clEnqueueNDRangeKernel

Enqueues a command to execute a kernel on a device.

`cl_int clEnqueueNDRangeKernel (`	cl_command_queue `command_queue`,
	cl_kernel `kernel`,
	cl_uint `work_dim`,
	const size_t `*global_work_offset`,
	const size_t `*global_work_size`,
	const size_t `*local_work_size`,
	cl_uint `num_events_in_wait_list`,
	const cl_event `*event_wait_list`,
	cl_event `*event)`

Parameters

command_queue

A valid host command-queue. The kernel will be queued for execution on the device associated with command_queue.

kernel

A valid kernel object. The OpenCL context associated with kernel and command_queue must be the same.

work_dim

The number of dimensions used to specify the global work-items and work-items in the work-group. work_dim must be greater than zero and less than or equal to CL_DEVICE_MAX_WORK_ITEM_DIMENSIONS.

global_work_offset

global_work_offset can be used to specify an array of work_dim unsigned values that describe the offset used to calculate the global ID of a work-item. If global_work_offset is NULL, the global IDs start at offset (0, 0, ... 0).

global_work_size

Points to an array of work_dim unsigned values that describe the number of global work-items in work_dim dimensions that will execute the kernel function. The total number of global work-items is computed as global_work_size[0] *...* global_work_size[work_dim - 1].

local_work_size

Points to an array of work_dim unsigned values that describe the number of work-items that make up a work-group (also referred to as the size of the work-group) that will execute the kernel specified by kernel. The total number of work-items in a work-group is computed as local_work_size[0] *... * local_work_size[work_dim - 1]. The total number of work-items in the work-group must be less than or equal to the CL_DEVICE_MAX_WORK_GROUP_SIZE value specified in table of OpenCL Device Queries for clGetDeviceInfo and the number of work-items specified in local_work_size[0],... local_work_size[work_dim - 1] must be less than or equal to the corresponding values specified by CL_DEVICE_MAX_WORK_ITEM_SIZES[0],.... CL_DEVICE_MAX_WORK_ITEM_SIZES[work_dim - 1]. The explicitly specified local_work_size will be used to determine how to break the global work-items specified by global_work_size into appropriate work-group instances. The values in local_work_size need not evenly divide the global_work_size in any dimension. In this case, any single dimension for which the global size is not divisible by the local size will be partitioned into two regions. One region will have workgroups that have the same number of work items as was specified by the local size parameter in that dimension. The other region will have work-groups with less than the number of work items specified by the local size parameter in that dimension. The global IDs and group IDs of the work items in the first region will be numerically lower than those in the second, and the second region will be at most one work-group wide in that dimension. Workgroup sizes could be non-uniform in multiple dimensions, potentially producing work-groups of up to 4 different sizes in a 2D range and 8 different sizes in a 3D range.

If local_work_size is NULL, the OpenCL runtime is free to implement the ND-range using uniform or non-uniform work-group sizes, regardless of the divisibility of the global work size. If the ND-range is implemented using non-uniform work-group sizes, the work-group sizes, global IDs and group IDs will follow the same pattern as described in above paragraph.

The work-group size to be used for kernel can also be specified in the program source using the __attribute__ ((reqd_work_group_size(X, Y, Z))) qualifier. In this case the size of work group specified by local_work_size must match the value specified by the reqd_work_group_size __attribute__ qualifier.

These work-group instances are executed in parallel across multiple compute units or concurrently on the same compute unit.

Each work-item is uniquely identified by a global identifier. The global ID, which can be read inside the kernel, is computed using the value given by global_work_size and global_work_offset. In addition, a work-item is also identified within a work-group by a unique local ID. The local ID, which can also be read by the kernel, is computed using the value given by local_work_size. The starting local ID is always (0, 0, ... 0).

event_wait_list and num_events_in_wait_list

Specify events that need to complete before this particular command can be executed. If event_wait_list is NULL, then this particular command does not wait on any event to complete. If event_wait_list is NULL, num_events_in_wait_list must be 0. If event_wait_list is not NULL, the list of events pointed to by event_wait_list must be valid and num_events_in_wait_list must be greater than 0. The events specified in event_wait_list act as synchronization points. The context associated with events in event_wait_list and command_queue must be the same. The memory associated with event_wait_list can be reused or freed after the function returns.

event

Returns an event object that identifies this particular kernel execution instance. Event objects are unique and can be used to identify a particular kernel execution instance later on. If event is NULL, no event will be created for this kernel execution instance and therefore it will not be possible for the application to query or queue a wait for this particular kernel execution instance. If the event_wait_list and the event arguments are not NULL, the event argument should not refer to an element of the event_wait_list array.

Errors

Returns CL_SUCCESS if the kernel execution was successfully queued. Otherwise, it returns one of the following errors:

CL_INVALID_PROGRAM_EXECUTABLE if there is no successfully built program executable available for device associated with command_queue.
CL_INVALID_COMMAND_QUEUE if command_queue is not a valid host command-queue.
CL_INVALID_KERNEL if kernel is not a valid kernel object.
CL_INVALID_CONTEXT if context associated with command_queue and kernel is not the same or if the context associated with command_queue and events in event_wait_list are not the same.
CL_INVALID_KERNEL_ARGS if the kernel argument values have not been specified or if a kernel argument declared to be a pointer to a type does not point to a named address space.
CL_INVALID_WORK_DIMENSION if work_dim is not a valid value (i.e. a value between 1 and 3).
CL_INVALID_GLOBAL_WORK_SIZE if global_work_size is NULL, or if any of the values specified in global_work_size[0], ...global_work_size [work_dim - 1] are 0 or exceed the range given by the sizeof(size_t) for the device on which the kernel execution will be enqueued.
CL_INVALID_GLOBAL_OFFSET if the value specified in global_work_size + the corresponding values in global_work_offset for any dimensions is greater than the sizeof(size_t) for the device on which the kernel execution will be enqueued.
CL_INVALID_WORK_GROUP_SIZE if local_work_size is specified and does not match the work-group size for kernel in the program source given by the __attribute__ ((reqd_work_group_size(X, Y, Z))) qualifier.
CL_INVALID_WORK_GROUP_SIZE if local_work_size is specified and the total number of work-items in the work-group computed as local_work_size[0] * … local_work_size[work_dim – 1] is greater than the value specified by CL_DEVICE_MAX_WORK_GROUP_SIZE in the table of OpenCL Device Queries for clGetDeviceInfo.
CL_INVALID_WORK_GROUP_SIZE if local_work_size is NULL and the __attribute__ ((reqd_work_group_size(X, Y, Z))) qualifier is used to declare the work-group size for kernel in the program source.
CL_INVALID_WORK_ITEM_SIZE if the number of work-items specified in any of local_work_size[0], ... local_work_size[work_dim - 1] is greater than the corresponding values specified by CL_DEVICE_MAX_WORK_ITEM_SIZES[0], .... CL_DEVICE_MAX_WORK_ITEM_SIZES[work_dim - 1].
CL_INVALID_WORK_GROUP_SIZE if the program was compiled with –cl-uniform-work-group-size and the number of work-items specified by global_work_size is not evenly divisible by size of work-group given by local_work_size.
CL_INVALID_WORK_ITEM_SIZE if the number of work-items specified in any of local_work_size[0], ... local_work_size[work_dim – 1] is greater than the corresponding values specified by CL_DEVICE_MAX_WORK_ITEM_SIZES[0], ... CL_DEVICE_MAX_WORK_ITEM_SIZES[work_dim – 1].
CL_MISALIGNED_SUB_BUFFER_OFFSET if a sub-buffer object is specified as the value for an argument that is a buffer object and the offset specified when the sub-buffer object is created is not aligned to CL_DEVICE_MEM_BASE_ADDR_ALIGN value for device associated with queue.
CL_INVALID_IMAGE_SIZE if an image object is specified as an argument value and the image dimensions (image width, height, specified or compute row and/or slice pitch) are not supported by device associated with queue.
CL_IMAGE_FORMAT_NOT_SUPPORTED if an image object is specified as an argument value and the image format (image channel order and data type) is not supported by device associated with queue.
CL_OUT_OF_RESOURCES if there is a failure to queue the execution instance of kernel on the command-queue because of insufficient resources needed to execute the kernel. For example, the explicitly specified local_work_size causes a failure to execute the kernel because of insufficient resources such as registers or local memory. Another example would be the number of read-only image args used in kernel exceed the CL_DEVICE_MAX_READ_IMAGE_ARGS value for device or the number of write-only image args used in kernel exceed the CL_DEVICE_MAX_READ_WRITE_IMAGE_ARGS value for device or the number of samplers used in kernel exceed CL_DEVICE_MAX_SAMPLERS for device.
CL_MEM_OBJECT_ALLOCATION_FAILURE if there is a failure to allocate memory for data store associated with image or buffer objects specified as arguments to kernel.
CL_INVALID_EVENT_WAIT_LIST if event_wait_list is NULL and num_events_in_wait_list > 0, or event_wait_list is not NULL and num_events_in_wait_list is 0, or if event objects in event_wait_list are not valid events.
CL_INVALID_OPERATION if SVM pointers are passed as arguments to a kernel and the device does not support SVM or if system pointers are passed as arguments to a kernel and/or stored inside SVM allocations passed as kernel arguments and the device does not support fine grain system SVM allocations.
CL_OUT_OF_RESOURCES if there is a failure to allocate resources required by the OpenCL implementation on the device.
CL_OUT_OF_HOST_MEMORY if there is a failure to allocate resources required by the OpenCL implementation on the host.

Specification

OpenCL Specification

Also see

clCreateCommandQueueWithProperties, clGetDeviceInfo, clEnqueueNativeKernel, Work-Item Functions

Copyright © 2007-2013 The Khronos Group Inc. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and/or associated documentation files (the "Materials"), to deal in the Materials without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Materials, and to permit persons to whom the Materials are furnished to do so, subject to the condition that this copyright notice and permission notice shall be included in all copies or substantial portions of the Materials.