min
Contents
min#
Entry point to compute min values.
Description and Assumptions
The oneapi::mkl::stats::min function is used to compute min arrays (min value for each dataset’s dimension).
min supports the following precisions for data:
T
float
double
min (buffer version)#
Syntax
namespace oneapi::mkl::stats {
template<method Method = fast, typename Type, layout ObservationsLayout>
void min(sycl::queue& queue,
const dataset<ObservationsLayout, sycl::buffer<Type, 1>>& data,
sycl::buffer<Type, 1> min);
}
Template Parameters
- Method
Method which is used for estimate computation. The specific values are as follows:
oneapi::mkl::stats::method::fast
- Type
Data precision.
- ObservationsLayout
Data layout. The specific values are described in dataset.
Input Parameters
- queue
The queue where the routine should be executed.
- data
Dataset which is used for computation.
Output Parameters
- min
sycl::buffer array of min values.
Throws
- oneapi::mkl::invalid_argument
Exception is thrown when min.get_count() == 0, or dataset object is invalid
min (USM version)#
Syntax
namespace oneapi::mkl::stats {
template<method Method = fast, typename Type, layout ObservationsLayout>
sycl::event min(sycl::queue& queue,
const dataset<ObservationsLayout, Type*>& data,
Type* min,
const std::vector<sycl::event> &dependencies = {});
}
Template Parameters
- Method
Method which is used for estimate computation. The specific values are as follows:
oneapi::mkl::stats::method::fast
- Type
Data precision.
- ObservationsLayout
Data layout. The specific values are described in dataset.
Input Parameters
- queue
The queue where the routine should be executed.
- data
Dataset which is used for computation.
- dependencies
Optional parameter. List of events to wait for before starting computation, if any.
Output Parameters
- min
Pointer to the array of min values.
Throws
- oneapi::mkl::invalid_argument
Exception is thrown when min == nullptr, or dataset object is invalid
Return Value
Output event to wait on to ensure computation is complete.
Parent topic: Summary Statistics Routines