functions have overloaded C++ API template versions documented separately in the C++
       API Routines module.

Function Documentation

   __cudart_builtin__ cudaError_t cudaFuncGetAttributes (struct cudaFuncAttributes * attr, const
       void * func)
       This function obtains the attributes of a function specified via func. func is a device
       function symbol and must be declared as a __global__ function. The fetched attributes are
       placed in attr. If the specified function does not exist, then
       cudaErrorInvalidDeviceFunction is returned. For templated functions, pass the function
       symbol as follows: func_name<template_arg_0,...,template_arg_N>

       Note that some function attributes such as maxThreadsPerBlock may vary based on the device
       that is currently being used.

       Parameters:
           attr - Return pointer to function's attributes
           func - Device function symbol

       Returns:
           cudaSuccess, cudaErrorInitializationError, cudaErrorInvalidDeviceFunction

       Note:
           Note that this function may also return error codes from previous, asynchronous
           launches.

           Use of a string naming a function as the func parameter was deprecated in CUDA 4.1 and
           removed in CUDA 5.0.

       See also:
           cudaConfigureCall, cudaFuncSetCacheConfig (C API), cudaFuncGetAttributes (C++ API),
           cudaLaunchKernel (C API), cudaSetDoubleForDevice, cudaSetDoubleForHost,
           cudaSetupArgument (C API)

   cudaError_t cudaFuncSetCacheConfig (const void * func, enum cudaFuncCache cacheConfig)
       On devices where the L1 cache and shared memory use the same hardware resources, this sets
       through cacheConfig the preferred cache configuration for the function specified via func.
       This is only a preference. The runtime will use the requested configuration if possible,
       but it is free to choose a different configuration if required to execute func.

       func is a device function symbol and must be declared as a __global__ function. If the
       specified function does not exist, then cudaErrorInvalidDeviceFunction is returned. For
       templated functions, pass the function symbol as follows:
       func_name<template_arg_0,...,template_arg_N>

       This setting does nothing on devices where the size of the L1 cache and shared memory are
       fixed.

       Launching a kernel with a different preference than the most recent preference setting may
       insert a device-side synchronization point.

       The supported cache configurations are:

       • cudaFuncCachePreferNone: no preference for shared memory or L1 (default)

       • cudaFuncCachePreferShared: prefer larger shared memory and smaller L1 cache

       • cudaFuncCachePreferL1: prefer larger L1 cache and smaller shared memory

       • cudaFuncCachePreferEqual: prefer equal size L1 cache and shared memory

       Parameters:
           func - Device function symbol
           cacheConfig - Requested cache configuration

       Returns:
           cudaSuccess, cudaErrorInitializationError, cudaErrorInvalidDeviceFunction

       Note:
           Note that this function may also return error codes from previous, asynchronous
           launches.

           Use of a string naming a function as the func parameter was deprecated in CUDA 4.1 and
           removed in CUDA 5.0.

       See also:
           cudaConfigureCall, cudaFuncSetCacheConfig (C++ API), cudaFuncGetAttributes (C API),
           cudaLaunchKernel (C API), cudaSetDoubleForDevice, cudaSetDoubleForHost,
           cudaSetupArgument (C API), cudaThreadGetCacheConfig, cudaThreadSetCacheConfig

   cudaError_t cudaFuncSetSharedMemConfig (const void * func, enum cudaSharedMemConfig config)
       On devices with configurable shared memory banks, this function will force all subsequent
       launches of the specified device function to have the given shared memory bank size
       configuration. On any given launch of the function, the shared memory configuration of the
       device will be temporarily changed if needed to suit the function's preferred
       configuration. Changes in shared memory configuration between subsequent launches of
       functions, may introduce a device side synchronization point.

       Any per-function setting of shared memory bank size set via cudaFuncSetSharedMemConfig
       will override the device wide setting set by cudaDeviceSetSharedMemConfig.

       Changing the shared memory bank size will not increase shared memory usage or affect
       occupancy of kernels, but may have major effects on performance. Larger bank sizes will
       allow for greater potential bandwidth to shared memory, but will change what kinds of
       accesses to shared memory will result in bank conflicts.

       This function will do nothing on devices with fixed shared memory bank size.

       For templated functions, pass the function symbol as follows:
       func_name<template_arg_0,...,template_arg_N>

       The supported bank configurations are:

       • cudaSharedMemBankSizeDefault: use the device's shared memory configuration when
         launching this function.

       • cudaSharedMemBankSizeFourByte: set shared memory bank width to be four bytes natively
         when launching this function.

       • cudaSharedMemBankSizeEightByte: set shared memory bank width to be eight bytes natively
         when launching this function.

       Parameters:
           func - Device function symbol
           config - Requested shared memory configuration

       Returns:
           cudaSuccess, cudaErrorInitializationError, cudaErrorInvalidDeviceFunction,
           cudaErrorInvalidValue,

       Note:
           Note that this function may also return error codes from previous, asynchronous
           launches.

           Use of a string naming a function as the func parameter was deprecated in CUDA 4.1 and
           removed in CUDA 5.0.

       See also:
           cudaConfigureCall, cudaDeviceSetSharedMemConfig, cudaDeviceGetSharedMemConfig,
           cudaDeviceSetCacheConfig, cudaDeviceGetCacheConfig, cudaFuncSetCacheConfig

   __device__ __cudart_builtin__ void* cudaGetParameterBuffer (size_t alignment, size_t size)
       Obtains a parameter buffer which can be filled with parameters for a kernel launch.
       Parameters passed to cudaLaunchDevice must be allocated via this function.

       This is a low level API and can only be accessed from Parallel Thread Execution (PTX).
       CUDA user code should use <<< >>> to launch kernels.

       Parameters:
           alignment - Specifies alignment requirement of the parameter buffer
           size - Specifies size requirement in bytes

       Returns:
           Returns pointer to the allocated parameterBuffer

       Note:
           Note that this function may also return error codes from previous, asynchronous
           launches.

       See also:
           cudaLaunchDevice

   __device__ __cudart_builtin__ void* cudaGetParameterBufferV2 (void * func, dim3 gridDimension,
       dim3 blockDimension, unsigned int sharedMemSize)
       Launches a specified kernel with the specified parameter buffer. A parameter buffer can be
       obtained by calling cudaGetParameterBuffer().

       This is a low level API and can only be accessed from Parallel Thread Execution (PTX).
       CUDA user code should use <<< >>> to launch the kernels.

       Parameters:
           func - Pointer to the kernel to be launched
           parameterBuffer - Holds the parameters to the launched kernel. parameterBuffer can be
           NULL. (Optional)
           gridDimension - Specifies grid dimensions
           blockDimension - Specifies block dimensions
           sharedMemSize - Specifies size of shared memory
           stream - Specifies the stream to be used

       Returns:
           cudaSuccess, cudaErrorInvalidDevice, cudaErrorLaunchMaxDepthExceeded,
           cudaErrorInvalidConfiguration, cudaErrorStartupFailure,
           cudaErrorLaunchPendingCountExceeded, cudaErrorLaunchOutOfResources

       Note:
           Note that this function may also return error codes from previous, asynchronous
           launches.
            Please refer to Execution Configuration and Parameter Buffer Layout from the CUDA
           Programming Guide for the detailed descriptions of launch configuration and parameter
           layout respectively.

       See also:
           cudaGetParameterBuffer

   cudaError_t cudaLaunchKernel (const void * func, dim3 gridDim, dim3 blockDim, void ** args,
       size_t sharedMem, cudaStream_t stream)
       The function invokes kernel func on gridDim (gridDim.x × gridDim.y × gridDim.z) grid of
       blocks. Each block contains blockDim (blockDim.x × blockDim.y × blockDim.z) threads.

       If the kernel has N parameters the args should point to array of N pointers. Each pointer,
       from args[0] to args[N - 1], point to the region of memory from which the actual parameter
       will be copied.

       For templated functions, pass the function symbol as follows:
       func_name<template_arg_0,...,template_arg_N>

       sharedMem sets the amount of dynamic shared memory that will be available to each thread
       block.

       stream specifies a stream the invocation is associated to.

       Parameters:
           func - Device function symbol
           gridDim - Grid dimentions
           blockDim - Block dimentions
           args - Arguments
           sharedMem - Shared memory
           stream - Stream identifier

       Returns:
           cudaSuccess, cudaErrorInvalidDeviceFunction, cudaErrorInvalidConfiguration,
           cudaErrorLaunchFailure, cudaErrorLaunchTimeout, cudaErrorLaunchOutOfResources,
           cudaErrorSharedObjectInitFailed

       Note:
           This function uses standard  semantics.

           Note that this function may also return error codes from previous, asynchronous
           launches.

       cudaLaunchKernel (C++ API)

   cudaError_t cudaSetDoubleForDevice (double * d)
       Parameters:
           d - Double to convert

       Deprecated
           This function is deprecated as of CUDA 7.5

       Converts the double value of d to an internal float representation if the device does not
       support double arithmetic. If the device does natively support doubles, then this function
       does nothing.

       Returns:
           cudaSuccess

       Note:
           Note that this function may also return error codes from previous, asynchronous
           launches.

       cudaLaunch (C API), cudaFuncSetCacheConfig (C API), cudaFuncGetAttributes (C API),
       cudaSetDoubleForHost, cudaSetupArgument (C API)

   cudaError_t cudaSetDoubleForHost (double * d)
       Deprecated
           This function is deprecated as of CUDA 7.5

       Converts the double value of d from a potentially internal float representation if the
       device does not support double arithmetic. If the device does natively support doubles,
       then this function does nothing.

       Parameters:
           d - Double to convert

       Returns:
           cudaSuccess

       Note:
           Note that this function may also return error codes from previous, asynchronous
           launches.

       cudaLaunch (C API), cudaFuncSetCacheConfig (C API), cudaFuncGetAttributes (C API),
       cudaSetDoubleForDevice, cudaSetupArgument (C API)

Author

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