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Newsletter September 2022

30 September 2022 | Julia Computing

SciML at Kennedy Space Center?: The SciML community is conducting a 4 question survey to assess interest and potential participation in a February 2023 SciML conference at the Kennedy Space Center in Cape Canaveral, Florida. Please click here to participate in this survey.

Free Webinars from Julia Computing

  1. Building Digital Twins with JuliaSim: Click here to register for a free Julia Computing webinar, Building Digital Twins with JuliaSim, on Tuesday October 18 from 2-3 pm Eastern (US). The Webinar is led by Dr. Raj Abhijit Dandekar (Julia Computing). JuliaSim is a next-generation simulation suite that combines the latest Scientific Machine Learning (SciML) techniques with equation-based digital twin modeling and simulation. Participants will learn how to build a digital twin with JuliaSim components, how to calibrate your model to data and how to train model surrogates. Space is limited, so please register now to reserve your spot.

  2. Fast and Furious Development with JuilaHub Workflows: Click here to register for a free Julia Computing webinar, Fast and Furious Development with JuliaHub Workflows, on Friday October 28 from 2-3 pm Eastern (US). The Webinar is led by Deep Datta (Julia Computing). JuliaHub is the fastest, easiest way to access Julia, the fastest and most powerful high performance open source programming language for scientific and numerical computing. Webinar participants will learn how JuliaHub tooling provides the easiest on-ramp for enterprise development, how to use the Julia package registry, bring new Julia packages into JuliaHub, create a private package repository and bring continuous integration into your workflows. Space is limited, so please register now to reserve your spot.

  3. PumasQSP: PumasQSP is a package and methodology for pharmacometrics users practicing QSP to solve difficult model calibration and analyses in a high-performance and user-friendly manner. New and upcoming features include:

  • New documentation

  • Tutorials

  • A full Pumas-QSP training exercise course including:

    • Model translation and definition

    • Generation of virtual populations using stochastic optimization

    • Subsampling of virtual populations using discrete density sampling

    • Global sensitivity analysis using Sobol

    • Pumas-QSP usage tips

    • Application of automatic parallelization on JuliaHub

More information is available here. Please contact us for more information.

Pumas v2.2 Release: Pumas is a comprehensive platform for pharmaceutical modeling and simulation, providing a single tool for the entire drug development pipeline. It is used for simulation and estimation of quantitative pre-clinical and clinical pharmacological models. Pumas v2.2 is now available, including the following features:

Pumas

  • Introduce prediction correction for continuous VPCs (pcVPC) based on a simulated population mean prediction

  • Support censoring and truncation with literal upper and lower bounds for SAEM (PumasEMModels)

  • A new closed-form solution for a model with one central compartment and one metabolite was added and is called Central1Meta1

PumasUtilities

  • All previous individual apps are now combined into a single app interface

  • Model builder UI for creating PumasModels

  • Data loader UI for reading in CSV files into DataFrames

  • Population Builder UI for converting DataFrames into Population objects

  • Launch interactive reports for selected diagnostics using Pluto notebooks

NCA

  • Support for Bioanalytical file format (all rows of amt filled) and separate dosing and concentration sheets

  • Sparse sampling NCA support

  • Dose linearity analysis, including plots and tables

Julia v1.8 Release: Julia v1.8 has been released. Highlights are available in Julia 1.8 Highlights and Julia 1.8 Improves Apple Silicon Support. New features include:

Julia Headlines September TIOBE Report: The latest TIOBE report is out and TIOBE CEO Paul Jansen says “Julia is getting close to the TIOBE index top 20. The Julia programming language is only 0.05% away from a top 20 position. Julia is designed for numerical analysis and computational science. There are many competing languages in that field. So what makes Julia stand out? Julia beats Matlab because it is much more modern and it can be used free of charge. Furthermore, Julia beats Python and R because it is much faster. Since there is a huge demand in the number crunching and modeling field, Julia has a serious chance to enter the top 20 in the near future.”

How Julia ODE Solve Compile Time Was Reduced From 30 Seconds to 0.1: SciML has published How Julia ODE Solve Compile Time Was Reduced From 30 Seconds to 0.1. Click here for more.

Julia for Epidemiology: Raj Dandekar has published two new blog posts: Julia for Epidemiology and Scientific Machine Learning for Epidemiologists - Part 1. The blog posts are available here and the code is available here.

Julia for Astronomy: Emina Hafiz is a University of Calgary student who completed a summer internship using Julia at the Université de Montréal Institute for Research on Exoplanets. Hafiz explains her work: “Solving the N-body problem for the eight planet compact system of KOI 2433 by implementing Jacobi coordinates using the Julia programming language. It was interesting to learn how to use MCMC (Markov Chain Monte Carlo) to take estimates we have of certain planet characteristics such as mass and period to calculate a series of best fits for the data that allow us to recalculate those values more accurately. It’s also very interesting and exciting to know that these values at some point will be uploaded to the NASA Exoplanet Archive. I found the masses, periods, centre of transit, and eccentricities for the planets in the KOI 2433 system and created a visual of how the orbits looked. This data included a newly discovered planet for this system. I believe the most important result was the orbits of the exoplanets because it provides a lot of information about how the exoplanets interact with one another, which in turn affects their individual characteristics. I learned how to code in Julia and how to use MCMC. Before this internship, I only knew how to code in Python which is quite similar to Julia but isn’t as computationally powerful.”

Julia Computing - Coming to a Conference Near You: Julia Computing will be present at a number of upcoming conferences and events. Click below for more information.

Algorithms for Decision Making: Algorithms for Decision Making is a new book from Mykel Kochenderfer, Tim Wheeler and Kyle Wray. Click here for more.

Interactive Visualization and Plotting with Julia: Interactive Visualization and Plotting with Julia is a new book by Diego Javier Zea. Click here for more information.

Fundamentals of Numerical Computation - Julia Edition: Fundamentals of Numerical Computation - Julia Edition is a new book by Tobin Driscoll and Richard Braun. Click here for more information.

Solving Nonlinear Equations with Iterative Methods - Solvers and Examples in Julia: Solving Nonlinear Equations with Iterative Methods - Solvers and Examples in Julia is a new book by C.T. Kelley. Click here for more information.

Research Software Engineering (RSE) International Survey: The UK Software Sustainability Institute has released the Research Software Engineering (RSE) International Survey. Julia ranks #12 on programming languages used at work, and has increased from 3.5% to 6.5%. Click here for full results.

Makie.jl: The Journal of Open Source Software has published Makie.jl: Flexible High-Performance Data Visualization for Julia. Click here for more.

BeautifulMakie: A new domain for BeautifulMakie is now available - Beautiful.Makie.org. 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? 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.

Careers at Julia Computing: Julia Computing 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 Julia Computing.

Julia for Market Prediction: “G-Research is looking for a software engineer who is keen to contribute directly to the open-source Julia project. G-Research uses data science and machine learning tools to predict movements in the markets and we're very interested in furthering the development of the Julia language and supporting the community. This role could focus on a number of different areas from the compiler to Flux to improved packaging to DataFrames – there's a lot to do and we're looking for someone who has a passion to move an area of Julia forward. This role will be a part of our open-source program office so all contributions from this role will definitely impact the entire community. If you're interested, reach out at jobs@gr-oss.io."

Julia and Julia Computing in the News

Julia Blog Posts

Upcoming Julia and Julia Computing Events

Recent Julia and Julia Computing Events

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 Cedar 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.

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