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From Luciano Resende <luckbr1...@gmail.com>
Subject Re: [Discuss} SystemML Roadmap page
Date Tue, 27 Sep 2016 00:33:15 GMT
Feel free to provide a PR to the website repo, and I will merge with the
new design in a few days when i am done with refactors.

On Monday, September 26, 2016, Acs S <acs_s@yahoo.com.invalid> wrote:

> +1
> Probably following line should remove future from it:   Planned for future
> SystemML 1.0
>
> Lets get this published on SystemML website soon.
> -Arvind
>
>       From: Deron Eriksson <deroneriksson@gmail.com <javascript:;>>
>  To: dev@systemml.incubator.apache.org <javascript:;>
>  Sent: Friday, September 23, 2016 12:49 PM
>  Subject: Re: [Discuss} SystemML Roadmap page
>
> +1
>
> Great idea, Berthold. Adding a roadmap to the project will be a very
> welcome addition to the project, both for users and developers.
>
> Deron
>
>
> On Fri, Sep 23, 2016 at 12:10 PM, Berthold Reinwald <reinwald@us.ibm.com
> <javascript:;>>
> wrote:
>
> > In the spirit of other Apache projects, we should publish a Roadmap page.
> > The page should be clear on the immediate timeline, point to some future
> > projects, and also summarize the past to demonstrate continuum. It is not
> > a replacement for jiras or release notes, but just a single place for
> > people to go to and see what happened in the past and what will happen
> > going forward.
> >
> >
> > SystemML Roadmap
> >
> >
> > SystemML Release Timeline
> > =========================
> >
> > Oct. 2016: SystemML 0.11.0 on Spark 1.x
> >
> > Nov. 2016: SystemML 0.11.1 on Spark 1.x/2.x
> >
> > Dec. 2016: SystemML 1.0 on Spark 1.x/2.x
> >
> >
> > Next SystemML 0.11.x
> > --------------------
> > - Features
> >  -- SystemML frames
> >  -- New MLContext API
> >  -- Transform functions based on SystemML frames
> > - Bug fixes
> > - Experimental Features / algorithms
> >  -- New built-in functions for deep learning (convolution and pooling)
> >  -- Deep learning library (DML bodied functions)
> >  -- Python DSL integration
> >  -- GPU support
> >  -- Compressed Linear Algebra
> >  -- New Algorithms
> >      --- Lasso
> >      --- kNN
> >      --- Lanczos
> >      --- PPCA
> >      --- Deep Learning: CNN (Lenet), RBM
> >
> >
> > Planned for future SystemML 1.0
> > -------------------------------
> > - Rigorous performance and scalability testing (bug fixes)
> > - Remove deprecated APIs
> > - Remove deprecated functions
> >
> >
> > Planned for future Releases
> > ---------------------------
> > - Completion of prior experimental features
> > - New algorithms: Non-linear SVMs, solvers, decomposition, inversion,
> etc.
> > - DSLs (e.g. Scala, Python) and common DSL architecture
> > - R interfaces: R DSL and R wrappers
> > - Native Zeppelin Notebook support
> > - Code generation
> > - Sum product optimizations
> > - Tree-based data structures
> > - Global dataflow optimizations
> >
> >
> > Prior Releases
> > ==============
> >
> >
> > SystemML 0.10.0-incubating (released in June, 2016) (link to release
> notes
> > (
> > https://github.com/apache/incubator-systemml-website/
> > blob/master/0.10.0-incubating/release_notes.md
> > ))
> > --------------------------
> > - Different types of Spark Matrix Blocks: MCSR, CSR, COO
> > - SystemML Frame support in JMLC/CP
> > - Initial Deep Learning support
> > - API/Scripts: parser error handling, SystemML configuration handling,
> > include algorithms in SystemML jar, print matrix
> > - New fused operator: wdivmm with variations
> > - Performance Features: cache-conscious operations, more multithreaded
> > operations, new simplications rewrites
> > - New Algorithms: kNN
> > - Documentation: javadocs, Jupyter/Zeppeling notebook examples
> >
> >
> > SystemML 0.9.0-incubating (released in Jan. 2016) (link to release notes
> (
> > https://github.com/apache/incubator-systemml-website/
> > blob/master/0.9.0-incubating/release_notes.md
> > ))
> > -------------------------
> > - Improvements to MLContext and MLPipeline wrappers
> > - New converter utilities for RDDs and DataFrames)
> > - New Optimizations for Spark Backend, e.g. eager RDD caching and
> > repartitioning, RDD checkpointing, on-demand creation of SparkContext
> > - New Runtime Operators for mmult, multihreaded readers and operators.
> > - New Algoriths: ALS, Cubic Splines
> > - Online documentation
> >
> >
> > Regards,
> > Berthold Reinwald
> > IBM Almaden Research Center
> > office: (408) 927 2208; T/L: 457 2208
> > e-mail: reinwald@us.ibm.com <javascript:;>
> >
> >
>
>
>



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