Functions

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:

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

See also:

cudaDeviceReset

cudaError_t cudaThreadGetCacheConfig ( cudaFuncCache ** pCacheConfig )

Returns the preferred cache configuration for the current device.

Parameters

pCacheConfig

- Returned cache configuration

Returns

cudaSuccess, cudaErrorInitializationError

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:

• 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

Note:

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

See also:

cudaDeviceGetCacheConfig

cudaError_t cudaThreadGetLimit ( size_t* pValue, cudaLimit limit )

Returns resource limits.

Parameters

pValue

- Returned size in bytes of limit

limit

- Limit to query

Returns

cudaSuccess, cudaErrorUnsupportedLimit, cudaErrorInvalidValue

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:

• 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;

Note:

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

See also:

cudaDeviceGetLimit

cudaError_t cudaThreadSetCacheConfig ( cudaFuncCache cacheConfig )

Sets the preferred cache configuration for the current device.

Parameters

cacheConfig

- Requested cache configuration

Returns

cudaSuccess, cudaErrorInitializationError

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:

• 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

Note:

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

See also:

cudaDeviceSetCacheConfig

cudaError_t cudaThreadSetLimit ( cudaLimit limit, size_t value )

Set resource limits.

Parameters

limit

- Limit to set

value

- Size in bytes of limit

Returns

cudaSuccess, cudaErrorUnsupportedLimit, cudaErrorInvalidValue

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.

• cudaLimitStackSize controls the stack size of each GPU thread. This limit is only applicable to devices of compute capability 2.0 and higher. Attempting to set this limit on devices of compute capability less than 2.0 will result in the error cudaErrorUnsupportedLimit being returned.

• 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. This limit is only applicable to devices of compute capability 2.0 and higher. Attempting to set this limit on devices of compute capability less than 2.0 will result in the error cudaErrorUnsupportedLimit being 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. This limit is only applicable to devices of compute capability 2.0 and higher. Attempting to set this limit on devices of compute capability less than 2.0 will result in the error cudaErrorUnsupportedLimit being returned.

Note:

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

See also:

cudaDeviceSetLimit

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:

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

See also:

cudaDeviceSynchronize