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Newsletter April 2019 - New Julia Debugger and Interpreter Released

7 April 2019 | Julia Computing

New Julia Debugger and Interpreter Is Released: The much-anticipated new Julia debugger and interpreter has been released by creators Tim Holy (Professor of Neuroscience at Washington University in St. Louis), Sebastian Pfitzner (Julia Computing, Institut für Physik Humboldt-Universität zu Berlin), Kristoffer Carlsson (Julia Computing) and Keno Fischer (Co-Founder and CTO Tools at Julia Computing).

The new Julia debugger incorporates JuliaInterpreter, Juno, Debugger, Rebugger, Revise, LoweredCodeUtils and CodeTracking into a fully featured debugger, interpreter and integrated development environment.

The new Julia debugger allows users to:

  • Step into functions and manually walk through your code while inspecting its state

  • Set breakpoints and trap errors, allowing you to discover what went wrong at the point of trouble

  • Interactively update and replace existing code to rapidly fix bugs in place without restarting

  • Use the full-featured IDE in Juno to bundle all these features together in an easy to use graphical interface

For more information, read the creators’ blog post or the article in TechRepublic.

Turing Award Winner Yann LeCun Discusses Julia: Turing Award winner Yann LeCun, Facebook’s Chief Artificial Intelligence Scientist, and Facebook’s Soumith Chintala join the Google Brain artificial intelligence team in recognizing Julia’s advantages for deep learning.

The Google Brain artificial intelligence team came to a similar conclusion last year as they sought to improve on TensorFlow for Python, having narrowed down their alternatives to Swift and Julia: “In the end, we narrowed the list based on technical merits down to Swift, Rust, C++, and potentially Julia. We next excluded C++ and Rust due to usability concerns, and picked Swift over Julia because Swift has a much larger community, is syntactically closer to Python, and because we were more familiar with its internal implementation details - which allowed us to implement a prototype much faster.”

Keno Fischer Conducts Quora Session by Invitation on Machine Learning and Julia: Julia Computing Co-Founder and CTO (Tools) Keno Fischer was invited to discuss the present and future of machine learning and Julia on Quora. Click here to read.

NASA Interviews Viral Shah About Circuitscape: The US National Aeronautics and Space Administration (NASA) interviewed Viral Shah (Julia Co-Creator, Julia Computing Co-Founder and CEO) about Circuitscape, a computational landscape ecology application built with Julia. Circuitscape applies electrical circuit theory to predict human, animal, plant and genetic migration in response to climate change. Migrating Circuitscape from Python to Julia resulted in an 8x acceleration. For more information, please read the interview with Viral, visit the Circuitscape Website, read the Circuitscape case study on the Julia Computing Website, watch Ranjan Anantharaman’s presentation on Circuitscape at JuliaCon 2018, or visit the Nature Conservancy’s Migrations in Motion map.

Julia Climbs in RedMonk Ranking: Julia rose from #36 to #34 in RedMonk’s ranking of programming languages for Q1

Differentiable Programming with Flux.jl: Mike Innes (Julia Computing) presented Differentiable Programming with Flux at the London Julia User Group Meetup at the Microsoft Reactor in London. Mike Innes and Google Summer of Code participants Neethu Maria Joy and Tejan Karmal also published a blog on Reinforcement Learning vs. Machine Learning on the Flux Website.

JuMP-dev 2019: Stefan Karpinski (Julia Co-Creator, Julia Computing Co-Founder and CTO Open Source) presented on the Unreasonable Effectiveness of Multiple Dispatch at JuMP-dev 2019 in Santiago, Chile.

JuliaCon 2019: JuliaCon 2019 will be held July 22-26 at the University of Maryland, Baltimore. Early Bird Ticket Sales are open now.

  • JuliaCon is looking for sponsors and university partners in diversity. Sponsorship is available at several levels and benefits include prominent mention and logo placement at JuliaCon and in JuliaCon conference materials and Website, an opportunity to present to JuliaCon participants, presentation space during the conference and registration for JuliaCon attendees. Past JuliaCon sponsors include the Alfred P. Sloan Foundation, Microsoft, Maven, Invenia, Julia Computing, Capital One, Gordon and Betty Moore Foundation, Gambit Research, Tangent Works, Amazon, Alan Turing Institute, Jeffrey Sarnoff, EVN and Conning.

  • Financial assistance for registration and travel is available for those who require assistance in order to attend if they are Google Summer of Code (GSoC) students, accepted speakers or attendees who increase the diversity of the Julia community. Financial assistance is limited, so please apply now if you are eligible and if you require financial assistance to attend JuliaCon.

JuliaTeam: JuliaTeam from Julia Computing enables enterprise governance, making it easy and safe to install Julia packages within your firewall, help administrators keep track of what packages and versions are in use and ensure that all your external dependencies are secure and up-to-date.

Upcoming JuliaTeam releases will include these features as well:

  • Read and search docs for all internal and external packages in a single place

  • Create and manage private package registries

  • Publish and test private packages as easily as public ones, making sure new versions work seamlessly with all the other versions of packages that your teams are using

  • Benchmark your code to make sure it runs as efficiently as possible and stays fast

  • Download a summary of licenses of all the software you depend on

For more information, contact Julia Computing.

JuliaDB: JuliaDB is a Julia Computing database product designed for big data. Features include just-in-time compilation, parallel computing, flexible type storage, fast UDFs and a fast CSV parser. JuliaDB in Julia 1.0 describes some of these features.

JuliaAcademy: Julia Computing’s training offerings continue to expand. JuliaAcademy is the Julia Computing training platform for 3 types of learning: self-directed, online instructor-led and in-person onsite training.

JuliaAcademy courses include: Intro to Julia, Machine Learning and Artificial Intelligence in Julia, Parallel Computing in Julia, Deep Learning with Flux, Optimization with JuMP and Machine Learning with Knet.

JuliaAcademy provides:

  1. Self-directed training - all online, learn at your own pace

  2. Instructor-led online training - live two-day courses taught by Julia Computing instructors

  3. In-person training - contact us at info@juliacomputing.com to schedule customized in-person training for your organization

Register now for instructor-led online courses. All courses include 8 hours of instruction: 4 hours per day for two consecutive days. Currently scheduled courses are from 11 am - 3 pm Eastern Daylight Time (US).

Course Title and DescriptionDate (11 am - 3 pm EDT)CostRegister
***Introduction to Julia***April 24-25$250Register
***Introduction to Machine Learning and Artificial Intelligence in Julia***May 2-3$500Register
***Parallel Computing in Julia***May 8-9$500Register

Geostatistics with GeoStats.jl: The International Association for Mathematical Geosciences (IAMG) annual conference Aug 10-16 in State College, PA will feature a short course on Geostatistics with GeoStats.jl led by Júlio Hoffimann Mendes (IBM Research).

ODSC East: ODSC East is the world’s leading applied data science conference, with 350+ hours of expert-led, hands-on talks and workshops on machine learning, deep learning, natural language processing, machine vision, data visualization and more. Network with 7,000+ peers, demo new platforms from top companies and boost your career, April 30 to May 3, in Boston. Use code ODSC_JuliaCon to sign up.

Julia and Julia Computing in the News

  • NASA: Conservation Through Coding - 5 Questions with Viral Shah

  • Analytics India: How Julia Is Making AI and ML Better

  • Analytics India: 5 Julia-Specific IDEs Developers Should Know

  • Analytics India: Can Julia Be the New Python? Here’s What You Need to Know

  • Analytics India: FB’s New Python Library Nevergrad Provides a Collection of Algorithms that Don’t Require Gradient Computation

  • Bio-IT World: Data Management And Data Transfer Technologies Giving A Spark To Collaboration

  • DevClass: AWS Tunes TensorFlow for Latest Deep Learning Images

  • DevClass: Mozilla Wants Iodide to Breathe Life into Data Science Documents

  • Heise: Deep Learning: MXNet 1.4 Ist Reif für Inferenz in Java-Umgebungen

  • HPCWire: Top Ten Ways AI Affects HPC in 2019

  • Inside HPC: IBM Powers AI at the GPU Technology Conference

  • Inside HPC: New Texascale Magazine from TACC looks at HPC for the Endless Frontier

  • iProgrammer: Apache MXNet Deep Learning Adds Julia API

  • iProgrammer: End Manual Data Entry in Excel

  • IT Jungle: What New Language Will IBM i Support Next?

  • JAXenter: TensorFlow Lite 1.0 Brings Improvements to Mobile Machine Learning

  • JAXenter: JavaScript Reigns Supreme while TypeScript and Julia Surprise with their Growth in New RedMonk Report

  • JAXenter: TensorFlow, Python, and Julia Helped Make 2018 the Year of Machine Learning on GitHub

  • Lei Feng: 芯片行业30年资深人士:AI为何是高性能计算史上 "最大的变革推动者"

  • MMS Holdings: GHP Recognises MMS Holdings in the 2019 Biotechnology Awards Winners

  • SDTimes:

    Julia Debugger Has Been Released

  • TechRepublic: Time to Try the Julia Programming Language? Python Challenger's New Debugger Fixes Major Complaint

  • TechRepublic: How to Learn Julia: A Resources Guide for Developers

  • TechRepublic: Getting Started with Julia: A List of Resources

  • TechRepublic: Mozilla's Iodide Tool Helps Data Scientists Write Interactive Reports

  • TechRepublic: プログラミング言語「Julia」の新サービス「JuliaTeam」–企業への導入を後押し

  • TechRepublic:

    Want to Learn the Fastest-Growing Programming Languages of 2019? Check Out these Two Unstoppable Newcomers

  • TechRepublic: Why PowerShell Is Now One of the Most Popular Programming Languages

  • Wired: TypeScript’s Quiet, Steady Rise Among Programming Languages

  • ZDNet: Programming Languages: PowerShell Nets More Linux, macOS, Windows Developers

  • ZDNet: Microsoft's TypeScript Programming Language Rising Fast, Almost Makes Top 10

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About Julia and Julia Computing

Julia is the fastest high performance open source computing language for data, analytics, algorithmic trading, machine learning, artificial intelligence, and other scientific and numeric computing applications. Julia solves the two language problem by combining the ease of use of Python and R with the speed of C++. Julia provides parallel computing capabilities out of the box and unlimited scalability with minimal effort. Julia has been downloaded more than 7 million times and is used at more than 1,500 universities. Julia co-creators are the winners of the 2019 James H. Wilkinson Prize for Numerical Software. Julia has run at petascale on 650,000 cores with 1.3 million threads to analyze over 56 terabytes of data using Cori, one of the ten largest and most powerful supercomputers in the world.

Julia Computing was founded in 2015 by all the creators of Julia to develop products and provide professional services to businesses and researchers using Julia.

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