Description

The __kernel qualifier can be used with the keyword attribute to declare additional information about the kernel function as described below.

The optional __attribute__((vec_type_hint(<type>)))24 is a hint to the compiler and is intended to be a representation of the computational width of the __kernel, and should serve as the basis for calculating processor bandwidth utilization when the compiler is looking to autovectorize the code. In the __attribute__((vec_type_hint(<type>))) qualifier <type> is one of the built-in vector types listed in https://www.khronos.org/registry/OpenCL/specs/2.2/html/OpenCL_C.html#table-builtin-vector-types or the constituent scalar element types. If vec_type_hint (<type>) is not specified, the kernel is assumed to have the __attribute__((vec_type_hint(int))) qualifier.

[24] Implicit in autovectorization is the assumption that any libraries called from the __kernel must be recompilable at run time to handle cases where the compiler decides to merge or separate workitems. This probably means that such libraries can never be hard coded binaries or that hard coded binaries must be accompanied either by source or some retargetable intermediate representation. This may be a code security question for some.

For example, where the developer specified a width of float4, the compiler should assume that the computation usually uses up to 4 lanes of a float vector, and would decide to merge work-items or possibly even separate one work-item into many threads to better match the hardware capabilities. A conforming implementation is not required to autovectorize code, but shall support the hint. A compiler may autovectorize, even if no hint is provided. If an implementation merges N work-items into one thread, it is responsible for correctly handling cases where the number of global or local work-items in any dimension modulo N is not zero.

Examples:

// autovectorize assuming float4 as the
// basic computation width
__kernel __attribute__((vec_type_hint(float4)))
void foo( __global float4 *p ) { ... }

// autovectorize assuming double as the
// basic computation width
__kernel __attribute__((vec_type_hint(double)))
void foo( __global float4 *p ) { ... }

// autovectorize assuming int (default)
// as the basic computation width
__kernel
void foo( __global float4 *p ) { ... }

If for example, a __kernel function is declared with

__attribute__(( vec_type_hint (float4)))

(meaning that most operations in the __kernel function are explicitly vectorized using float4) and the kernel is running using Intel® Advanced Vector Instructions (Intel® AVX) which implements a 8-float-wide vector unit, the autovectorizer might choose to merge two work-items to one thread, running a second work-item in the high half of the 256-bit AVX register.

As another example, a Power4 machine has two scalar double precision floating-point units with an 6-cycle deep pipe. An autovectorizer for the Power4 machine might choose to interleave six kernels declared with the __attribute__(( vec_type_hint (double2))) qualifier into one hardware thread, to ensure that there is always 12-way parallelism available to saturate the FPUs. It might also choose to merge 4 or 8 work-items (or some other number) if it concludes that these are better choices, due to resource utilization concerns or some preference for divisibility by 2.

The optional __attribute__((work_group_size_hint(X, Y, Z))) is a hint to the compiler and is intended to specify the work-group size that may be used i.e. value most likely to be specified by the local_work_size argument to clEnqueueNDRangeKernel. For example, the __attribute__((work_group_size_hint(1, 1, 1))) is a hint to the compiler that the kernel will most likely be executed with a work-group size of 1.

The optional __attribute__((reqd_work_group_size(X, Y, Z))) is the work-group size that must be used as the local_work_size argument to clEnqueueNDRangeKernel. This allows the compiler to optimize the generated code appropriately for this kernel.

If Z is one, the work_dim argument to clEnqueueNDRangeKernel can be 2 or 3. If Y and Z are one, the work_dim argument to clEnqueueNDRangeKernel can be 1, 2 or 3.

The optional __attribute__((nosvm)) qualifier can be used with a pointer variable to inform the compiler that the pointer does not refer to a shared virtual memory region.

__attribute__((nosvm)) is deprecated, and the compiler can ignore it.

See Also

Document Notes

For more information, see the OpenCL C Specification

This page is extracted from the OpenCL C Specification. Fixes and changes should be made to the Specification, not directly.

Copyright (c) 2014-2020 Khronos Group. This work is licensed under a Creative Commons Attribution 4.0 International License.