Also, Rasmus if you are interested, I can provide some use cases that would be well suited to additional vectorization. Not sure if I can peer too deeply into the internals of Eigen, but I'm happy to help around the margins.
On Mon, May 10, 2021 at 8:09 PM Ian Bell <[email protected]> wrote: > Rasmus, your commits are these, right: > > > https://gitlab.com/libeigen/eigen/-/commit/88d4c6d4c870f53d129ab5f8b43e01812d9b500e > > https://gitlab.com/libeigen/eigen/-/commit/be0574e2159ce3d6a1748ba6060bea5dedccdbc9 > > Which Array methods pick up these new packet methods? > > On Mon, May 10, 2021 at 7:53 PM Rasmus Munk Larsen <[email protected]> > wrote: > >> I recently vectorized the implementation of pow in Eigen for float and >> double arguments. It does not apply to pow(float, int), however, but >> should give you a significant speedup if you cast your exponents to >> double. I thought about implementing a more efficient algorithm if the >> exponents are all integers, but didn't get round to it. Could you >> please try if this helps you? The improvements are in the master >> branch (as well as the 3.4 branch that we are preparing for release). >> >> On Mon, May 10, 2021 at 4:28 PM Marc Glisse <[email protected]> wrote: >> > >> > On Mon, 10 May 2021, Ian Bell wrote: >> > >> > > Of course, shortly after having sent this message I figured it out, >> but it >> > > doesn't actually result in an increase in my throughput sadly. For >> > > posterity: >> > > >> > > #include <Eigen/Dense> >> > > #include <iostream> >> > > >> > > using namespace Eigen; >> > > >> > > struct myUnaryFunctor { >> > > const double m_base; >> > > myUnaryFunctor(double base): m_base(base) {}; >> > > typedef double result_type; >> > > result_type operator()(const int &e) const >> > > { >> > > return pow(m_base, e); >> > > } >> > > }; >> > > >> > > int main() >> > > { >> > > auto e = Eigen::ArrayXi::LinSpaced(11, 0, 10).eval(); >> > > double base = 2.9; >> > > std::cout << e.unaryExpr(myUnaryFunctor(base)); >> > > } >> > >> > Assuming pow is actually your own function and does the usual repeated >> > squaring, unlike std::pow, this may do a lot of redundant computation >> (in >> > particular base*base is computed many times). Do you know anything about >> > the integers? In particular, are they always small? I assume the >> LinSpaced >> > example doesn't look like the true data. Does your pow function already >> > cache some results? >> > >> > -- >> > Marc Glisse >> > >> > >> >> >>
