Newsletter February 2021 - Julia Climate Modeling Featured in US National Press

“Meet the Team Shaking Up Climate Models” from the Christian Science Monitor describes climate modeling in Julia.

Journalist Doug Struck explains:

“The man with the answer [to the two language problem] occupied an office on the seventh floor of MIT’s “CSAIL” building – the Computer Science and Artificial Intelligence labs. … “They said they thought they wanted to use Julia,” Dr. Edelman recalls. He immediately saw Julia and CliMA as a perfect match. “I was tickled pink, really.” ... the simplicity of using Julia was a game-changer. When the CliMA group began to cautiously use the new language, Dr. Edelman suddenly realized that other scientists and younger graduate students were poking their heads into his lab to learn about this new whiz-fast programming tool. People from different disciplines were interacting. “I didn’t see this coming,” he says. The group at CliMA was quickly convinced. “There was no way we could have done it with another language,” Dr. Ferrari says. “After three or four months, we realized there was no way we could go back.” “Julia paid off for us better than they would have imagined,” Dr. Schneider admits. With Julia, the team released CliMA 0.1, part of the first version of the model, in June. Dr. Schneider says their work is ahead of schedule, and he is encouraged.”

Julia Computing’s Alan Edelman Elected 2020 Association for Computing Machinery Fellow: Alan Edelman has been elected as a fellow of the Association for Computing Machinery. Alan is a co-creator of Julia, co-founder of Julia Computing, MIT Professor of Applied Mathematics, Director of the MIT Julia Lab and leader of the Applied Computing Group at the MIT Computer Science and Artificial Intelligence Laboratory.

Xiu-Zhe (Roger) Luo Awarded Wittek Quantum Prize for Open Source Software: Quantum Open Source Foundation (QOSF) awarded the Wittek Quantum Prize for Open Source Software to Xiu-Zhe (Roger) Luo for his work on Yao.jl and the quantum ecosystem in Julia. Click here to watch the interview on YouTube.

NASA Uses Julia to Analyze the ‘Largest Batch of Earth-Sized Planets Ever Found’: According to NASA, “The TRAPPIST-1 star is home to the largest batch of roughly Earth-size planets ever found.” The analysis is conducted using Julia. According to astrophysicist Eric Agol, “I don't think I could have written & debugged the code so quickly in FORTRAN or C, or debugged it so quickly in IDL or Python … The TRAPPIST-1 planets now have the best measurements of any set of terrestrial planets other than our Solar System … and they look different than our terrestrial planets.”

Julia Adoption Keeps Climbing - Is it a Python Challenger? (HPC Wire): “The rapid adoption of Julia, the open source, high level programming language with roots at MIT, shows no sign of slowing. Julia is hot. One prominent Julia user, Rick Stevens, associate director of Argonne National Laboratory, told HPCwire, ‘I saw the 87 percent increase [in cumulative downloads in 2020] and think it is wonderful to see Julia growing. I think that Julia has great potential to replace C/C++/Python (and of course Fortran) in scientific and technical computing as it matures. The low level performance is excellent. It will be important for it to be adopted as a first-class target language by CPU/GPU vendors.’”

Algorithms for Decision Making: Mykel Kochenderfer, Tim Wheeler and Kyle Wray have published Algorithms for Decision Making, a new textbook using Julia. The book can be downloaded for free.

JuliaCon 2021 - Free and Online - Register Today: JuliaCon 2021 will be free and online from July 28-30. Last year’s JuliaCon brought together 30,000 online participants from over 115 countries. Click here to register and for more information.

JuliaCon 2021 Call for Proposals: The JuliaCon 2021 Call for Proposals is open now. Please prepare and submit your proposal for a talk, lightning talk, minisymposium, workshop, virtual poster, experience or bird of feather session. Proposals must be submitted by March 23.

Julia Computing CEO and Co-Founder Dr. Viral Shah Presents at Shaastra 2021 Tech and Innovation Fair Online: The IIT Madras Shaastra 2021 Tech and Innovation Fair is one of the largest tech conferences in India. This year’s event is online and will take place on Feb 25-28.

JuliaHub Tutorial: JuliaHub is the entry point for all things Julia: explore the ecosystem, build packages, and easily run code in the cloud on big machines and on-demand clusters. A free tutorial from Dr. Matt Bauman (Julia Computing) is available on YouTube.

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

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.

JuliaHub from Julia Computing: 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.

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.

2020 Industry Julia Users Contributhon: Jarrett Revels published a blog post about new open source contributions from commercial Julia users. Contributors include Beacon Biosignals, Invenia, TriScale innov, RelationalAI, and PumasAI. Contributions include:

• Lighthouse.jl, which provides a minimal framework-agnostic interface to standardize/automate performance evaluation for multiclass, multirater classification models (Beacon Biosignals)

• SerializationCaches.jl, which provides a simple, composable mechanism for caching objects that take significantly longer to compute from scratch than to (de)serialize from disk (Beacon Biosignals)

• K8sClusterManagers.jl, which provides mechanisms to dynamically provision Julia workers overtop a K8s cluster (Beacon Biosignals)

• KeywordSearch.jl, which leverages StringDistances.jl to provide a nice interface for fuzzy document searches (Beacon Biosignals)

• PyMNE.jl, an interface to MNE built on top of PyCall (Beacon Biosignals)

• Myriad JuliaPlots contributions (Beacon Biosignals): AbstractPlotting.jl#569, AbstractPlotting.jl#570, WGLMakie.jl#71, JSServe.jl#76

• Improved RegistryCI.jl support for private package registries (Beacon Biosignals)

• Myriad AWS-related contributions (Invenia, Beacon Biosignals):, AWSS3.jl#118, AWSS3.jl#119, AWSS3.jl#120, AWSS3.jl#121, AWSS3.jl#124, AWS.jl#257, AWS.jl#260, AWS.jl#262, AWS.jl#265

• AWSTools.jl, assortment of AWS utility functions (Invenia)

• DateSelectors.jl, which provides utilities for partitioning dates into test/train/validation/etc. sets for time-series machine learning (Invenia)

• Cliquing.jl, which implements various algorithms for finding a non-overlapping set of cliques in a graph (Invenia)

• Checkpoints.jl, which provides mechanisms for dynamically checkpointing Julia program state (Invenia)

• PDMatsExtras.jl, which extends PDMats.jl with a couple different positive (semi-)definite matrix types that nicely interoperate with Distributions.jl (Invenia)

• RegistryCLI.jl, a tool for easily managing private package registries directly from the command line (TriScale innov)

• XUnit.jl, a unit test framework with nice parallelization capabilities (RelationalAI)

• Compiler support for compilation profiling during inference/LLVM optimization, enabling cool new SnoopCompile.jl features (RelationalAI)

• Various quality-of-life improvements to PProf.jl, including interoperability with FlameGraphs.jl and SnoopCompile.jl. (RelationalAI)

Apache Arrow Support in Julia: Apache Arrow provides a cross-language development platform for in-memory analytics. Julia support launched last year and major updates have been released this year. More information is available here.

Julia Package Documentation, Testing and Continuous Integration: Mosè Giordano conducted and published analysis of Julia package documentation, testing and continuous integration.

• 4,312 packages analyzed (4,296 hosted on GitHub + 16 hosted on GitLab)

• 4,287 packages cloned (99.4%)

• 4,139 packages with testing (96.5%)

• 4,105 packages using one or more CI services (95.8%), including:

  • 3,240 using GitHub Actions (75.6%)

  • 2,512 using Travis CI (58.6%)

ITensor: ITensor is a software library for tensor algorithms in Julia and C++. The Julia version of ITensor now offers multithreaded contraction of block-sparse tensors. Visit ITensor.org or The ITensor Software Library for Tensor Network Calculations for more information.

Julia and Julia Computing in the News

• Christian Science Monitor: Meet the Team Shaking Up Climate Models

• HPC Wire: Julia Update - Adoption Keeps Climbing; Is It a Python Challenger?

• Technology Networks: Project Uses Cloud Computing and AI To Address Unsafe Street Drugs

• HPC Wire: Three MIT Faculty Elected 2020 ACM Fellows

• MIT News: Three MIT Faculty Elected 2020 ACM Fellows

• O’Reilly Radar: Where Programming, Ops, AI, and the Cloud are Headed in 2021

• I-Programmer: Season Of Docs 2020 - A Success Story

• Fear the Wall: Westfalenstats - Return of the Math

• Customer Think: For Data Professionals, Python Remains Top Programming Language while R Continues to Decline

• Manufacturer: AI and How Manufacturers Can Embrace It

• Analytics India: Top Programming Languages For Data Scientists In 2021

Julia Blog Posts

• The 2020 Industry Julia Users Contributhon (Jarrett Revels)

• Apache Arrow Support in Julia (Jacob Quinn)

• Profiling Type-Inference (Tim Holy and Nathan Daly)

• On the Bang Row Selector in DataFrames.jl (Bogumił Kamiński)

• Mass Transformations of Data Frames How-To (Bogumił Kamiński)

• Playing with Chain.jl (Bogumił Kamiński)

• Why DataFrame Is Not Type Stable and When it Matters (Bogumił Kamiński)

• Measure Theory for Probabilistic Modeling (Chad Scherrer)

• Symbolic Simplification (Chad Scherrer)

• Generic Bridges (Ole Kröger)

• Creating Bridges with JuMP.jl and MOI.jl (Ole Kröger)

• Sketchy Exact Reals from Interval Arithmetic (Philip Zucker)

• Measuring the Prevalence of Documentation, Testing and Continuous Integration in Julia Packages (Mosè Giordano)

• SciML Ecosystem Update: Bayesian Neural ODEs, Virtual Brownian Trees, Parallel Batching and More

• JuliaCall Update: Automated Julia Installation for R Packages (Chris Rackauckas)

• CUDA.jl 2.4 and 2.5 (Tim Besard)

• Tutorial on Precompilation (Tim Holy)

Upcoming Julia Online Events

• Online Meetup: Differential Equations in Julia with Stuttgart Julia Programming Language Meetup Feb 6

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

• Webinar: AMQP for Flexible and Robust Messaging in Julia with Tanmay Mohapatra (Julia Computing) Feb 19

• Virtual Conference: Shaastra Tech and Innovation Fair with Dr. Viral Shah (Julia Computing) and IIT Madras Feb 25-28

• Webinar: Putting a Trained ML Pipeline Behind a Webserver to Serve It with Dhairya Gandhi (Julia Computing) Feb 26

• Webinar: Pumas-NLME - Integrated, Efficient, and Scalable Pharmacometric Workflows with Dr. Vijay Ivaturi (Pumas-AI) Mar 5

• Online Training: Introduction to Machine Learning and Artificial Intelligence Using Julia with Dr. Matt Bauman (Julia Computing) Mar 11-12

• Webinar: Parallelizing Data Science with Julia with Dr. Elliot Saba (Julia Computing) Mar 17

• Webinar: Multi-Threading Using Julia for Enterprises with Dr. Jeff Bezanson (Julia Computing) Mar 24

• Online Training: Parallel Computing Using Julia with Dr. Matt Bauman (Julia Computing) Apr 8-9

• Virtual Conference: JuliaCon 2021 Jul 28-30

Recent Julia Online Events

• Online Meetup: SymPy.jl and Symata.jl with Boulder Data Science, Machine Learning and AI Jan 14

• Online Meetup: C-Sets for Data Analysis: Relational Data and Conjunctive Queries in Julia with Category Theory and Applications Jan 20

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

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

Julia Jobs, Fellowships and Internships

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

Postdoctoral Research Fellow in Machine Learning: The University of Auckland, New Zealand, is looking to make a two-year postdoctoral appointment to join the Machine Learning in Julia project, a collaboration with the Alan Turing Institute in the United Kingdom. A PhD in mathematics, statistics, computer science or related field is essential, as is experience in scientific programming (Julia preferred) and some software engineering skills. Qualified candidates can find out more about the role by emailing Sebastian Vollmer (svollmer@turing.ac.uk) or Anthony Blaom (anthony.blaom@gmail.com). A significant part of the role will be to provide support for the development of the MLJ machine learning toolbox: https://github.com/alan-<wbr>turing-institute/MLJ.jl

Senior HPC Software Engineer at Liquid Analytics: Liquid Analytics uses artificial intelligence for consulting including retail, technology and market research. They are based in Toronto but hire remote team members anywhere worldwide. More information is available here.

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.