Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

LFortran: Modern interactive LLVM-based Fortran compiler

lfortran.org

Post reply on HN
Print view View original

11–20 of 73 posts

Re: LFortran: Modern interactive LLVM-based Fortran compiler

#11

Post by kergonath »

waynecochran wrote: post #8

I use C++ Eigen extensively. I wonder if it feasible to write a C++ programs that hands off blocks of linear algebra code to Fortran subroutines. Eigen does a wonderful job of late binding and lazy evaluation so that something like the following is fairly efficient: (L.transpose() * P).diagonal().array().square().mean(); which computes the squared average of column by column dot products between matrices L and P. I a…

If you use LAPACK there’s a chance that some Fortran code will be run at some point. For example OpenBLAS does it behind the scenes of you give it a matrix to diagonalise.

Re: LFortran: Modern interactive LLVM-based Fortran compiler

#13

Post by celrod »

waynecochran wrote: post #8

I use C++ Eigen extensively. I wonder if it feasible to write a C++ programs that hands off blocks of linear algebra code to Fortran subroutines. Eigen does a wonderful job of late binding and lazy evaluation so that something like the following is fairly efficient: (L.transpose() * P).diagonal().array().square().mean(); which computes the squared average of column by column dot products between matrices L and P. I a…

I think Eigen's template strategy is probably hard to beat from the perspective of combining operations. How well Fortran does is probably mostly up to the compiler implementation. In some of my benchmarks, gfortran sometimes seems to fuse the operations and end up much slower than if it has performed them separately in succession, but I wouldn't be surprised if compiling with `-fexternal-blas` (and linking MKL) would've solved that.

If you want to try external BLAS/LAPACK with Eigen, I'd look at: https://eigen.tuxfamily.org/dox/TopicUsingBlasLapack.html

I have `A * B`, `A * B'`, `A' * B` and `A' * B'` small-single-threaded-matmul benchmarks here: https://chriselrod.github.io/LoopVectorization.jl/latest/exa... I compared triple nested loops with Clang, icc, ifort, gfortran, Julia, and LoopVectorization.jl with matmul routines from ifort, gfortran, OpenBLAS, MKL, and Eigen.

While gfortran's builtin hit over 40 GFLOPS with `A * B` and `A' * B'`, it failed to get half that if only one argument was transposed. I'm supposed awkward fusing at the start of this post because if it had done one after the other, it should have still hit >40 GFLOPS when only 1 matrix was transposed.

Re: LFortran: Modern interactive LLVM-based Fortran compiler

#15

Post by dang »

kergonath wrote: post #12
dang wrote: post #10

If curious see also 2019 https://news.ycombinator.com/item?id=19795262 https://news.ycombinator.com/item?id=19788526

These are very interesting discussions. I don’t know how I managed to miss them when I submitted...

The cutoff point for reposts is about a year, so it's good that you didn't see them and then not post.

https://news.ycombinator.com/newsfaq.html

Re: LFortran: Modern interactive LLVM-based Fortran compiler

#16

Post by kergonath »

celrod wrote: post #13
waynecochran wrote: post #8

I use C++ Eigen extensively. I wonder if it feasible to write a C++ programs that hands off blocks of linear algebra code to Fortran subroutines. Eigen does a wonderful job of late binding and lazy evaluation so that something like the following is fairly efficient: (L.transpose() * P).diagonal().array().square().mean(); which computes the squared average of column by column dot products between matrices L and P. I a…

I think Eigen's template strategy is probably hard to beat from the perspective of combining operations. How well Fortran does is probably mostly up to the compiler implementation. In some of my benchmarks, gfortran sometimes seems to fuse the operations and end up much slower than if it has performed them separately in succession, but I wouldn't be surprised if compiling with `-fexternal-blas` (and linking MKL) woul…

These benchmarks are very interesting! From my experience gfortran’s MATMUL is very good for small matrices, but OpenBLAS gets better from ~10x10 elements. Not quite sure that’s the same as your benchmark; its colour code is a bit confusing. Would you mind making the data available?

Certainly, gfortran’s default implementation works well as a quick and easy solution for small vectors and matrices outside of hot paths. Also, I remember discussions about improving matmul(transpose(A),B) somewhat recently. I don’t remember for which version it was, but it’s the sort of things that is improved regularly.

I would love an option to align arrays in gfortran. It’s very important to take advantage of automatic vectorisation but I haven’t found a reliable way to do it.

Re: LFortran: Modern interactive LLVM-based Fortran compiler

#17

Post by kergonath »

dng88 wrote: post #14

Wish lisp have these like jupyter integration. And my first computer lecture many decades ago is really about how he hated fortran and why FORTRAN is still not dead (Mainly negative view due to haveGOTO that time). And it is still not dead.

To be fair, it does not look much like it was many decades ago.

Re: LFortran: Modern interactive LLVM-based Fortran compiler

#19

Post by adamnemecek »

waynecochran wrote: post #8

I use C++ Eigen extensively. I wonder if it feasible to write a C++ programs that hands off blocks of linear algebra code to Fortran subroutines. Eigen does a wonderful job of late binding and lazy evaluation so that something like the following is fairly efficient: (L.transpose() * P).diagonal().array().square().mean(); which computes the squared average of column by column dot products between matrices L and P. I a…

You can do this with Julia. Julia has an insanely good interop with essentially any language you can name, including cpp and Fortran. You will go through julia but hey, for linear algebra it's the shit.

Re: LFortran: Modern interactive LLVM-based Fortran compiler

#20

Post by mmaul »

dng88 wrote: post #14

Wish lisp have these like jupyter integration. And my first computer lecture many decades ago is really about how he hated fortran and why FORTRAN is still not dead (Mainly negative view due to haveGOTO that time). And it is still not dead.

Common Lisp has had Jupyter integration for a while.

First cl-jupyter (https://github.com/fredokun/cl-jupyter) which is now in maintance mode and now common-lisp-jupyter (https://github.com/yitzchak/common-lisp-jupyter).

Here is a notebook I did awhile back with cl-jupyter: https://github.com/mmaul/clml.tutorials/blob/master/CLML-Win...

Post reply on HN