Newsletter August 2021 - Julia Computing Completes $24 Million Series A Fundraise and Former Snowflake CEO Bob Muglia Joins Julia Computing Board of Directors

Julia Computing completed a $24 million Series A fundraise and announced that former Snowflake CEO Bob Muglia has joined the Julia Computing Board of Directors. More than 200 news organizations covered this announcement including US News & World Report, Reuters, Yahoo! Finance, Fortune Italia, Financial Post, Benzinga, Markets Insider, HPCWire, Woburn Daily Times Chronicle, Boston Business Journal, Analytics Insight, YourStory, Yahoo! Finance India, Daily Hunt, MSN India, eeNews Europe, Times of India, I Programmer, eFinancial Careers, Analytics India, AIThority, Economic Times, ET Tech Morning Dispatch, eeDesignNews Europe, Venture Capital Journal, Silicon ANGLE, Robotics 247 and TexasNewsToday.

Julia Computing Featured in Wall Street Journal: Julia Computing is featured in the July 31 Wall Street Journal article by Christopher Mims titled Why Artificial Intelligence Isn’t Intelligent. As the Wall Street Journal explains, “Viral Shah is CEO of Julia Computing, a cloud-software company that makes tools for programmers who build AI and related systems. His customers range from universities working on better batteries for electric vehicles to pharmaceutical companies searching for new drugs.”

Can You Spot the JuliaHub Logo? JuliaHub, the fastest and easiest on-ramp for using Julia in the cloud, was featured on the Williams Formula One race car at the Formula One Hungarian Grand Prix. James Bower, Commercial Director for William Racing, said, “We are delighted to welcome Julia Computing to Williams as a partner of Dorilton Ventures. Investing in companies building best-in-class cloud technology is a strategic focus for Dorilton and the versatile JuliaHub platform, with revolutionary capabilities in simulation and modeling, is hugely relevant to our business. We look forward to embedding Julia Computing in the world’s most technologically advanced sport and we are excited to be involved in their future successes.” The story appeared in BlackBook MotorSport, F1News.ru and AutoMobilSport.

Julia Ranked 5th Most Loved Language - Stack Overflow Developer Survey: Julia outranked Python, Swift and Go as the 5th Most Loved Language in the Stack Overflow Developer Survey.

Julia Computing Receives DARPA Award to Build AI-Based Digital Phased Arrays with GPUs: Julia Computing has been awarded funding by the US Department of Defense Advanced Research Projects Agency (DARPA) to bring Julia’s advanced artificial intelligence (AI) and machine learning (ML) capabilities to the field of fully digital phased array systems. Funding was awarded as part of DARPA’s Tensors for Reprogrammable Intelligent Array Demonstrations (TRIAD) program. More information is available here.

Julia Reaches 50k Commits on GitHub: GitHub congratulated Julia on reaching 50,000 commits. This milestone was achieved thanks to the efforts of more than 1,000 Julia contributors. There are more than 5,000 contributors who have contributed to packages in the Julia General registry.

Media Surge for Julia and Julia Computing: Julia Computing’s Series A Funding drove a large increase in news articles about Julia and Julia Computing.

JuliaCon 2021: This year’s JuliaCon was the biggest and best JuliaCon yet, with more than 300 presentations available for free on YouTube, more than 20 thousand registrations and more than 43 thousand unique YouTube viewers during the conference. This is up from 162 presentations, 10 thousand registrations and 28,900 unique viewers during last year’s conference. Blog posts about JuliaCon 2021 include:

• Julia Computing at JuliaCon 2021

• JuliaCon 2021 Highlights

• JuliaCon 2021, the Largest Julia Programming Event in History (Logan Kilpatrick)

• Julia User & Developer Survey 2021 (Andrew Claster, Viral Shah)

• Growing Open-Source from Torch to PyTorch (Soumith Chintala)

• The Best Data Science Talks of JuliaCon 2021 (Josh Day)

• SciML at JuliaCon 2021

• Invenia at JuliaCon 2021 (Glenn Moynihan, Lyndon White, Matt Brzezinski, Miha Zgubič, Rory Finnegan, Will Tebbutt)

Julia Computing at JuliaCon 2021: Presentations featuring Julia Computing presenters include:

• State of Julia - Jeff Bezanson, Stefan Karpinski, Keno Fischer, Viral Shah

• JuliaSim: Machine Learning Accelerated Modeling and Simulation - Chris Rackauckas

• JuliaHub & JuliaSim (Julia Computing Sponsor Presentation) - Viral Shah, Matt Bauman, Chris Rackauckas

• Julia User & Developer Survey 2021 - Andrew Claster

• GPU Programming in Julia - Valentin Churavy, Tim Besard, Julia Samaroo

• Game Development in Julia with GameZero.jl - Ahan Sengupta, Avik Sengupta

• Package Development in VSCode - David Anthoff, Sebastian Pfitzner

• Simulating Big Models in Julia with ModelingToolkit - Chris Rackauckas

• A Tour of the Differentiable Programming Landscape with Flux.jl - Dhairya Gandhi

• Open and Interactive Computational Thinking with Julia and Pluto - David P. Sanders, Fons van der Plas, Alan Edelman

• JuliaSPICE: A Composable ML Accelerated Analog Circuit Simulator - Glen Hertz, Pepijn de Vos

• CUDA.jl 3.0 - Tim Besard

• DataSets.jl: A Bridge Between Code and Data - Chris Foster

• Global Sensitivity Analysis for SciML Models in Julia - Vaibhav Dixit

• Atomic Fields: the New Primitives on the Block - Jameson Nash

• Partitions and Chains: Enabling Batch Processing for Your Data - Jacob Quinn

• PGFPlotsX.jl - Plotting with LaTeX, Directly from Julia - Kristoffer Carlsson

• Deep Dive: Creating Shared Libraries with PackageCompiler.jl - Kristoffer Carlsson, Simon Byrne, Kevin Squire, Nikhil Mitra

• Creating a Shared Library Bundle with Package Compiler - Kristoffer Carlsson, Simon Byrne, Kevin Squire

• Systems Biology in ModelingToolkit - Anand Jain, Shahriar Iravanian, Paul Lang

• Roadmap to Julia BLAS and LinearAlgebra - Chris Elrod

• Symbolics.jl - Fast and Flexible Symbolic Programming - Shashi Gowda, Yingbo Ma

• Runtime-Switchable BLAS/LAPACK Backends via libblastrampoline - Elliot Saba, Mosè Giordano

JuliaHub & JuliaSim: Viral Shah, Matt Bauman and Chris Rackauckas presented JuliaHub & JuliaSim, the Julia Computing sponsor presentation. JuliaHub is the entry point for all things Julia: explore the ecosystem, build packages, deploy a supercomputer, develop Julia applications interactively using a browser-based IDE or by using the Pluto notebook environment and then scale workloads to thousands of cores. JuliaSim is a next-generation cloud-based modeling and simulation platform, combining the latest techniques from scientific machine learning with equation-based digital twin modeling and simulation. For more information, check out Chris Rackauckas’s presentation JuliaSim: Machine Learning Accelerated Modeling and Simulation.

Julia Community Prize Winners: Congratulations to the winners of the Julia Community Prize. The presentation is available here. The winners are:

• Bogumił Kamiński & Milan Bouchet-Valat for their custodianship of DataFrames.jl and the data ecosystem

• Fons van der Plas for his work on Pluto.jl

• Dilum Aluthge for his contributions to our community infrastructure and community building

Keynote Speeches: This year’s keynote speeches were stellar, as always, and among the most viewed presentations of the conference.

• William Kahan, Professor Emeritus of Mathematics, and of Electrical Engineering and Computer Science presented Debugging Tools for Floating-Point Programs

• Jan Vitek, Professor of Computer Science at Northeastern University presented Julia: Great Language, or The Greatest Language?

• Xiaoye (Sherry) Li, Senior Scientist at Lawrence Berkeley National Laboratory presented Interplay of Linear Algebra, Machine Learning and HPC

• Soumith Chintala, Distinguished Engineer at Facebook AI Research presented PyTorch and My Journey in Open Source. Blog post is available here.

Code, Docs and Tests: What’s In the General Registry? Mosè Giordano and Eric P. Hanson presented Code, Docs and Tests: What’s In the General Registry? The General registry is the collection of open source packages that makes up the Julia package ecosystem. The Julia General registry has 11.8 million lines of code (including docs and tests). More than 96% of packages have an Open Source Initiative approved license, 88% have at least 20 lines of readme or docs, 96% have run tests, 95% have setup for continuous integration, 58% of packages have at least 2 contributors, 93% have at least 10 commits, 48% of contributors have contributed to two or more packages and 60% of contributors have made at least 5 commits. There are currently more than 5,000 Julia contributors who have contributed to packages in the General registry. For more information, read their blog post.

State of Julia: Jeff Bezanson, Stefan Karpinski, Keno Fischer and Viral Shah presented the State of Julia, including recent and future improvements. DevClass published a summary of the presentation titled State of Julia: The Future Looks Modular, Generic, and Fast which explains many of the highlights. These include speed increases for CSV.jl and DataFrames.jl, packages reaching 1.0, threading roadmap, faster method insertion, small type info improvements, inference improvements, subtyping and intersection fixes and speedups, CI stability, latency, system images, array optimizations, GC performance, compiler extensibility, new compiler directions, AbstractInterpreter, OpaqueClosure, compiler plugins, AD, BLAS, sparse matrices and linear algebra.

JuMP-dev Conference: This year, the JuMP-dev conference was co-located with JuliaCon for the first time. JuMP-dev presentations are available via this dedicated YouTube playlist.

Julia User & Developer Survey: The third annual Julia User & Developer Survey was presented. 2,660 Julia users and developers from 104 countries participated, and explained how much and why they love Julia and the Julia community, as well as their biggest pain points and areas for improvement. Click here for the video presentation, slides, blog post and article.

Julia Jumps to #26 on TIOBE Index: Julia jumped from #35 to #26 this month in the volatile TIOBE Index. TIOBE CEO Paul Jansen says “Both Rust and Julia are strong candidates for a permanent top 20 position.” For more information about the TIOBE Index, other programming language rankings and Julia, read Julia Computing’s 2019 Thoughts on TIOBE’s Language Ranking Methodology. Julia ranks #7 in GitHub stars, #19 on the IEEE Spectrum list of top programming languages, #26 on the PYPL ranking and #28 on the RedMonk list.

Free Webinar from Julia Computing: Register today to participate in a free one hour Webinar from Julia Computing.

Pumas - Enhanced and In the Cloud: Pumas-AI has launched an enhanced version of Pumas that is readily accessible in the cloud. Pumas is the revolutionary advanced healthcare analytics platform that facilitates quantitative capabilities across the drug development cycle. Designed from the ground up in Julia, Pumas allows users to scale, integrate and accelerate their quantitative scientific activities all under one umbrella. Pumas is a product of Pumas-AI and deployed through the JuliaHub platform from Julia Computing to leverage JuliaHub's ease of use and scalability. Julia Computing is a technology partner and exclusive reseller of Pumas. Click here for more information.

JuliaHub from Julia Computing: JuliaHub is the entry point for all things Julia: explore the ecosystem, build packages and deploy a supercomputer at the click of a button. JuliaHub also allows you to develop Julia applications interactively using a browser-based IDE or by using the Pluto notebook environment and then scale workloads to thousands of cores . Version 5 features a brand new user interface, reduced app startup latency, and many more usability enhancements. JuliaHub is the easiest way to start developing in Julia or share your work using dashboards and notebooks.

More information is available in these two presentations from Dr. Matt Bauman (Julia Computing):

• JuliaHub - The Best Way to Run Large Scale Computing in the Cloud

• GUI Front Ends for Julia Programs on JuliaHub

JuliaSim: JuliaSim is a next generation cloud-based modeling and simulation platform, combining the latest techniques from scientific machine learning with equation-based digital twin modeling and simulation. There is more information about JuliaSim available in this presentation from Dr. Chris Rackauckas.

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 Jobs: Julia Computing is looking to hire:

• Wireless Systems Research Engineer

• Compiler and Runtime Engineer

• Cloud Engineer

• Sales Engineer

• Julia Application Developer

Julia Computing is also looking to fill internship positions:

• GUI and 3D Visualization Intern

• Modeling and Simulation Intern

Please click here for more information and to apply.

Julia and Julia Computing in the News (Highlights from the 250+ Julia and Julia Computing News Stories Published Last Month)

• Wall Street Journal: Why Artificial Intelligence Isn’t Intelligent

• Analytics India: “Today’s Systems For Numerical Computing Are Stuck In A Local Basin Of Performance & Ease Of Use”

• ELE Times: Novel Scientific Computing Method for Studying Utility-Scale Renewable Power Systems

• Analytics Insight: Julia Is Causing Quite a Stir with Code Modernization in the Tech Industry

• DevClass: State of Julia: the Future Looks Modular, Generic, and Fast

• Analytics Insight: The Best Programming Language for Data Science - Python vs. Julia vs. R

• Market Research Telecast: Survey - Performance Is the Most Important Argument in Favor of the Julia Programming Language

Julia Blog Posts

• Julia Computing at JuliaCon 2021

• JuliaCon 2021 Highlights

• JuliaCon 2021, the Largest Julia Programming Event in History (Logan Kilpatrick)

• Julia User & Developer Survey 2021 (Andrew Claster and Viral Shah)

• Code, Docs, and Tests: What's In the General Registry? (Eric P. Hanson, Mosè Giordano)

• SciML at JuliaCon 2021

• The Best Data Science Talks of JuliaCon 2021 (Josh Day)

• Growing Open-Source from Torch to PyTorch (Soumith Chintala)

• Invenia at JuliaCon 2021 (Glenn Moynihan, Lyndon White, Matt Brzezinski, Miha Zgubič, Rory Finnegan, Will Tebbutt)

• Javis.jl Examples Series: The Chase Problem (Ole Kröger)

• Summer Break Puzzle (Bogumił Kamiński)

• Using QuestDB to Build a Crypto Trade Database in Julia (Dean Markwick)

• QuestDB Part 2 - High Frequency Finance (Again!) (Dean Markwick)

• AbstractDifferentiation.jl for AD-Backend Agnostic Code (Frank Schäfer)

• How to Make Your Joins Faster in DataFrames.jl? (Bogumił Kamiński)

• Basic DataFrames.jl: Getting the Data (Bogumił Kamiński)

• DataFrames.jl at JuliaCon 2021 (Bogumił Kamiński)

• Transforming Multiple Columns with Multiple Functions in DataFrames.jl (Bogumił Kamiński)

• What Is New in DataFrames.jl 1.2.0? (Bogumił Kamiński)

• Useful Algorithms That Are Not Optimized By Jax, PyTorch, or Tensorflow (Chris Rackauckas)

• ThorneHole.jl

• Shadowing Methods for Forward and Adjoint Sensitivity Analysis of Chaotic Systems (Frank Schäfer)

• Sensitivity Analysis of Hybrid Differential Equations (Frank Schäfer and Moritz Schauer)

• Simulation of a Swimming Dogfish Shark (Gabriel D Weymouth)

• The State of Multiple Threading in DataFrames.jl (Bogumił Kamiński)

• CUDA.jl 3.4 (Tim Besard)

• DataFrames.jl User's Corner: Filtering Performance (Bogumił Kamiński)

• Embedding Jupyter and Pluto Notebooks in a Blog Post is Easy (Julia Frank)

• Gnuplot with Julia for Powerful Plotting Option (Julia Frank)

• Creating Custom Plot Markers in JuliaLang in 2 Ways (Julia Frank)

Upcoming Julia Events

• Webinar: GPU Programming in Julia with Dr. Tim Besard (Julia Computing) Aug 26

• Virtual Conference: Population Approach Group Europe (PAGE) with Julia Computing Sep 2-7

• Virtual Meetup: A Client Interface in Julia - TypeDBClient.jl with Mark Schulze, Frank Urbach, Daniel Crowe and TypeDB New York Engineers Sep 7

• Virtual Meetup: CUDA.jl with Boulder Data Science, Machine Learning and AI Sep 9

• Virtual Meetup: Poisson Regression and Introduction to Julia with Steve Simon and Kansas City R Users Group Sep 11

• Virtual Conference: Modelica Conference with Julia Computing Sep 20-24

• Virtual Conference: Geostats.jl Workshop with Júlio Hoffimann at FOSS4G Sep 28

• Virtual Conference: American Conference on Pharmacometrics with Julia Computing and Pumas-AI Nov 8-12

Recent Julia Online Events

• Meetup: Julia - Data Model - A Conversation Built Around Types with Pleasanton Julia - Programming the Language Jul 2

• Meetup: What Makes Julia the unPython? with Pleasanton Julia - Programming the Language Jul 3

• Online Meetup: Share & Code Probabilistic Modelling with Turing.jl with Stephan Sahm and Julia User Group Munich Jul 5

• Online Workshop: Introduction to Julia for Statistics and Data Science with Statistical Society of Australia, Victoria Branch Jul 8-9

• Webinar: Pluto Notebook Support on JuliaHub with Dr. Matt Bauman (Julia Computing) Jul 15

• Virtual Conference: Accelerating the Simulation of Highly Stiff HVAC Systems with Continuous-Time Echo State Networks with Dr. Chris Rackauckas (Julia Computing) at the 16th U.S. National Congress on Computational Mechanics Jul 25-29

• Virtual Conference: JuliaCon 2021 and JuMP-dev 2021 Jul 28-30

• Virtual Meetup: JuliaCon 2021 Round Table and Discussion with Boulder Data Science, Machine Learning and AI Aug 12

• Webinar: Package Compiler and Static Compilation in Julia with Kristoffer Carlsson (Julia Computing) Aug 17

• Virtual Meetup: Meet Julia! with Scott Lett and Ft. Collins Data Science Aug 24

Contact Us: Please contact us if you wish to:

• Purchase or obtain license information for products such as JuliaHub, JuliaSim 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 Computing and Julia

Julia Computing's mission is to develop products that bring Julia's superpowers to its customers. Julia Computing's flagship product is JuliaHub, a secure, software-as-a-service platform for developing Julia programs, deploying them, and scaling to thousands of nodes. It provides the power of a supercomputer at the fingertips of every data scientist and engineer. In addition to data science workflows, JuliaHub also provides access to cutting-edge products such as Pumas for pharmaceutical modeling and simulation, JuliaSim for multi-physics modeling and simulation, and JuliaSPICE for electronic circuit simulation, combining traditional simulation with modern SciML approaches.

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.