Zip Iterator

[victorjunaidy]

Add:

• zip iterator
• simple zip iterator example in host

Failed when building for accelerator testing

[SimeonEhrig]

Comment this line to skip the format check: https://github.com/alpaka-group/vikunja/blob/91028b1d408c773bcf6a72b2cc7830a590cc4d01/.gitlab-ci.yml#L36

[SimeonEhrig]

Please rebase on the current master. I removed C++ 14. Therefore, it is less to test.

[victorjunaidy]

Sorry for the delay, finally all checks have passed

[SimeonEhrig]

I see a conceptional problem in your implementation. If I understand it correctly, you pass a tuple of the begin pointers of each buffer (std::tuple<bufType1*, bufType2*, bufType3*>) to the constructor of the zip operator, which is fine. But the operator* returns the same type, which is not correct. Your operator* needs to return a tuple of single values and not the tuple of pointers. The implementation needs to be something like this:

std::tuple<bufType1, bufType2, bufType3> operator*(){
    return std::make_tuple(std::get<0>(m_iteratorTuple[m_index]), std::get<1>(m_iteratorTuple[m_index]), std::get<2>(m_iteratorTuple[index]));
}

std::tuple<bufType1, bufType2, bufType3> operator[](int i){
    return std::make_tuple(std::get<0>(m_iteratorTuple[i]), std::get<1>(m_iteratorTuple[i]), std::get<2>(m_iteratorTuple[i]));
}

I think, the main problem is to make it generic for an arbitrary number of tuple members.

I would also suggest, to test it first with deviceTransform. If you use deviceTransformReduce you have to care about the types of the functions. The return type of the transformation functor is the argument type of the reduce functor:

auto transform = [](Data1 input) -> Data2 { return static_cast<Data2>(input);};
auto reduce =  [](Data2 sum, Data2 input) -> Data2 { return sum + input;};

Also the reduce functor is restricted to a single type for the moment, see here: #52