Man pages sections > man3 > CUDART_THREAD_DEPRECATED

Thread Management [DEPRECATED] - deprecated thread management functions of the

Thread Management [DEPRECATED](3) Doxygen Thread Management [DEPRECATED](3)

NAME

Thread Management [DEPRECATED] - deprecated thread management functions of the CUDA runtime API (cuda_runtime_api.h)
 

Functions


cudaError_t cudaThreadExit (void)
 
Exit and clean up from CUDA launches. cudaError_t cudaThreadGetCacheConfig (enum cudaFuncCache *pCacheConfig)
 
Returns the preferred cache configuration for the current device. cudaError_t cudaThreadGetLimit (size_t *pValue, enum cudaLimit limit)
 
Returns resource limits. cudaError_t cudaThreadSetCacheConfig (enum cudaFuncCache cacheConfig)
 
Sets the preferred cache configuration for the current device. cudaError_t cudaThreadSetLimit (enum cudaLimit limit, size_t value)
 
Set resource limits. cudaError_t cudaThreadSynchronize (void)
 
Wait for compute device to finish.

Detailed Description

This section describes deprecated thread management functions of the CUDA runtime application programming interface.

Function Documentation

cudaError_t cudaThreadExit (void)

Deprecated
Note that this function is deprecated because its name does not reflect its behavior. Its functionality is identical to the non-deprecated function cudaDeviceReset(), which should be used instead.
Explicitly destroys all cleans up all resources associated with the current device in the current process. Any subsequent API call to this device will reinitialize the device.
Note that this function will reset the device immediately. It is the caller's responsibility to ensure that the device is not being accessed by any other host threads from the process when this function is called.
Returns:
cudaSuccess
Note:
Note that this function may also return error codes from previous, asynchronous launches.
See also:
cudaDeviceReset

cudaError_t cudaThreadGetCacheConfig (enum cudaFuncCache * pCacheConfig)

Deprecated
Note that this function is deprecated because its name does not reflect its behavior. Its functionality is identical to the non-deprecated function cudaDeviceGetCacheConfig(), which should be used instead.
On devices where the L1 cache and shared memory use the same hardware resources, this returns through pCacheConfig the preferred cache configuration for the current device. 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 functions.
This will return a pCacheConfig of cudaFuncCachePreferNone on devices where the size of the L1 cache and shared memory are fixed.
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
Parameters:
pCacheConfig - Returned cache configuration
Returns:
cudaSuccess, cudaErrorInitializationError
Note:
Note that this function may also return error codes from previous, asynchronous launches.
See also:
cudaDeviceGetCacheConfig

cudaError_t cudaThreadGetLimit (size_t * pValue, enum cudaLimit limit)

Deprecated
Note that this function is deprecated because its name does not reflect its behavior. Its functionality is identical to the non-deprecated function cudaDeviceGetLimit(), which should be used instead.
Returns in *pValue the current size of limit. The supported cudaLimit values are:
cudaLimitStackSize: stack size of each GPU thread;
cudaLimitPrintfFifoSize: size of the shared FIFO used by the printf() and fprintf() device system calls.
cudaLimitMallocHeapSize: size of the heap used by the malloc() and free() device system calls;
Parameters:
limit - Limit to query
 
pValue - Returned size in bytes of limit
Returns:
cudaSuccess, cudaErrorUnsupportedLimit, cudaErrorInvalidValue
Note:
Note that this function may also return error codes from previous, asynchronous launches.
See also:
cudaDeviceGetLimit

cudaError_t cudaThreadSetCacheConfig (enum cudaFuncCache cacheConfig)

Deprecated
Note that this function is deprecated because its name does not reflect its behavior. Its functionality is identical to the non-deprecated function cudaDeviceSetCacheConfig(), which should be used instead.
On devices where the L1 cache and shared memory use the same hardware resources, this sets through cacheConfig the preferred cache configuration for the current device. 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 the function. Any function preference set via cudaFuncSetCacheConfig (C API) or cudaFuncSetCacheConfig (C++ API) will be preferred over this device-wide setting. Setting the device-wide cache configuration to cudaFuncCachePreferNone will cause subsequent kernel launches to prefer to not change the cache configuration unless required to launch the kernel.
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
Parameters:
cacheConfig - Requested cache configuration
Returns:
cudaSuccess, cudaErrorInitializationError
Note:
Note that this function may also return error codes from previous, asynchronous launches.
See also:
cudaDeviceSetCacheConfig

cudaError_t cudaThreadSetLimit (enum cudaLimit limit, size_t value)

Deprecated
Note that this function is deprecated because its name does not reflect its behavior. Its functionality is identical to the non-deprecated function cudaDeviceSetLimit(), which should be used instead.
Setting limit to value is a request by the application to update the current limit maintained by the device. The driver is free to modify the requested value to meet h/w requirements (this could be clamping to minimum or maximum values, rounding up to nearest element size, etc). The application can use cudaThreadGetLimit() to find out exactly what the limit has been set to.
Setting each cudaLimit has its own specific restrictions, so each is discussed here.
cudaLimitStackSize controls the stack size of each GPU thread.
cudaLimitPrintfFifoSize controls the size of the shared FIFO used by the printf() and fprintf() device system calls. Setting cudaLimitPrintfFifoSize must be performed before launching any kernel that uses the printf() or fprintf() device system calls, otherwise cudaErrorInvalidValue will be returned.
cudaLimitMallocHeapSize controls the size of the heap used by the malloc() and free() device system calls. Setting cudaLimitMallocHeapSize must be performed before launching any kernel that uses the malloc() or free() device system calls, otherwise cudaErrorInvalidValue will be returned.
Parameters:
limit - Limit to set
 
value - Size in bytes of limit
Returns:
cudaSuccess, cudaErrorUnsupportedLimit, cudaErrorInvalidValue
Note:
Note that this function may also return error codes from previous, asynchronous launches.
See also:
cudaDeviceSetLimit

cudaError_t cudaThreadSynchronize (void)

Deprecated
Note that this function is deprecated because its name does not reflect its behavior. Its functionality is similar to the non-deprecated function cudaDeviceSynchronize(), which should be used instead.
Blocks until the device has completed all preceding requested tasks. cudaThreadSynchronize() returns an error if one of the preceding tasks has failed. If the cudaDeviceScheduleBlockingSync flag was set for this device, the host thread will block until the device has finished its work.
Returns:
cudaSuccess
Note:
Note that this function may also return error codes from previous, asynchronous launches.
See also:
cudaDeviceSynchronize

Author

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