Newsletter December 2020 - JuliaHub Facilitates Interactive Julia Application Development

As you may know, JuliaHub is the easiest way to scale large distributed Julia jobs using the cloud. Now JuliaHub also allows you to develop Julia applications interactively, using an online browser based IDE, or by using the Pluto notebook environment. Hosted on the cloud and paid by the minute, JuliaHub is the easiest way to get started with Julia development or share your work with dashboards and notebooks.

Google Research Director Peter Norvig Says “I Would Be Happier If Julia [Were] the Main Language” [for AI]: Google Research Director Peter Norvig joined Weights and Biases CEO Lukas Biewald on Gradient Dissent, a podcast about machine learning and artificial intelligence. Peter Norvig is the co-author of Artificial Intelligence: A Modern Approach, the leading college textbook on artificial intelligence. Norvig says, “... I would be happier if Julia was the main language [for AI]. Python’s starting to have type declarations now but they don’t quite take them seriously. Julia does a much better job of that and Julia was written to be more efficient from the start.” Click here to listen to the podcast.

Live Instructor-Led Online Julia Training from Julia Computing: Register today for Introduction to Julia, Introduction to Machine Learning and Artificial Intelligence in Julia and Parallel Computing in Julia. All three courses consist of 8 hours of live instruction online from Dr. Matt Bauman, Julia Computing Director of Applications Engineering.

Free Julia Computing Webinars: Register today to participate in a free Webinar from Julia Computing. Each free Webinar is one hour and is presented by a Julia Computing expert.

Converting from Proprietary Software to Julia: Are you looking to leverage Julia’s superior speed and ease of use, but limited due to legacy software and code? Julia Computing and our partners can help accelerate replacing your existing proprietary applications, improve performance, reduce development time, augment or replace existing systems and provide an extended trusted team to deliver Julia solutions. Leverage experienced resources from Julia Computing and our partners to get your team up and running quickly. For more information, please contact us.

Julia Computing Enterprise Products

• JuliaHub: JuliaHub from Julia Computing provides a seamless experience for Julia users to manage their packages, find documentation, make open source contributions and run large compute-intensive workloads. Click here for more information.

• JuliaSure: JuliaSure from Julia Computing provides full service development support, production support and indemnification for companies using Julia. Subscriptions are USD $99 per month. Click here to subscribe.

• JuliaTeam: JuliaTeam from Julia Computing lets your entire enterprise work together using Julia. Collaborate, develop and manage private and public packages across your organization, manage open source licenses and benefit from continuous integration, deployment, security, indemnity and enterprise governance. Click here for more information.

• Pumas: Pumas from Julia Computing and Pumas.ai is a comprehensive platform for pharmaceutical modeling and simulation, providing a single tool for the entire drug development pipeline. Click here for more information.

Julia Computing Is Looking to Hire an Electronics Simulation Engineer: Are you interested in working at Julia Computing, the most exciting tech company devoted to all things Julia? We are looking to hire an Electronics Simulation Engineer to extend Julia’s modeling and simulation capabilities for electronics simulation. Please review the job description and application information.

Julia Part of Apache Arrow: Julia is officially part of the Apache Arrow project. Apache Arrow is a cross-language development platform for in-memory analytics.

Top JPMorgan Technologist Warms to Julia Over Python: Sarah Butcher reports that “Constantin Gonciulea, one of JPMorgan's distinguished engineers [and Executive Director], has had an encounter with Julia, and he's impressed. "When we discuss Machine Learning, Quantum Computing, or Linear Algebra we use Python," says Gonciulea on his LinkedIn page. "After looking at Julia I decided to give it a try and use it anywhere I would use Python. It can also be used instead of the languages I mentioned." Gonciulea says Julia is a good replacement for Python because it has a scripting side and a plot module that allows it to interface with Python plot libraries. "I generally like having types, and generics, and Julia has both," he says. "It does not have covariant and contravariant types like Scala, whose type system is a language in itself, but having generics is a big plus. Like in Python, types can be skipped when it makes sense. It has a lot of libraries, the plotting is great, and it is fast."

Julia Computing at SPLASH: Julia Computing delivered two presentations at the Association for Computing Machinery (ACM) Special Interest Group on Programming Languages (SIGPLAN) conference on Systems, Programming, Languages and Applications: Software for Humanity (SPLASH).

• The Impact of Differentiable Programming: How δP Is Enabling New Science in Julia with Matt Bauman, Julia Computing Director of Applications Engineering

• Daydreaming of Cotangents with Keno Fischer, Julia Computing Co-Founder and CTO Tools

Microsoft Announces Jupyter Extension for VS Code: Microsoft released the new Jupyter extension for VS Code, including sample Julia code. This new release combines the power, speed and ease of use of Julia with the leading code editor and the leading notebook environment. More information is available here.

An Introduction to Pluto.jl: Pluto is a new computational notebook for Julia. LWN’s Lee Phillips published An Introduction to Pluto, which provides more information.

IQdigitec Uses Julia for Finance: IQdigitec is a software development and advisory firm. They deployed a Julia solution for a multinational insurance company with $1.4 trillion in assets to optimize collateral assignment for swaps and derivatives. According to IQdigitec Technology Architect Al Wong, “As we looked at preserving faster compute times and scalability for the future, Julia was the better choice for replacing legacy APL language. Julia works well for executing compute intensive matrix math that works through optimization scenarios which involve very large volumes of alternate solution sets.” More information is available here.

Chris Rackauckas Receives Emerging Scientist Award from International Society of Pharmacometrics: Chris Rackauckas received the Emerging Scientist Award from the International Society of Pharmacometrics at the American Conference on Pharmacometrics. ISoP says “We expect great(er) things from @ChrisRackauckas in the future!”

Deep Nonlinear Mixed Effects Modeling in Pumas: Chris Rackauckas presented a Webinar on Automated Model Discovery and Verification with Deep Nonlinear Mixed Effects Modeling in Pumas. Pumas is built in Julia and is the fastest end-to-end pharmaceutical modeling and simulation platform for quantitative analysis across the drug development lifecycle.

Julia for Climate Modeling: MIT’s Computational Thinking course features Julia as the language of instruction. Course lectures are available free online, including six lectures on climate modeling. Henri Drake’s lecture on ocean currents as two-dimensional advection-diffusion is available here.

Make Your First Julia Pull Request: Katharine Hyatt published an excellent tutorial titled ‘Making a First Julia Pull Request’. This step-by-step guide provides all the information you need to become a contributor to open source Julia.

PrettyTables.jl: PrettyTables.jl is a new backend for DataFrames.jl that allows text tables to be printed with improved formatting and readability. More information is available here.

Julia for Oceanography: Oceananigans.jl and MakieLayout.jl are used to create 3D ocean images. Click here to see this image in motion.

Variography - Spatial Correlation: Júlio Hoffiman presented a tutorial on Variography - Spatial Correlation using Julia. Click here for more information.

Julia and Julia Computing in the News

• Analytics India: Popular Deep Learning Frameworks

• BuiltIn: Top Data Science Podcasts

• Analytics India: Inside Genpact’s Analytics And AI Unit: In Conversation With Sanjay Srivastava, CDO, Genpact

• LWN: An Introduction to Pluto

• Gradient Dissent: Singularity Is in the Eye of the Beholder

• EFinancialCareers: Top JPMorgan Technologist Warms to Julia Over Python

Julia Blog Posts

• Making a First Julia Pull Request (Katharine Hyatt)

• Introducing the Jupyter Extension for VS Code (Rong Lu)

• Graph Coloring Using Cliques (Ole Kröger)

• ABC of A/B Testing (Bogumił Kamiński)

• The Need for Rand Speed (Bogumił Kamiński)

• A Classical Sorting Exercise (Bogumił Kamiński)

• Swift as an Arrow.jl (Bogumił Kamiński)

• Javis v0.3: How to Animate a Fourier Series (Ole Kröger)

• E-graphs in Julia (Part I) (Philip Zucker)

• DataFrames.jl Style Linear Relations (Philip Zucker)

• I Gave a Talk on "Executing Categories" (Philip Zucker)

• Chain.jl - Even More Convenient Piping (Julius Krumbiegel)

• Try MakieLayout - Perfect Layouts For Interactive Scientific Graphics in Julia (Julius Krumbiegel)

• Conversion of Julia DataFrames to Dictionaries (Matt Roughan)

• Partition All the Datas! (Jacob Quinn)

• Bayesian Inference on State Space Models - Part 4 (Patrick Aschermayr)

• Julia First Impressions (Pedro López-Adeva Fernández-Layos)

• Development with Interface Packages (Sam Morrison)

• Introducing: oneAPI.jl (Tim Besard)

• NeuriViz (Part 1) - Performant Graphics for Neuroinformatics (Jacob Zelko)

• Tuples and Vectors, Allocations and Performance for Beginners (Julius Krumbiegel)

Upcoming Julia Online Events

• Webinar: Quantitative Systems Pharmacology Using Pumas with Dr. Matt Bauman (Julia Computing) December 4

• Webinar: High Performance Computation (HPC) on JuliaHub with Dr. Matt Bauman (Julia Computing) December 8

• Webinar: Financial Modeling on Large Streaming Datasets with Dr. Josh Day (Julia Computing) December 10

• Online Meetup: Julia DataFrames with Konstantino Michailidis and Julia User Group Freiburg December 15

• Online Meetup: Julia for R Users with Dr. Paul Palmes, Kevin O’Brien and Dublin R December 17

• Webinar: GPU Programming with Dr. Tim Besard (Julia Computing) January 22

• Webinar: Package Compiler and Static Compilation in Julia with Kristoffer Carlsson (Julia Computing) January 29

• Webinar: Pharmacology and Pharmacometrics Using Pumas with Dr. Vijay Ivaturi (Pumas-AI) February 5

• Online Training: Introduction to Julia with Dr. Matt Bauman (Julia Computing) Feb 11-12

• Online Training: Introduction to Machine Learning and Artificial Intelligence Using Julia with Dr. Matt Bauman (Julia Computing) Feb 18-19

• Online Training: Parallel Computing Using Julia with Dr. Matt Bauman (Julia Computing) Feb 25-26

Recent Julia Online Events

• Virtual Conference: American Conference on Pharmacometrics with Julia Computing November 9-13

• Online Meetup: Aspects of R and Julia with R User Group Rhein-Neckar November 10

• Virtual Conference: SPLASH 2020 with Matt Bauman and Keno Fischer (Julia Computing) November 15-20

• Virtual Conference: Task Based Algorithms and Applications panel at SC20 with Keno Fischer (Julia Computing) November 18

• Webinar: Building Production Applications Using Julia with Avik Sengupta (Julia Computing) November 19

• Online Meetup: R Coffee Break - Vorstellung von Julia (Programmiersprache) with Wiesbaden R User Group November 25

• Online Meetup: Workshop - Ein Machine Learning Task in drei Sprachen: R, Python, Julia with Wiesbaden R User Group December 1

Julia Jobs, Fellowships and Internships Julia Computing is looking to hire an Electronics Simulation Engineer to extend Julia’s modeling and simulation capabilities in electronics. Qualified applicants should review the job description and application information and apply.

There are hundreds of Julia jobs currently listed on Indeed.com and JuliaLang Discourse.

Do you work at or know of an organization looking to hire Julia programmers as staff, research fellows or interns? Would your employer be interested in hiring interns to work on open source packages that are useful to their business? Help us connect members of our community to great opportunities by sending us an email, and we'll get the word out.

Contact Us: Please contact us if you wish to:

• Purchase or obtain license information for Julia Computing products such as JuliaHub, JuliaSure, JuliaTeam or Pumas

• Obtain pricing for Julia consulting projects for your organization

• Schedule online Julia training for your organization

• Share information about exciting new Julia case studies or use cases

• Spread the word about an upcoming online event involving Julia

• Partner with Julia Computing to organize a Julia event online

• Submit a Julia internship, fellowship or job posting

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 by users at more than 10,000 companies 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 and the 2019 Sidney Fernbach Award. 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.