Parallel Computing and Multi-Threading Using JuliaHub

By JuliaHub | Sep 20, 2023

Parallel Computing and Multi-Threading Using JuliaHub: JuliaHub is the best, fastest and easiest way to leverage Julia’s parallel computing and multi-threading capabilities. JuliaHub Sales Engineer Jacob Vaverka has created three resources to help users leverage Julia’s parallel computing and multi-threading capabilities using JuliaHub:

Pluto Notebook Competition: JuliaHub is pleased to announce the winners of the 2023 Pluto Notebook Competition. The winners are:



The winners received cash prizes plus free compute hours on JuliaHub.com. The notebooks were judged based on the following 3 criteria:

  • Does it solve an interesting problem?
  • How interactive is it and what kind of output visualization does it include?
  • How well does it use Julia package(s) / JuliaHub?

Free Webinars from JuliaHub: JuliaHub provides free Webinars covering a range of Julia topics. The Webinars are free but advance registration is required and space is limited. Please click the links below to register.




Guide to Parallel Computing with Julia

Jacob Vaverka, Sales Engineer

Tues Sept 26, 11:30 am - 12:30 pm Eastern (US)

Private Registries and Proprietary Packages on JuliaHub

Deep Datta, Product Director

Thurs Sept 28, 1-2 pm Eastern (US)

APIs and Custom Julia Development on JuliaHub

Morten Piibeleht, Software Engineer

Wed Oct 11, 2-3 pm Eastern (US)

Next-Gen HVAC Simulations for Future-Ready Designs

Avinash Subramanian, Lead developer - JuliaSim HVAC

Thurs Oct 19, 11 am -12 pm Eastern (US)

Accelerating Simulations Using JuliaSimCompiler

Yingbo Ma, Engineering Team Lead

Wed Nov 2, 1-2 pm Eastern (US)


JuliaSim Now Runs Locally or Via Browser: JuliaSim provides best-in-class modeling and simulation tools. Now you can choose whether to install JuliaSim on your personal computer or access JuliaSim via your browser using JuliaHub. Instructions for local installation are available here. JuliaSim modules available through the local registry include:

  • JuliaSimCompiler: A new compiler backend which accelerates the generated code of ModelingToolkit models and improves scaling.
  • JuliaSimModelOptimizer: A toolbox for calibration of ODEs and DAEs with high-performance multiple shooting, collocation, prediction-error method, and other noise-robust approaches. This toolbox is centered around making it easy to perform calibration and design optimization on ModelingToolkit models.
  • JuliaSimControl: A control suite for ModelingToolkit models, allowing for model-predictive control, robust controls, and more in a simple and easy to use interface.

These tools are free for academic and non-commercial usage. Commercial users can make use of JuliaHub’s standard tier to explore these tools and the growing JuliaSim ecosystem. Stay tuned for coming webinars and tutorials which will share all of the ways industrial engineers are making use of these tools and more. Click here for documentation.

Dr. Chris Rackauckas Reviews New JuliaSim Capabilities at JuliaCon: Dr. Chris Rackauckas, JuliaHub VP of Modeling and Simulation, reviewed new JuliaSim capabilities during JuliaCon. Click here to learn more.

Dr. Michael Tiller Joins JuliaHub as Senior Director of Product Management for JuliaSim: JuliaHub is pleased to welcome Dr. Michael Tiller as Senior Director of Product Management for JuliaSim. Dr. Michael Tiller is a Modelica contributor, creator of Modelica University and author of two books including “Modelica by Example”. JuliaSim is the next-generation cloud-based platform for model-based design from JuliaHub that uses modern scientific machine learning (SciML) techniques and equation-based digital twin modeling and simulation to accelerate simulations by up to 500x. Click here for more.

Secure Julia Coding Best Practices: A new white paper from JuliaHub provides a set of best practices for programming securely in Julia. Click here to read.

JuliaCon 2023 Videos Available on YouTube: More than 200 JuliaCon 2023 presentations are now available on YouTube. Click here to watch them all.

JuliaHub Presenters at JuliaCon 2023: JuliaHub presenters were part of at least 24 JuliaCon presentations this year. Click here for a list of JuliaHub presenters at JuliaCon 2023 and links to watch their presentations.

Julia for Chemical Engineering: Efficient Hybrid Modeling and Sorption Model Discovery for Non-Linear Advection-Diffusion-Sorption Systems: A Systematic Scientific Machine Learning Approach is a new paper co-authored by Dr. Chris Rackauckas, JuliaHub VP of Modeling and Simulation. Click here for more.



JuliaHub Release Notes: JuliaHub v6.3.0 release notes are available here. New features include:

  • v6.3.0 adds the capability to build a sysimage to go along with your job run. The sysimage is built before the job starts. After the sysimage build completes, the sysimage is mounted to every Julia process the job uses (main and workers). JuliaHub users can choose to create a SYSIMG by checking the "Build SYSIMG" checkbox during job submission. More information on "What a SYSIMG is?" can be found here.
  • Simple caching based on the pre-built SYSIMGs, this feature ensures that additional runs of a job with the same manifest will reuse the already built sysimage.
  • A fresh and modern user interface for JuliaHub. This update brings a host of usability improvements and a cleaner design, making user interactions smoother and ensures faster loading. UI improvements include a major overhaul to Notifications, Registrator and Projects features.
  • A new grouping for shared datasets for easy distinction, using these groupings; end-users can easily distinguish between shared datasets based on who shared them; without going into details.
  • Users can now create folders or directories in File explorer UI, this will help users to organize their files in an efficient way.
  • New search filter for dependencies & dependents in the packages UI. Using this feature, end-users can now search for direct and indirect dependencies & dependents for a particular package.
  • You can now remove a project viewer's access by setting the resource's general access level to "No Access"
  • Enterprise: Job time limits can now be made optional by an admin on enterprise installs. If this option is enabled, end-users on the JuliaHub instance can start jobs with no time limits.

Recent JuliaHub Webinars Available Free Online: More than 65 free Webinars from JuliaHub are available for free online, including the most recent, Genomic Data Analytics with JuliaHub Using SingleCellProjections and GLMakie. Click here to access all past JuliaHub Webinars.

New Blog Posts from JuliaHub: JuliaHub has published several new blog posts, including new features in JuliaHub and JuliaSim. Click the links below to learn more.

Williams Racing Unlocks SciML Using JuliaSim: Williams Racing is a Formula 1 race team. They use JuliaSim to:

  • Model aerodynamics 169x faster and 7% more accurately than MATLAB
  • Model tire deformation using a quasi-static partial differential equation 1,000x faster than MATLAB and a dynamic differential equation 8x faster using a geometry that is 2.3x higher fidelity
  • Create a digital twin for a physical sensor in order to model in-lap conditions without the extra weight and aerodynamic cost of a physical sensor

Click here to read more about how Williams Racing uses JuliaSim for Formula 1 racing.



Free Compute on JuliaHub (20 hours): In addition to the features JuliaHub has always offered for free – Julia ecosystem search, package registration tools, a dedicated package server – the platform now also gives every user 20 hours of free compute. This allows people to seamlessly share Pluto notebooks and IDE projects with others and let them get their feet wet with computing without having to open up their wallets. Click here to get started or check out Deep Datta’s introductory video, “JuliaHub Is a Free Platform to Start Your Technical Computing Journey”, where he explains how and why to start using JuliaHub for cloud computing.

Upcoming JuliaHub and Julia In-Person Events: Several in-person events featuring JuliaHub and Julia are coming to Europe and North America this year including:

Julia for Hamiltonian Neural Network (HNN): Mustafa Kaddoura has posted an 11 minute video about using Hamiltonian Neural Networks (HNN) in Julia for modeling dynamic systems. Click here to watch.



ASML Uses Makie.jl for Wafer Plots in Julia: ASML, the world’s largest supplier to the semiconductor industry, uses Makie.jl to make wafer plots in Julia. Click here for more information from ASML Architect Matthijs Cox.




Uptake Bivalent Booster Scenario on the COVID-19 Burden and Healthcare Costs in New York City is a new article in the Lancet (Regional Health - Americas) using Julia for public health modeling. Click here for more.


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 20 countries on 6 continents. Click here to learn more about exciting careers and internships with JuliaHub.

Julia and JuliaHub in the News

  • Devmio: Julia - The Programming Language at a Glance
  • EINPresswire: Julia Programming Language Breaks Into the Top 20 of TIOBE Index as Traditional Leaders Hold Their Ground
  • CitizenSide: 10 Amazing Language Software for 2023
  • TechRepublic: TIOBE Index News: Programming Language Julia Makes a Strong Showing
  • Entwickler: Julia - Die Programmiersprache im Überblick
  • HackerNoon: 61 Stories To Learn About Scalability
  • IEEE Spectrum: The Top Programming Languages 2023
  • IEEE Spectrum: How Python Swallowed the World
  • KD Nuggets: Want to Become a Data Scientist? Part 1: 10 Hard Skills You Need
  • Analytics Insight: Top Programming Languages to Land a Job in AI
  • Hacker Noon: 61 Stories to Learn About Scalability
  • Developer Tech: Programming Language Julia Makes TIOBE Index Top 20 Debut
  • Applause: Software Development FAQs Answered
  • The Server Side: Is Python's GIL the Software World's Biggest Blunder?
  • Cellular News: What Is Julia Programming Language?
  • Cryptopolitan: Can Blockchain Technology Foil Sophisticated AI-Fueled Scams?
  • Times of India: Gen AI Has Transformed the Programming World
  • Tribuna Economica: Ce GPU(e) Aveti Nevoie Pentru Deep Learning
  • Developpez: Python et SQL en Tête des Langages des Programmations les Plus Populaires de 2023 sur IEEE Spectrum

Julia Blog Posts

Upcoming Julia and JuliaHub Events

Recent Julia and JuliaHub Events

Contact Us: Please contact us if you want to:

  • Learn more about JuliaHub, JuliaSim, Pumas, PumasQSP or CedarEDA
  • Obtain pricing for Julia consulting projects for your organization
  • Schedule Julia training for your organization
  • Share information about exciting new Julia case studies or use cases
  • Spread the word about an upcoming online or offline event involving Julia
  • Partner with JuliaHub to organize a Julia event online or offline
  • Submit a Julia internship, fellowship or job posting

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.

Looking for Model Predictive Control (MPC)?

Learn about JuliaSim Control in our webinar on MPC, trimming, and linearization in JuliaSim.

Watch Now


Contact Us