6.2. Thread Management [DEPRECATED]

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

Functions

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

Functions

__host__cudaError_t cudaThreadExit ( void )
Exit and clean up from CUDA launches.
Returns

cudaSuccess

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.

Description

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.

Note:

See also:

cudaDeviceReset

__host__cudaError_t cudaThreadGetCacheConfig ( cudaFuncCache ** pCacheConfig )
Returns the preferred cache configuration for the current device.
Parameters
pCacheConfig
- Returned cache configuration
Returns

cudaSuccess

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.

Description

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:

Note:

See also:

cudaDeviceGetCacheConfig

__host__cudaError_t cudaThreadGetLimit ( size_t* pValue, cudaLimit limit )
Returns resource limits.
Parameters
pValue
- Returned size in bytes of limit
limit
- Limit to query
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.

Description

Returns in *pValue the current size of limit. The supported cudaLimit values are:

Note:

See also:

cudaDeviceGetLimit

__host__cudaError_t cudaThreadSetCacheConfig ( cudaFuncCache cacheConfig )
Sets the preferred cache configuration for the current device.
Parameters
cacheConfig
- Requested cache configuration
Returns

cudaSuccess

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.

Description

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:

Note:

See also:

cudaDeviceSetCacheConfig

__host__cudaError_t cudaThreadSetLimit ( cudaLimit limit, size_t value )
Set resource limits.
Parameters
limit
- Limit to set
value
- Size in bytes of 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 cudaDeviceSetLimit(), which should be used instead.

Description

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.

Note:

See also:

cudaDeviceSetLimit

__host__cudaError_t cudaThreadSynchronize ( void )
Wait for compute device to finish.
Returns

cudaSuccess

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.

Description

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.

Note:

See also:

cudaDeviceSynchronize