Roadmap Shogun 2015 hack

Heiko Strathmann edited this page Feb 28, 2015 · 25 revisions

Shogun hack 2015 Ideas

This is a list of topics to address when all Shogun developers get together. We aim to have a structured list of items, with links to existing or newly created github issues. Feel free to merge this with content from the other Wiki pages or discussions.

Usability.

  • A meta-langauge for Shogun example: #2508.
  • Website updates (Kevin had some ideas?)
  • Developer information (wiki or website?) #2533
  • Manifest "What is Shogun? What tries Shogun to be?"
  • Notebooks of things that are not yet covered
  • Binary packages for various OS
  • Ubuntu LTS #2520
  • OSX #2521
  • Improve [Shogun development guidelines](Shogun development guidelines)
  • Scheduling a separate release for "easier installation": packages and scripts for Ubuntu/Debian/MacOSC https://github.com/shogun-toolbox/shogun/milestones/Shogun%203.4.1

Efficiency & Clean-ups

Computing Backends.

  • Parallelism backend interface
  • Batch cluster backend (PBS/SGE,SLURM,etc) #1622
  • Pthread/openMP backend #1623
  • Director classes to use Shogun as scheduler from modular interface #1624
  • Add dependencies between jobs #2524
  • Graphlab backend #2525
  • Zookeeper coordination?
  • Populate internal Linear algebra interface
  • Add matrix factorisations #2526
  • Add linear solves #2527
  • Stan for autodiff and MCMC #1875 #1998 #1929
  • Vowpal Wabbit update

SHOGUN goes large-scale

  • Investigate how non-toy examples scale in SHOGUN.
  • Increase awareness of benchmarking and profiling:
  • Identify hotspots using selected examples and right tools (gprof?).
  • Create minimal example(s!) which covers hotspot and benchmark.
  • Start optimizing minimal example(s!) and benchmark again.
  • Developers should know how to benchmark and profile: Small document to describe this?
  • If you know examples that scale better in other frameworks, please document them here, so we can investigate:
  • ...
  • Better support of sparse-datastructures and online-algorithms.
  • Interface with MOE for better model selection
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