Re: [eigen] New project using Eigen

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This project is indeed aims to be feature rich, scalable, and tuned. It is a cooperation between The HDFGroup: (mostly but not only)Gerd Heber and I.

If i missed some features, datastructures please let me know.
Also in the next version i am adding sparse and tensor support: if anyone would like to discuss this would be great. 

Best:
Steve

On Thu., Mar. 26, 2020, 13:21 Wood, Tobias, <tobias.wood@xxxxxxxxx> wrote:

Oh! This looks very interesting - I'm currently using the old HDF5 C++ libraries and they are a pain. I will be testing this ASAP.

 

Thanks for highlighting.

 

From: Steven Varga <steven.varga@xxxxxxxxx>
Reply to: "eigen@xxxxxxxxxxxxxxxxxxx" <eigen@xxxxxxxxxxxxxxxxxxx>
Date: Thursday, 26 March 2020 at 12:27
To: "eigen@xxxxxxxxxxxxxxxxxxx" <eigen@xxxxxxxxxxxxxxxxxxx>
Subject: [eigen] New project using Eigen

 

Hello,

 

This is a request to list H5CPP as an eigen3 related project.

 

H5CPP is a novel approach to persistence in the field of machine learning, it provides high performance sequential and block access to HDF5 containers through modern C++, In this specific case Eigen3::Array<...> and Eigen3::Matrix<....>; 

Arbitrary deep POD types are handled via LLVM based compiler assisted reflection resulting in mechanism similar to interpreted languages -- without trade offs. H5CPP was introduced in 2018 Chicago C++ User Group Meetup; has been presented on ISC'19 BOF thanks to HDFGroup sponsorship, it is continuously developed and works with major C++ compilers: Intel DPC++ v2021(beta), Intel 19.1.0.166, g++-7, g++-8, g++-9, clang++-6.0, clang++-7, clang++-8, clang++-9, clang++-10

 

author: steven varga (vargaconsulting.ca)

project name: H5CPP

 



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