Man pages sections > man3 > CUDART_EXECUTION

Execution Control - execution control functions of the CUDA runtime API

Execution Control(3) Doxygen Execution Control(3)

NAME

Execution Control - execution control functions of the CUDA runtime API (cuda_runtime_api.h)
 

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

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 dimensions
 
blockDim - Block dimensions
 
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

Generated automatically by Doxygen from the source code.
13 Jan 2017 Version 6.0