Newsletter November 2020 - JuliaHub from Julia Computing - Effortless Parallel Computing in the Cloud

JuliaHub: JuliaHub from Julia Computing includes effortless parallel computing in the cloud plus package management. For more information, visit JuliaHub or watch the free Webinar: Single-Click Scaling and Cluster Deployment in the Cloud.

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.

NeuralSim: Existing modeling and simulation tools are unable to keep pace with what engineers need today. As part of ARPA-e DIFFERENTIATE, Julia Computing is developing NeuralSim - a simulation system that uses machine learning to construct surrogates and accelerate models described with ModelingToolkit.jl. Leveraging the FMI interface, NeuralSim can also build surrogates from other blackbox simulators implemented in systems such as Modelica. This can lead to an order of magnitude higher performance for simulations, and is enabled through Julia’s language design, new solvers, and differentiable programming. Julia Computing presented Accelerating Modeling and Simulation with Julia at the American Modelica Conference in September. Contact Julia Computing to learn more about how to speed up your simulations with NeuralSim.

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 Used to Address COVID-19 Pandemic: Professors Janet Sinsheimer, Mary Sehl, Alfonso Landeros and Kenneth Lange discussed Back to School with COVID-19 on “This Week in Virology” with Professors Vincent Racaniello and Rich Condit. The team used SciML/DifferentialEquations.jl to model school reopening strategies. Their research paper, An Examination of School Reopening Strategies during the SARS-CoV-2 Pandemic, is available online.

Julia for VSCode: Julia for VSCode is a free IDE for Julia users. Installation and more information are available here.

Algorithms from THE BOOK: Kenneth Lange has published a new textbook featuring Julia for first-year graduate students and advanced undergraduate students. Algorithms from THE BOOK uses Julia to introduce, illustrate and explore algorithms across a number of disciplines including the principles behind these examples and the assembly of complex algorithms from simple building blocks.

Julia for Actuaries: Alec Loudenback published Julia for Actuaries in Actuarial Technology Today. As Alec explains, “Julia is well suited for actuarial work: easy to read and write and very performant for large amounts of data/modeling … Julia is relatively new and it shows. It is evident in its pragmatic, productivity-focused design choices, pleasant syntax, rich ecosystem, thriving communities, and its ability to both very general purpose and power cutting edge computing … With Julia, math-heavy code looks like math. It’s easy to pick up and quick to prototype. Packages are well integrated with excellent visualization libraries and pragmatic design choices … The language is not just great for data science, but also modeling, ETL, visualizations, package control/version management, machine learning, string manipulation, Web backends and many other use cases.”

How to Build an Artificial Neural Network from Scratch in Julia: Bernard Brenyah published a new blog post about building a new artificial neural network in Julia with no machine learning library. Brenyah explains that Julia “is the perfect companion for numerical computing.”

The Unreasonable Effectiveness of the Julia Programming Language and The Accelerating Adoption of Julia: Lee Philips published The Unreasonable Effectiveness of the Julia Programming Language in Ars Technica and The Accelerating Adoption of Julia in LWN. The Accelerating Adoption of Julia was ranked second on Hacker News.

Franklin: Franklin.jl is a simple, customizable static Website generator for building static Websites in Julia. Learn more at Franklinjl.org.

Introduction to Julia OpenCV Binding: Introduction to Julia OpenCV Binding is a tutorial for open source computer vision and machine learning in Julia. Learn more at OpenCV.

Julia and Julia Computing in the News

• Towards Data Science: How To Build An Artificial Neural Network From Scratch In Julia

• Actuarial Technology Today: Julia for Actuaries

• Financial Express: From Services to Products, SaaS Could Be the Panacea for Indian IT’s Future Growth

• Ars Technica: The Unreasonable Effectiveness of the Julia Programming Language

• LWN: The Accelerating Adoption of Julia

• Plotly: Announcing Dash for Julia

• War on the Rocks: Trust Algorithms? The Army Doesn’t Even Trust Its Own AI Developers

• US Air Force: Historic Agreement Opens Defense Data to Academia

• Tech Xplore: A Home Energy Management System to Achieve Optimal Control of Heat Pumps and Photovoltaics

Julia Blog Posts

• A Quick Introduction to Data Parallelism in Julia (Takafumi Arakaki)

• How the Julia Language Is Making it Easy for Programmers to Use GPU Capabilities with JuliaGPU (Federico Carrone)

• Why Does Julia Work So Well?

• Epidemiological Modeling With Structured Cospans

• Julia Helps To Bridge The Gap Between User and Creator (Julius Krumbiegel)

• Ditch Excel and Use Julia Data Frames (Erik Engheim)

• Train Your Brain with the Julia Language (Bogumił Kamiński)

• The Power of Lookup Functions in Julia (Bogumił Kamiński)

• Should I Use Mutable or Immutable Containers for Agent Based Models in Julia? (Bogumił Kamiński)

• PyData Global 2020 DataFrames.jl Tutorial (Bogumił Kamiński)

• Julia Base is DataFrames.jl Best Friend (Bogumił Kamiński)

• Bayesian Inference in State Space Models - Part 1 (Patrick Aschermayr)

• Inference in State Space Models - Part 2 (Patrick Aschermayr)

• Bayesian Inference in State Space Models - Part 3 (Patrick Aschermayr)

• CUDA.jl 2.1 (Tim Besard)

• Debugging in Julia - Two Different Ways (Ole Kröger)

• The Julia Package Manager (Ole Kröger)

• Theorem Proving For Catlab 2: Let’s Try Z3 This Time. Nope. (Philip Zucker)

• Asterisk (Cormullion)

Upcoming 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 Jeff Bezanson (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

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

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

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

Recent Julia Online Events

• Online Meetup: Julia Meetup featuring Zachary Sunberg’s Reinforcement Learning in Julia with Boulder Data Science, Machine Learning and AI October 8

• Webinar: High Performance Computation (HPC) on JuliaHub with Matt Bauman (Julia Computing) October 13

• Online Meetup: Pluto - Simple Reactive Notebooks for Julia with Julia User Group Freiburg October 13

• Virtual Conference: R in Pharma with Viral Shah (Julia Computing) and Vijay Ivaturi (Pumas-AI) October 13-15

• Online Training: Intro to Julia with Matt Bauman (Julia Computing) October 15-16

• Online Training: Introduction to Machine Learning and Artificial Intelligence Using Julia with Matt Bauman (Julia Computing) October 22-23

• Webinar: Parallel Computing for Enterprises in Julia with Alan Edelman (Julia Computing) October 23

• Online Training: Parallel Computing Using Julia with Matt Bauman (Julia Computing) October 29-30

Julia Jobs, Fellowships and Internships 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, JuliaRun 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.