An opaque descriptor handle. The descriptor encapsulates multiple created and configured resources. Created via cuDevResourceGenerateDesc

Type of resource

Sharing scope for workqueues

Converts a green context into the primary context.

Parameters

pContext

Returned primary context with green context resources

hCtx

Green context to convert

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_CONTEXT, CUDA_ERROR_INVALID_VALUE

Description

The API converts a green context into the primary context returned in pContext. It is important to note that the converted context pContext is a normal primary context but with the resources of the specified green context hCtx. Once converted, it can then be used to set the context current with cuCtxSetCurrent or with any of the CUDA APIs that accept a CUcontext parameter.

Users are expected to call this API before calling any CUDA APIs that accept a CUcontext. Failing to do so will result in the APIs returning CUDA_ERROR_INVALID_CONTEXT.

See also:

cuGreenCtxCreate

Get context resources.

Parameters

hCtx

- Context to get resource for

resource

- Output pointer to a CUdevResource structure

type

- Type of resource to retrieve

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_RESOURCE_TYPE, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_INVALID_CONTEXT

Description

Get the type resources available to the context represented by hCtx Note: The API is not supported on 32-bit platforms.

See also:

cuDevResourceGenerateDesc

Generate a resource descriptor.

Parameters

phDesc

- Output descriptor

resources

- Array of resources to be included in the descriptor

nbResources

- Number of resources passed in resources

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_INVALID_RESOURCE_TYPE, CUDA_ERROR_INVALID_RESOURCE_CONFIGURATION

Description

Generates a single resource descriptor with the set of resources specified in resources. The generated resource descriptor is necessary for the creation of green contexts via the cuGreenCtxCreate API. Resources of the same type can be passed in, provided they meet the requirements as noted below.

A successful API call must have:

• A valid output pointer for the phDesc descriptor as well as a valid array of resources pointers, with the array size passed in nbResources. If multiple resources are provided in resources, the device they came from must be the same, otherwise CUDA_ERROR_INVALID_RESOURCE_CONFIGURATION is returned. If multiple resources are provided in resources and they are of type CU_DEV_RESOURCE_TYPE_SM, they must be outputs (whether result or remaining) from the same split API instance and have the same smCoscheduledAlignment values, otherwise CUDA_ERROR_INVALID_RESOURCE_CONFIGURATION is returned.

Note: The API is not supported on 32-bit platforms.

See also:

cuDevSmResourceSplitByCount

Splits a CU_DEV_RESOURCE_TYPE_SM resource into structured groups.

Parameters

result

- Output array of CUdevResource resources. Can be NULL, alongside an smCount of 0, for discovery purpose.

nbGroups

- Specifies the number of groups in result and groupParams

input

- Input SM resource to be split. Must be a valid CU_DEV_RESOURCE_TYPE_SM resource.

remainder

- If splitting the input resource leaves any SMs, the remainder is placed in here.

flags

- Flags specifying how the API should behave. The value should be 0 for now.

groupParams

- Description of how the SMs should be split and assigned to the corresponding result entry.

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_DEVICE, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_INVALID_RESOURCE_TYPE, CUDA_ERROR_INVALID_RESOURCE_CONFIGURATION

Description

This API will split a resource of CU_DEV_RESOURCE_TYPE_SM into nbGroups structured device resource groups (the result array), as well as an optional remainder, according to a set of requirements specified in the groupParams array. The term “structured” is a trait that specifies the result has SMs that are co-scheduled together. This co-scheduling can be specified via the coscheduledSmCount field of the groupParams structure, while the smCount will specify how many SMs are required in total for that result. The remainder is always “unstructured”, it does not have any set guarantees with respect to co-scheduling and those properties will need to either be queried via the occupancy set of APIs or further split into structured groups by this API.

The API has a discovery mode for use cases where it is difficult to know ahead of time what the SM count should be. Discovery happens when the smCount field of a given groupParams array entry is set to 0 - the smCount will be filled in by the API with the derived SM count according to the provided groupParams fields and constraints. Discovery can be used with both a valid result array and with a NULL result pointer value. The latter is useful in situations where the smCount will end up being zero, which is an invalid value to create a result entry with, but allowed for discovery purposes when the result is NULL.

The groupParams array is evaluated from index 0 to nbGroups - 1. For each index in the groupParams array, the API will evaluate which SMs may be a good fit based on constraints and assign those SMs to result. This evaluation order is important to consider when using discovery mode, as it helps discover the remaining SMs.

For a valid call:

• result should point to a CUdevResource array of size nbGroups, or alternatively, may be NULL, if the developer wishes for only the groupParams entries to be updated

• input should be a valid CU_DEV_RESOURCE_TYPE_SM resource that originates from querying the green context, device context, or device.

• The remainder group may be NULL.

• There are no API flags at this time, so the value passed in should be 0.

• A CU_DEV_SM_RESOURCE_GROUP_PARAMS array of size nbGroups. Each entry must be zero-initialized.

  • smCount: must be either 0 or in the range of [2,inputSmCount] where inputSmCount is the amount of SMs the input resource has. smCount must be a multiple of 2, as well as a multiple of coscheduledSmCount. When assigning SMs to a group (and if results are expected by having the result parameter set), smCount cannot end up with 0 or a value less than coscheduledSmCount otherwise CUDA_ERROR_INVALID_RESOURCE_CONFIGURATION will be returned.

  • coscheduledSmCount: allows grouping SMs together in order to be able to launch clusters on Compute Architecture 9.0+. The default value may be queried from the device’s CU_DEV_RESOURCE_TYPE_SM resource (8 on Compute Architecture 9.0+ and 2 otherwise). The maximum is 32 on Compute Architecture 9.0+ and 2 otherwise.

  • preferredCoscheduledSmCount: Attempts to merge coscheduledSmCount groups into larger groups, in order to make use of preferredClusterDimensions on Compute Architecture 10.0+. The default value is set to coscheduledSmCount.

  • flags:

    • CU_DEV_SM_RESOURCE_SPLIT_BACKFILL: lets smCount be a non-multiple of coscheduledSmCount, filling the difference between SM count and already assigned co-scheduled groupings with other SMs. This lets any resulting group behave similar to the remainder group for example.

Example params and their effect:

A groupParams array element is defined in the following order:

‎ { .smCount, .coscheduledSmCount, .preferredCoscheduledSmCount, .flags, \/\* .reserved \*\/ }

‎// Example 1
      // Will discover how many SMs there are, that are co-scheduled in groups of smCoscheduledAlignment.
      // The rest is placed in the optional remainder.
      CU_DEV_SM_RESOURCE_GROUP_PARAMS params { 0, 0, 0, 0 };

‎// Example 2
      // Assuming the device has 10+ SMs, the result will have 10 SMs that are co-scheduled in groups of 2 SMs.
      // The rest is placed in the optional remainder.
      CU_DEV_SM_RESOURCE_GROUP_PARAMS params { 10, 2, 0, 0};
      // Setting the coscheduledSmCount to 2 guarantees that we can always have a valid result
      // as long as the SM count is less than or equal to the input resource SM count.

‎// Example 3
      // A single piece is split-off, but instead of assigning the rest to the remainder, a second group contains everything else
      // This assumes the device has 10+ SMs (8 of which are coscheduled in groups of 4),
      // otherwise the second group could end up with 0 SMs, which is not allowed.
      CU_DEV_SM_RESOURCE_GROUP_PARAMS params { {8, 4, 0, 0}, {0, 2, 0, CU_DEV_SM_RESOURCE_SPLIT_BACKFILL } }

The difference between a catch-all param group as the last entry and the remainder is in two aspects:

• The remainder may be NULL / _TYPE_INVALID (if there are no SMs remaining), while a result group must always be valid.

• The remainder does not have a structure, while the result group will always need to adhere to a structure of coscheduledSmCount (even if its just 2), and therefore must always have enough coscheduled SMs to cover that requirement (even with the CU_DEV_SM_RESOURCE_SPLIT_BACKFILL flag enabled).

Splitting an input into N groups, can be accomplished by repeatedly splitting off 1 group and re-splitting the remainder (a bisect operation). However, it's recommended to accomplish this with a single call wherever possible.

See also:

cuGreenCtxGetDevResource, cuCtxGetDevResource, cuDeviceGetDevResource

Splits CU_DEV_RESOURCE_TYPE_SM resources.

Parameters

result

- Output array of CUdevResource resources. Can be NULL to query the number of groups.

nbGroups

- This is a pointer, specifying the number of groups that would be or should be created as described below.

input

- Input SM resource to be split. Must be a valid CU_DEV_RESOURCE_TYPE_SM resource.

remainder

- If the input resource cannot be cleanly split among nbGroups, the remainder is placed in here. Can be ommitted (NULL) if the user does not need the remaining set.

flags

- Flags specifying how these partitions are used or which constraints to abide by when splitting the input. Zero is valid for default behavior.

minCount

- Minimum number of SMs required

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_DEVICE, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_INVALID_RESOURCE_TYPE, CUDA_ERROR_INVALID_RESOURCE_CONFIGURATION

Description

Splits CU_DEV_RESOURCE_TYPE_SM resources into nbGroups, adhering to the minimum SM count specified in minCount and the usage flags in flags. If result is NULL, the API simulates a split and provides the amount of groups that would be created in nbGroups. Otherwise, nbGroups must point to the amount of elements in result and on return, the API will overwrite nbGroups with the amount actually created. The groups are written to the array in result. nbGroups can be less than the total amount if a smaller number of groups is needed.

This API is used to spatially partition the input resource. The input resource needs to come from one of cuDeviceGetDevResource, cuCtxGetDevResource, or cuGreenCtxGetDevResource. A limitation of the API is that the output results cannot be split again without first creating a descriptor and a green context with that descriptor.

When creating the groups, the API will take into account the performance and functional characteristics of the input resource, and guarantee a split that will create a disjoint set of symmetrical partitions. This may lead to fewer groups created than purely dividing the total SM count by the minCount due to cluster requirements or alignment and granularity requirements for the minCount. These requirements can be queried with cuDeviceGetDevResource, cuCtxGetDevResource, and cuGreenCtxGetDevResource for CU_DEV_RESOURCE_TYPE_SM, using the minSmPartitionSize and smCoscheduledAlignment fields to determine minimum partition size and alignment granularity, respectively.

The remainder set does not have the same functional or performance guarantees as the groups in result. Its use should be carefully planned and future partitions of the remainder set are discouraged.

The following flags are supported:

• CU_DEV_SM_RESOURCE_SPLIT_IGNORE_SM_COSCHEDULING : Lower the minimum SM count and alignment, and treat each SM independent of its hierarchy. This allows more fine grained partitions but at the cost of advanced features (such as large clusters on compute capability 9.0+).

• CU_DEV_SM_RESOURCE_SPLIT_MAX_POTENTIAL_CLUSTER_SIZE : Compute Capability 9.0+ only. Attempt to create groups that may allow for maximally sized thread clusters. This can be queried post green context creation using cuOccupancyMaxPotentialClusterSize.

A successful API call must either have:

• A valid array of result pointers of size passed in nbGroups, with input of type CU_DEV_RESOURCE_TYPE_SM. Value of minCount must be between 0 and the SM count specified in input. remainder may be NULL.

• NULL passed in for result, with a valid integer pointer in nbGroups and input of type CU_DEV_RESOURCE_TYPE_SM. Value of minCount must be between 0 and the SM count specified in input. remainder may be NULL. This queries the number of groups that would be created by the API.

Note: The API is not supported on 32-bit platforms.

See also:

cuGreenCtxGetDevResource, cuCtxGetDevResource, cuDeviceGetDevResource

Get device resources.

Parameters

device

- Device to get resource for

resource

- Output pointer to a CUdevResource structure

type

- Type of resource to retrieve

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_RESOURCE_TYPE, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_INVALID_DEVICE

Description

Get the type resources available to the device. This may often be the starting point for further partitioning or configuring of resources.

Note: The API is not supported on 32-bit platforms.

See also:

cuDevResourceGenerateDesc

Creates a green context with a specified set of resources.

Parameters

phCtx

- Pointer for the output handle to the green context

desc

- Descriptor generated via cuDevResourceGenerateDesc which contains the set of resources to be used

dev

- Device on which to create the green context.

flags

- One of the supported green context creation flags. CU_GREEN_CTX_DEFAULT_STREAM is required.

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_DEVICE, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_NOT_SUPPORTED, CUDA_ERROR_OUT_OF_MEMORY

Description

This API creates a green context with the resources specified in the descriptor desc and returns it in the handle represented by phCtx. This API will retain the primary context on device dev, which will is released when the green context is destroyed. It is advised to have the primary context active before calling this API to avoid the heavy cost of triggering primary context initialization and deinitialization multiple times.

The API does not set the green context current. In order to set it current, you need to explicitly set it current by first converting the green context to a CUcontext using cuCtxFromGreenCtx and subsequently calling cuCtxSetCurrent / cuCtxPushCurrent. It should be noted that a green context can be current to only one thread at a time. There is no internal synchronization to make API calls accessing the same green context from multiple threads work.

Note: The API is not supported on 32-bit platforms.

The supported flags are:

• CU_GREEN_CTX_DEFAULT_STREAM : Creates a default stream to use inside the green context. Required.

See also:

cuGreenCtxDestroy, cuCtxFromGreenCtx, cuCtxSetCurrent, cuCtxPushCurrent, cuDevResourceGenerateDesc, cuDevicePrimaryCtxRetain, cuCtxCreate

Destroys a green context.

Parameters

hCtx

- Green context to be destroyed

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_CONTEXT, CUDA_ERROR_CONTEXT_IS_DESTROYED

Description

Destroys the green context, releasing the primary context of the device that this green context was created for. Any resources provisioned for this green context (that were initially available via the resource descriptor) are released as well. The API does not destroy streams created via cuGreenCtxStreamCreate, cuStreamCreate, or cuStreamCreateWithPriority. Users are expected to destroy these streams explicitly using cuStreamDestroy to avoid resource leaks. Once the green context is destroyed, any subsequent API calls involving these streams will return CUDA_ERROR_STREAM_DETACHED with the exception of the following APIs:

• cuStreamDestroy.

Additionally, the API will invalidate all active captures on these streams.

See also:

cuGreenCtxCreate, cuCtxDestroy

Get green context resources.

Parameters

hCtx

- Green context to get resource for

resource

- Output pointer to a CUdevResource structure

type

- Type of resource to retrieve

Returns

CUDA_SUCCESSCUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_CONTEXT, CUDA_ERROR_INVALID_RESOURCE_TYPE, CUDA_ERROR_INVALID_VALUE

Description

Get the type resources available to the green context represented by hCtx

See also:

cuDevResourceGenerateDesc

Returns the unique Id associated with the green context supplied.

Parameters

greenCtx

- Green context for which to obtain the Id

greenCtxId

- Pointer to store the Id of the green context

Returns

CUDA_SUCCESS, CUDA_ERROR_CONTEXT_IS_DESTROYED, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_CONTEXT, CUDA_ERROR_INVALID_VALUE

Description

Returns in greenCtxId the unique Id which is associated with a given green context. The Id is unique for the life of the program for this instance of CUDA. If green context is supplied as NULL and the current context is set to a green context, the Id of the current green context is returned.

See also:

cuGreenCtxCreate, cuGreenCtxDestroy, cuCtxGetId

Records an event.

Parameters

hCtx

- Green context to record event for

hEvent

- Event to record

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_CONTEXT, CUDA_ERROR_INVALID_HANDLE, CUDA_ERROR_STREAM_CAPTURE_UNSUPPORTED

Description

Captures in hEvent all the activities of the green context of hCtx at the time of this call. hEvent and hCtx must be from the same primary context otherwise CUDA_ERROR_INVALID_HANDLE is returned. Calls such as cuEventQuery() or cuGreenCtxWaitEvent() will then examine or wait for completion of the work that was captured. Uses of hCtx after this call do not modify hEvent.

See also:

cuGreenCtxWaitEvent, cuEventRecord, cuCtxRecordEvent, cuCtxWaitEvent

Create a stream for use in the green context.

Parameters

phStream

- Returned newly created stream

greenCtx

- Green context for which to create the stream for

flags

- Flags for stream creation. CU_STREAM_NON_BLOCKING must be specified.

priority

- Stream priority. Lower numbers represent higher priorities. See cuCtxGetStreamPriorityRange for more information about meaningful stream priorities that can be passed.

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_CONTEXT, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_OUT_OF_MEMORY

Description

Creates a stream for use in the specified green context greenCtx and returns a handle in phStream. The stream can be destroyed by calling cuStreamDestroy(). Note that the API ignores the context that is current to the calling thread and creates a stream in the specified green context greenCtx.

The supported values for flags are:

• CU_STREAM_NON_BLOCKING: This must be specified. It indicates that work running in the created stream may run concurrently with work in the default stream, and that the created stream should perform no implicit synchronization with the default stream.

Specifying priority affects the scheduling priority of work in the stream. Priorities provide a hint to preferentially run work with higher priority when possible, but do not preempt already-running work or provide any other functional guarantee on execution order. priority follows a convention where lower numbers represent higher priorities. '0' represents default priority. The range of meaningful numerical priorities can be queried using cuCtxGetStreamPriorityRange. If the specified priority is outside the numerical range returned by cuCtxGetStreamPriorityRange, it will automatically be clamped to the lowest or the highest number in the range.

See also:

cuStreamDestroy, cuGreenCtxCreatecuStreamCreate, cuStreamGetPriority, cuCtxGetStreamPriorityRange, cuStreamGetFlags, cuStreamGetDevice, cuStreamWaitEvent, cuStreamQuery, cuStreamSynchronize, cuStreamAddCallback, cudaStreamCreateWithPriority

Make a green context wait on an event.

Parameters

hCtx

- Green context to wait

hEvent

- Event to wait on

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_CONTEXT, CUDA_ERROR_INVALID_HANDLE, CUDA_ERROR_STREAM_CAPTURE_UNSUPPORTED

Description

Makes all future work submitted to green context hCtx wait for all work captured in hEvent. The synchronization will be performed on the device and will not block the calling CPU thread. See cuGreenCtxRecordEvent() or cuEventRecord(), for details on what is captured by an event.

See also:

cuGreenCtxRecordEvent, cuStreamWaitEvent, cuCtxRecordEvent, cuCtxWaitEvent

Get stream resources.

Parameters

hStream

- Stream to get resource for

resource

- Output pointer to a CUdevResource structure

type

- Type of resource to retrieve

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_RESOURCE_TYPE, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_INVALID_HANDLE

Description

Get the type resources available to the hStream and store them in resource.

Note: The API will return CUDA_ERROR_INVALID_RESOURCE_TYPE is type is CU_DEV_RESOURCE_TYPE_WORKQUEUE_CONFIG or CU_DEV_RESOURCE_TYPE_WORKQUEUE.

See also:

cuGreenCtxCreate, cuGreenCtxStreamCreate, cuStreamCreate, cuDevSmResourceSplitByCount, cuDevResourceGenerateDesc, cudaStreamGetDevResource

Query the green context associated with a stream.

Parameters

hStream

- Handle to the stream to be queried

phCtx

- Returned green context associated with the stream

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_CONTEXT, CUDA_ERROR_INVALID_HANDLE,

Description

Returns the CUDA green context that the stream is associated with, or NULL if the stream is not associated with any green context.

The stream handle hStream can refer to any of the following:

• a stream created via any of the CUDA driver APIs such as cuStreamCreate, cuStreamCreateWithPriority and cuGreenCtxStreamCreate, or their runtime API equivalents such as cudaStreamCreate, cudaStreamCreateWithFlags and cudaStreamCreateWithPriority. If during stream creation the context that was active in the calling thread was obtained with cuCtxFromGreenCtx, that green context is returned in phCtx. Otherwise, *phCtx is set to NULL instead.

• special stream such as the NULL stream or CU_STREAM_LEGACY. In that case if context that is active in the calling thread was obtained with cuCtxFromGreenCtx, that green context is returned. Otherwise, *phCtx is set to NULL instead.

Passing an invalid handle will result in undefined behavior.

See also:

cuStreamDestroy, cuStreamCreate, cuStreamCreateWithPriority, cuStreamGetCtx, cuGreenCtxStreamCreate, cuStreamGetPriority, cuStreamGetFlags, cuStreamGetDevice, cuStreamWaitEvent, cuStreamQuery, cuStreamSynchronize, cuStreamAddCallback, cudaStreamCreate, cudaStreamCreateWithFlags