Author Archives: Julia Developers

JuliaCon 2015 Preview – Deep Learning, 3D Printing, Parallel Computing, and so much more

By: Julia Developers

Re-posted from: http://feedproxy.google.com/~r/JuliaLang/~3/z-Evw2AMzvU/juliacon-preview

JuliaCon 2015 is being held at the Massachusetts Institute of Technology from June 24th to the 28th. Get your tickets and book your hotel before June 4th to take advantage of early bird pricing.


The first ever JuliaCon was held in Chicago last year and was a great success. JuliaCon is back for 2015, this time in Cambridge, Massachusetts at MIT’s architecturally-delightful Stata Center, the home of computer science at MIT. Last year we had a single-track format, but this year we’ve expanded into a four-day extravaganza:
* On Wednesday 24th there will an introduction to Julia workshop run by David P. Sanders (@dpsanders) as well as a Julia hackathon – a great chance to get some help for your new Julia projects, or to begin contributing to Julia or its many packages.
* On Thursday 25th and Friday 26th we will be having speakers talking about a range of topics – we were fortunate to have so many fantastic submissions that we had to open up a second track of talks. The near-final schedule is on the main page. We’ll be alternating between ~40 minute long “regular” talks, and ~10 minute long “lightning” talks across all the sessions.
* On Saturday 27th we will finish with a series of workshops on a range of topics: data wrangling and visualization, optimization, high-performance computing and more. These workshops run from 1.5 to 3 hours and will be a great way to rapidly boost your Julia skills.

Thursday’s Talks

After getting everyone settled in, we’ll start the conference proper with a session about the use of Julia in a wide variety of scientific applications. Many of the talks at the conference focus on Julia package organizations: groupings of similar packages that promote interoperability and focussing of efforts. In the session Daniel C. Jones (@dcjones), the creator of the visualization package Gadfly, will discuss the advances being made in the BioJulia bioinformatics organization, and Kyle Barbary (@kbarbary) will present JuliaAstro, a home for astronomy and astrophysics packages. Theres something for everyone: quantitative economic modeling (QuantEcon.jl), quantum statistical simulations, and how to fit Julia into a pre-existing body of code in other languages.

After lunch we’ll be splitting into two tracks: visualization and interactivity and statistics. The visualization track will be demonstrating some of the exciting advances being made that enable Julia to both produce high-quality visualizations, but also share them. Mike Innes (@one-more-minute), creator of the Juno IDE for Julia, will be sharing his working on building web-powered apps in Julia, while Viral B. Shah (@ViralBShah), one of the Julia founders, will be discussing more about the inner workings of and plans for JuliaBox. For a different take on “visualization”, Jack Minardi of Voxel8 will be sharing how Julia is powering their 3D printing work.

The statistics session covers some hot topics in the field, including two talks from researchers at MIT about how Julia is playing a big part: probabilistic programming (Sigma.jl) and deep learning (Mocha.jl). Facebooker John Myles White, author of “Machine Learning for Hackers” and a variety of packages in R and Julia, will share his thoughts on how statistics in Julia can be taken to the next stage in development, and Pontus Stenetop (@ninjin) will educate and entertain in his talk “Suitably Naming a Child with Multiple Nationalities using Julia”.

We’ll come together at the end of Thursday to learn more about how to write good Julia code, how to write packages that Just Work on Windows, and how wrappers around C libraries can be made easier than you might think through the magic of Clang.jl. Iain Dunning (@IainNZ), maintainer of Julia’s package listing and test infrastructure will follow up on last years talk by giving a brief history and updated status report on Julia’s package ecosystem. Finally current Googler Lean Hanson (@astrieanna) will share some of her tips for people looking to get started with contributing to Julia and to open-source projects.

Whatever you get up to after the talks end on Thursday, make sure you are up in time for…

Friday’s talks

If you are interested in learning how Julia works from the people who work on it every day, then Friday morning’s session is for you. The morning will kick off with newly-minted-PhD and Julia co-founder Jeff Bezanson (@JeffBezanson), who is still recovering from his defense and will be updating us on the title of his talk soon. We’ll be learning more about different stages of the compilation process from contributors Jake Bolewski (@jakebolewski) and Jacob Quinn (@quinnj), and we’ll be covering a miscellany of other cutting-edge topics for Julia like tuning LLVM, debugging, and interfaces.

In the afternoon we’ll have four sessions split across two rooms. In the second scientific applications session we’ll be learning more about how Julia is being used to prevent airborne collisions from Lincoln Lab’s Robert Moss, and Iain Dunning (@IainNZ) will give a sequel to last years JuliaOpt talk to update us on how Julia is becoming the language of choice for many for optimization. We’ll also hear how Julia is enabling rapid development of advanced algorithms for simulating quantum systems, evolving graphs, and analyzing seismic waves.

The numerical computing track kicks of with Stanford’s Prof. Jack Poulson (@poulson), creator of the Elemental library for distributed-memory linear algebra. Right after, the linear algebra wizard Zhang Xianyi (@xianyi) will give a talk about OpenBLAS, the high-performance linear algebra library Julia ships with. After a break, we’ll hear Viral’s thoughts on how sparse matrices currently and should work in Julia, before finishing off with lightning talks about validated numerics and Taylor series.

We’ll see out the day with two sessions that hit some topics of interest to people deploying Julia into larger systems: data and parallel computing. In the data session we’ll learn how about the nuts and bolts of sharing and storing data in Julia and hear more about plans for the future by the contributors working in these areas. Make sure to check out the talk by Avik Sengupta (@aviks) about his real-world industry experiences about putting Julia code behind a web-accessible API.

The parallel computing session will tackle parallelism at all levels. Contributor Amit Murthy (@amitmurthy) will open the session with a discussion of his recent work and plans for managing Julia in a cluster. We’ll also hear about work being done to make Julia multithreaded at Intel, and about running Julia on a Cray supercomputer.

After all that you will surely be inspired to hack on Julia projects all night, but make sure to wake up for a full day of workshops on Saturday!

Remember to get your tickets and book your hotel before June 4th to take advantage of early bird pricing. We’d also like to thank our platinum sponsors: the Gordon and Betty Moore Foundation, BlackRock, and Julia Computing. We can’t forget out silver sponsors either: Intel and Invenia. We’re looking forward to seeing you there!

Julia Summer of Code 2015

By: Julia Developers

Re-posted from: http://feedproxy.google.com/~r/JuliaLang/~3/Ow64XLo4F5g/jsoc-cfp

Thanks to a generous grant from the Moore Foundation, we are happy to announce the 2015 Julia Summer of Code (JSoC) administered by NumFocus. We realize that this announcement comes quite late in the summer internship process, but we are hoping to fund six projects. The duration of JSoC 2015 will be June 15-September 15. Last date for submitting applications is June 1.

Stipends will match those of the Google Summer of Code (GSoC) at $5500 for the summer plus travel support to attend this year’s JuliaCon at MIT. Some amazing work from last year’s GSoC includes the Juno IDE and Interact.jl package, and we hope to support another round of fun and useful projects.

If you are looking for a project, first, find a mentor. You may want to contact your favorite core developer, package author, or look through some of the previously proposed projects. Mentors will be looking for some evidence that you have experience using Julia and contributing to open source projects, but you are not expected to be an expert in the proposed project area. In fact, JSoC could be a great opportunity to explore an entirely new subject. If you’re already a contributor to Julia or a Julia package and want to get paid to continue an existing project, that’s okay too! In this case we still ask you to find a mentor who’s familiar with your field of work.

If you are a mentor looking for a student, advertise the project! Post it on julia-users and relevant community forums. Keep in mind that project proposals should be concrete but flexible enough to adapt to the interests of a broad range of potential applicants.

Once a mentor and student have agreed on a project, send an email to juliasoc@googlegroups.com for feedback and approval. We ask for this to be done by June 1st at the latest (yes that’s soon!).

Note that we use student in the broad sense. Participation is open to all, in accordance with applicable regulations. Participants do not need to demonstrate student status in any formal way. Contact juliasoc@googlegroups.com with any questions regarding eligibility.

Happy coding!

Julia 0.3 Release Announcement

By: Julia Developers

Re-posted from: http://feedproxy.google.com/~r/JuliaLang/~3/CL0YTb9rG-g/julia-0.3-release

We are pleased to announce the release of Julia 0.3.0. This release contains numerous improvements across the
board from standard library changes to pure performance enhancements as well as an expanded ecosystem of packages as
compared to the 0.2 releases. A summary of changes is available in NEWS.md
found in our main repository, and binaries are now available on our main download page.

A few notable changes:

  • System image caching for fast startup.
  • A pure-Julia REPL was introduced, replacing readline and providing expanded functionality and customization.
  • The workspace() function was added, to clear the environment without restarting.
  • Tab substitution of Latex character codes is now supported in the REPL, IJulia, and several editor environments.
  • Unicode improvements including expanded operators and NFC normalization.
  • Multi-process shared memory support. (multi-threading support is in progress and has been a major summer focus)
  • Improved hashing and floating point range support.
  • Better tuple performance.

We are now transitioning into the 0.4 development cycle and encourage users to use the 0.3.X line if they need a stable
julia environment. Many breaking changes will be entering the environment over the course of the next few months. To reflect this period of change, nightly builds will use the versioning scheme 0.4.0-dev. Once the major breaking changes have been merged and the
development cycle progresses towards a stable release, the version will shift to 0.4.0-pre, at which point package authors
and users should start to think about transitioning the codebases over to the 0.4.X line.

The release-0.3 branch of the codebase will remain open for bugfixes during this time. We encourage users facing
problems to open issues on our GitHub tracker, or email the julia-users mailing list.

Happy coding.


News

JuliaBloggers and the searchable package listing were recently introduced.

The first ever JuliaCon was held in Chicago in June, 2014. Several session recordings are available, and the others will be released soon:

The Julia community participated in Google Summer of Code 2014. Wrap-up blog posts will be coming soon from the participants:

Topical highlights

The colors of chemistry” notebook by Jiahao Chen demonstrating IJulia, Gadfly, dimensional computation with SIUnits, and more.

JuliaStats – statistical and machine learning community.
JuliaOpt – optimization community.
IJulia – notebook interface built on IPython.
Images – image processing and i/o library.
Gadfly – Grammar of Graphics-inspired statistical plotting.
Winston – 2D plotting.