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Newsletter April 2023 - Bob Metcalfe, MIT JuliaLab Research Affiliate, Wins Turing Award

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Bob Metcalfe Wins Turing Award: Professor Bob Metcalfe, MIT JuliaLab Research Affiliate, was awarded the Turing Award, which has been nicknamed the ‘Nobel Prize for Computer Science’. Bob joined Professor Alan Edelman (JuliaHub Co-Founder and Chief Scientist, Julia Co-Creator and MIT JuliaLab Principal Investigator) in a conversation about Julia, technology and the future of computing. Click here to watch.

What’s New in Julia 1.9: Dr. Jeff Bezanson, Julia co-creator and JuliaHub co-founder and CTO, hosted a Webinar on Julia 1.9. Julia 1.9 fixes the longstanding TTFX, or Time to First Execution issue (often called Time to First Plot). Package precompilation now saves native code into a “package image”, accelerating the first plot operation to a fraction of a second. There are several other improvements to threading, packages, and compilation, with an exhaustive list in the Julia 1.9 release notes. Click here to watch.

London JuliaHub Meetup April 21 with JuliaHub VP Engineering Avik Sengupta and VP Modeling and Simulation Dr. Chris Rackauckas: Join JuliaHub in person in London on April 21 at 5:30 pm at the University of London to learn more about Julia 1.9 and Scientific Machine Learning (SciML). Snacks and beverages will be served. Please click here to register.

Free Webinars from JuliaHub: Please register today to participate in a free Webinar from JuliaHub.

  1. Robust MPC for Uncertain Parameters - Wednesday, April, 19 - 10:30 - 11:30 am Eastern (US): Register to see a demo for controlling a simple linear system consisting of a single integrator. We will implement two versions of the controller, the first one will use the nominal plant model only and the second controller will use a model with explicit parameter uncertainty. This Webinar is presented by Dr. Fredrik Bagge Carlson, JuliaHub Control Systems Team Lead.
  2. Cutting Model Translation Time with Pumas-QSP Importers - Tuesday, April 25, 1-2 pm Eastern (US): Click here to register for this free Webinar which answers the question: ‘How do you use performance research without having to go through the painstaking model development steps again?’ As part of this Webinar, we will: a) specify a full optimization problem with the PEtab format; b) import SBML and BioNetGen models together with CSV data; c) visualize your virtual population; d) generate a report of the optimization results. This Webinar is presented by Dr. Paul Lang, JuliaHub Software Engineer.
  3. Using OpenAPI to Describe, Produce, and Consume Web APIs in Julia - Wednesday, May 3, 12-1 pm Eastern (US):  The Julia package OpenAPI.jl along with Julia code generator plugins to OpenAPI Generator help use OpenAPI in Julia projects. This webinar will give a broad overview of OpenAPI and will walk through an example where we start from the specification and create both a Julia web service and a corresponding Julia client to consume it. Attendees will leave with an understanding of how to use OpenAPI in Julia projects. This Webinar is presented by Tanmay Mohapatra, JuliaHub Principal Software Engineer.
  4. Differentiable Simulation and Scientific Machine Learning: Fast Solving and Automated Model Construction - Tuesday, May 9, 10:30 - 11:30 am Eastern (US): Register for this free Webinar. Dr. Chris Rackauckas, JuliaHub Director of Modeling and Simulation, will discuss how using structured scientific (differential equation) models together with unstructured data-driven machine learning models can accelerate simulators and help simulators approximate the true systems, all while enjoying the robustness and explainability of mechanistic dynamical models. Participants will learn the impact of SciML on industrial engineering, the benefits of a SciML approach to modeling, and the difference between SciML and other machine learning techniques.
  5. CUDA.jl 4.0: Using CUDA-Accelerated Binaries and Libraries in Julia - Wednesday, May 10, 10-11 am Eastern (US): Click here to register for this free Webinar with JuliaHub Software Engineer Dr. Tim Besard. Participants will learn how to adapt code or applications to CUDA.jl 4.0, make use of new features and integrate with an existing CUDA-accelerated C application or library.
  6. Modeling Battery Lifespan with JuliaSim - Wednesday, May 17, 10-11 am Eastern (US): Join us as we explore how to model battery lifespan using JuliaSim. JuliaHub Software Engineer Dr. Marc Berliner will demonstrate a new lithium-ion battery simulation tool that offers advanced electrochemical, thermal, and degradation physics for simulating cells, modules, and packs. Attendees will learn how this tool can accurately predict battery performance under various operating conditions, and how it can be used to design and optimize battery systems. A live demonstration will showcase the tool's ease of use and effectiveness in analyzing battery performance, thermal behavior, and degradation over time.
  7. Building Data Visualization Apps with Dash and Julia - Wednesday, May 24, 1-2 pm Eastern (US): Register to see how you can turn your Julia data outputs into beautiful visualizations with Dash.jl. JuliaHub Product Manager Deep Datta will demonstrate how you can build, deploy, manage, and share interactive dashboards with Dash for Julia. Through a couple of simple patterns, you can abstract away all of the technologies and protocols that are required to build a full-stack web app with interactive data visualization. It is simple enough that you can bind a user interface to your code in less than 10 minutes.

American Control Conference: Come meet with JuliaHub at the American Control Conference in San Diego May 31-June 2. You can find JuliaHub at Exhibition Booth #5.

JuliaCon 2023: Early Bird pricing is still available for JuliaCon 2023! Click here to take advantage of discounted Early Bird pricing. JuliaCon will be held in person for the first time since 2019, and will be held at MIT for the first time since 2016. JuliaCon will take place July 25-29. JuMP-dev and SciMLCon will both take place during JuliaCon this year.

  1. Keynote Speakers:  Dr. Christopher Rackauckas, Dr. Stephen Wolfram, Dr. Rumman Chowdhury, Dr. Tim Davis
  2. Sponsorship: Sponsorship is available at many levels, from $1,000 for an exhibition table to $45,000 for Diamond sponsorship. Recent sponsors include: JuliaHub, RelationalAI, Julius Technologies, Intel, AWS, Invenia Labs, Google, EVN, DataChef, Gordon and Betty Moore Foundation, Tangent Works, Replit, Capital One, Nvidia, Microsoft, Alan Turing Institute, Zapata, Beacon Biosignals, Metalenz, ASML, G-Research, Conning, Pumas-AI, QuEra Computing, Jeffrey Sarnoff and more.
  3. Julia Community Prize: Is there someone who you would like to see recognized for their contributions to the Julia language and/or community? Nominations are open now. Please note that past winners are not eligible.

JuliaHub v6.1.0 Release: JuliaHub v6.1.0 is now available with the following features:

  • JuliaHub Projects: We're excited to introduce the new JuliaHub Projects feature, a powerful new capability that allows you to encapsulate files, folders, datasets, code, and share permissions, all within JuliaHub. Collaborate and share your work with your team members with ease. Click here to learn more about JuliaHub Projects.
  • BlobTree Viewer: We've added a new Dataset Viewer feature that enables you to view the BlobTree. The BlobTree is an important data structure in JuliaHub that represents datasets as hierarchical blobs. Click here to learn more about the BlobTree.
  • Event Auditing: You can now view JuliaHub events for auditing purposes. Keep track of all the changes happening within your enterprise account with this new feature.
  • Search Filter: We've added the ability to filter search results by multiple registries, making it easier to find the packages you need.
  • Repository Metadata Display: The metadata for Bitbucket packages is now displayed, making it easier to get the information you need about your repositories.
  • Gitlens Extension: We've added the Gitlens extension to the Julia IDE, enhancing your experience when working with Git repositories.
  • Julia Version Upgrade: We've upgraded the Julia version to 1.8.5, offering improved performance and stability.
  • User Environment Variables: Applications can load environment variables defined in the user's bashrc file.

Julia in the Daily Mail: Julia is featured in The Divisive Math Teaser that Split the World in the Daily Mail, the UK’s highest paid circulation newspaper. The article discusses different interpretations of arithmetic notation and the order of arithmetic operations.

JuliaHub Chief Scientist Alan Edelman at Intel: Intel’s Max Terry published a new blog post on Accelerating Scientific Computing with Julia and oneAPI and shared a link to a 2 hour workshop on The Scientific Computing Power of Julia Revealed featuring Alan Edelman. Alan is Chief Scientist and Co-Founder of JuliaHub, Co-Creator of Julia and Principal Investigator at the JuliaLab at MIT.

JuliaHub and Julia Ranked #12 in Redpoint Open-Source Top 25: The venture team at Redpoint released their debut Open-Source Top 25 and JuliaHub and Julia are ranked #12. Blog posts on the Redpoint Open-Source Top 25 are available from Mischa St. Amand (JuliaHub Senior Director of Marketing) and Redpoint.

JuliaHub_Blog_Bob_Metcalfe_MIT

 
Julia for Coral Reef Fish Communication: Wild Animals Suppress the Spread of Socially Transmitted Misinformation is a new article in the Proceedings of the National Academy of Sciences that demonstrates how coral reef fish weed out false alarms that occur when one fish flees when there is no true shared threat. Click here for the article, data and code.

 

Julia for Biologists: Julia for Biologists is a new article in Nature - Methods. Co-authors include JuliaHub’s Dr. Chris Rackauckas (Director of Modeling and Simulation) and Dr. Elisabeth Roesch. “Julia … is poised to meet the current and emerging demands in the computational biosciences and beyond. Speed, flexibility, a thriving package ecosystem and readability are major factors that make high-performance computing and data analysis available to an unprecedented degree. We highlight how Julia’s design is already enabling new ways of analyzing biological data and systems, and we provide a list of resources that can facilitate the transition into Julian computing.”

Julia for Complex Biological System Modeling: Large-Scale Correlation Network Construction for Unraveling the Coordination of Complex Biological Systems is a new paper featuring Julia in Nature - Computational Science by Huda Nassar and co-authors from Stanford University School of Medicine Departments of Biomedical Data Science, Pediatrics, and Anesthesiology, Perioperative and Pain Medicine.

Julia for Stem Cells: Aberrant Activation of TCL1A Promotes Stem Cell Expansion in Clonal Haematopoiesis is a new article in Nature featuring Julia.

Julia for Climate Modeling: Modeling Global Vegetation Gross Primary Productivity, Transpiration and Hyperspectral Canopy Radiative Transfer Simultaneously Using a Next Generation Land Surface Model—CliMA Land is a new article in the Journal of Advances in Modeling Earth Systems (JAMES). Researchers used Julia to create a next generation land model developed within the Climate Modeling Alliance (CliMA).

Julia for Modeling Fire Connectivity: Assessing Large Landscape Patterns of Potential Fire Connectivity Using Circuit Methods is a new article in Landscape Ecology. Researchers from the US Geological Survey (USGS) and the US Bureau of Land Management (BLM) use the Omniscape connectivity modeling algorithm in Julia.

Julia as a Second Language: Julia as a Second Language is a new book from Erik Engheim. “Originally designed for high-performance data science, Julia has become an awesome general purpose programming language. It offers developer-friendly features like garbage collection, dynamic typing, and a flexible approach to concurrency and distributed computing. It is the perfect mix of simplicity, flexibility and performance.”

Exercism Julia Track: Exercism provides free resources for learning 67 programming languages, including Julia. A new video from Exercism Co-Founder & CEO Jeremy Walker and Exercism Head of Open-Source Eric Schierboom provides an introduction to Julia, Python and R.

Julia vs. R and Julia vs. Python: New Arkiana articles on Julia vs. R and Julia vs. Python point out that Julia is faster, more productive, Julia developers earn higher salaries, Julia is growing fast, Julia developers love Julia and Julia has advanced features and libraries for data science, machine learning, scientific computing, parallel computing, data visualization and plotting.

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? JuliaHub 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 JuliaHub and our partners to get your team up and running quickly. For more information, please contact us.

Careers at JuliaHub: JuliaHub is a fast-growing tech company with fully remote employees in 12 countries on 5 continents. Click here to learn more about exciting careers and internships with JuliaHub.

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About JuliaHub and Julia

JuliaHub is a fast and easy-to-use code-to-cloud platform that accelerates the development and deployment of Julia programs. JuliaHub users include some of the most innovative companies in a range of industries including pharmaceuticals, automotive, energy, manufacturing, and semiconductor design and manufacture.

Julia is a high performance open source programming language that powers computationally demanding applications in modeling and simulation, drug development, design of multi-physical systems, electronic design automation, big data analytics, scientific machine learning and artificial intelligence. 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 prestigious James H. Wilkinson Prize for Numerical Software and the Sidney Fernbach Award.

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