Provided by: nvidia-cuda-dev_7.5.18-0ubuntu1_amd64 
NAME
Thread Management [DEPRECATED] -
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
\brief deprecated thread management functions of the CUDA runtime API (cuda_runtime_api.h)
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
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Version 6.0 15 Aug 2015 Thread Management [DEPRECATED](3)