ParallelTransformsCUDA

# Parallel Transforms

Include the Header

Include the Header

ParallelTransformsCUDA_1CUDAParallelTransformsIncludeTheHeader
Transform a Range of Items

Transform a Range of Items

ParallelTransformsCUDA_1cudaFlowTransformARangeOfItems
Transform Two Ranges of Items

Transform Two Ranges of Items

ParallelTransformsCUDA_1cudaFlowTransformTwoRangesOfItems
Miscellaneous Items

Miscellaneous Items

ParallelTransformsCUDA_1ParallelTransformCUDAMiscellaneousItems

tf::cudaFlow provides template methods for transforming ranges of items to different outputs.

# Include the Header

You need to include the header file, `taskflow/cuda/algorithm/transform.hpp`, for creating a parallel-transform task.

    #include<taskflow/cuda/algorithm/transform.hpp>

# Transform a Range of Items

Iterator-based parallel-transform applies the given transform function to a range of items and store the result in another range specified by two iterators, `first` and `last`. The task created by tf::cudaFlow::transform(I first, I last, O output, C op) represents a parallel execution for the following loop:

    while(first!=last){
    *output++=op(*first++);
    }

The following example creates a transform kernel that transforms an input range of `N` items to an output range by multiplying each item by 10.

    //output[i]=input[i]*10
    cudaflow.transform(
    input,input+N,output,[]__device__(intx){returnx*10;}
    );

Each iteration is independent of each other and is assigned one kernel thread to run the callable. Since the callable runs on GPU, it must be declared with a `__device__` specifier.

# Transform Two Ranges of Items

You can transform two ranges of items to an output range through a binary operator. The task created by tf::cudaFlow::transform(I1 first1, I1 last1, I2 first2, O output, C op) represents a parallel execution for the following loop:

    while(first1!=last1){
    *output++=op(*first1++,*first2++);
    }

The following example creates a transform kernel that transforms two input ranges of `N` items to an output range by summing each pair of items in the input ranges.

    //output[i]=input1[i]+inpu2[i]
    cudaflow.transform(
    input1,input1+N,input2,output,[]__device__(inta,intb){returna+b;}
    );

# Miscellaneous Items

The parallel-transform algorithms are also available in tf::cudaFlowCapturer.