Newsletter May 2022 - Julia Computing In-Person Finance Seminar in NY June 1

Julia Computing Finance Seminar: Julia Computing returns to New York City on June 1 with a new Julia Computing Finance Seminar. The seminar is free to attend but registration is required. Please click here to register. Presenters include Julia co-creator and Julia Computing co-founder and Chief Product Officer Stefan Karpinski, Julia co-creator and Julia Computing co-founder and Chief Technology Officer Jeff Bezanson, and Julia Computing co-founder and Chief Operating Officer Deepak Vinchhi. Participants will learn how Julia is shaping the future of financial technology, increasing the speed, accuracy, and sophistication of financial modeling, reducing computing costs, and providing traders, banks, insurers, analysts, and others with a competitive edge when every millisecond counts. Learn how successful financial companies and organizations such as BlackRock, State Street, Aviva, and the Federal Reserve Bank of New York are using Julia to:

• Improve productivity, speed and performance

• Reduce computing costs and time to market

• Deploy Julia in production and manage enterprise requirements including security, governance, licenses, private package management, access control, scalability, and continuous integration

Seating is limited so please register today! The seminar will take place from 6-8 pm at 15 W 38th St. Drinks and a light dinner will be served.

Free Julia Computing Webinar - Stipple, Building An Interactive App for Data Exploration and Model Explanation: Register today for a free one hour Webinar presented by Jeremie Bouchard (Julia Computing) on Stipple, Building an Interactive App for Data Exploration and Model Explanation. The Webinar will take place on Thursday May 26 from 12 noon - 1 pm Eastern (US). Registration is free.

JuliaSim Webinar Now Available Online: 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. Click here to watch JuliaSim: Model Predictive Control (MPC) and Proportional-Integrated-Derivative (PID) Control, a free one-hour Webinar presented by Julia Computing’s Dr. Fredrik Bagge Carlson

Julia Computing at Advanced Research Projects Agency-Energy (ARPA-E) Energy Innovation Summit: In 2019, Julia Computing was awarded funding through the ARPA-E DIFFERENTIATE program to “develop a neural component machine learning tool to reduce the total energy consumption of heating, ventilation and air conditioning (HVAC) systems in buildings.” Julia Computing CEO Dr. Viral Shah will present the latest update at the ARPA-E Energy Innovation Summit May 23-25. Click here for more information.

GPU Programming with Julia: Dr. Samuel Omlin (CSCS - Swiss National Supercomputing Center) and Dr. Tim Besard (Julia Computing) presented an 8.5 hour course on GPU Programming with Julia at CSCS last year. This course is now available for free online. Course materials are available on GitHub.

JuliaHub: 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. More information about JuliaSim is available here.

Pumas: 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.

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 11 countries on 4 continents. Click the links below to learn more about exciting careers and internships with Julia Computing.

Sales

• Enterprise Account Executive - AI/ML

• Enterprise Account Executive - Pharma/Biotech

• Sales Engineer

• Sales Operations Analyst (Enterprise Software)

Human Resources

• People Operations Specialist

• Talent Acquisition Specialist - US

Engineering

• CI Systems Engineer

• Cloud Engineer

• Cloud Security Architect

• EDA Core System & Compiler Engineer

• Julia Application Developer

• QA Automation Engineer

• Scientific GUI Engineer

• Systems Programmer

Product and Program Management

• Product Manager

• Program Manager

• Quality Manager

Internships

• Controls Engineering Intern

• GUI and 3D Visualization Intern

• Machine Learning Intern

• Modeling and Simulation Intern

• Semiconductor EDA Intern

Please click here for more information and to apply.

JuliaCon 2022: JuliaCon 2022 will be free and online July 27-29.

• Register for Free Today! Registration is required. Registration is free but donations are strongly encouraged for those who are able and want to support JuliaCon and the Julia community. Donations support initiatives such as Julia Community Prizes, Julia Summer of Code, Diversity & Inclusion, Infrastructure and more.

• Sponsorship: JuliaCon sponsorships are available at the Platinum ($30,000), Gold ($15,000) and Silver ($5,000) level. Current and recent JuliaCon sponsors include Julia Computing, Julius Technologies, RelationalAI, Beacon Biosignals, PumasAI, QuEra,Conning, Invenia, Metalenz, NumFOCUS, DataChef, Jeffrey Sarnoff, Amazon, Facebook, Google, Microsoft, Intel, Nvidia, JP Morgan, Capital One, BlackRock, Invenia, Gordon and Betty Moore Foundation, Juspay, Zapata, University of Maryland School of Pharmacy, Alfred P. Sloan Foundation, Replit, Maven, Gambit, Tangent Works, Alan Turing Institute, EVN and Voxel8.

• Julia Community Prizes: The 5th annual Julia Community Prizes will be awarded during JuliaCon. You are encouraged to nominate groups or members of the Julia community for their contributions to the Julia language, community and/or ecosystem.

5x Faster than PyTorch - Scientific Machine Learning in Julia: Chris Elrod, Niklas Korsbo and Chris Rackauckas (Julia Computing) have published a new blog post about Scientific Machine Learning (SciML). They use SimpleChains.jl to achieve results 5x faster than PyTorch.

Julia Computing Selected as 2022 Innovation Showcase Finalist by MIT Sloan CIO Symposium: Julia Computing has been selected by MIT’s Sloan CIO Symposium as a 2022 Innovation Showcase Finalist. The selected outstanding early-stage companies have developed cutting-edge solutions that combine both value and innovation to the Enterprise IT space. The finalists will receive key exposure to many of the world's most creative and influential IT executives at the in-person Symposium from May 22-23, 2022.

Climate Modeling Using Julia: MIT News describes recent advancements in climate modeling using Julia. The Climate Modeling Alliance (CliMA) is a joint project including scientists from MIT, Caltech, the Naval Postgraduate School and NASA’s Jet Propulsion Lab. “For climate models to take full advantage of [recent] advancements, there’s only one option: starting over with a modern, more flexible language. Written in Julia, a part of JuliaLab’s Scientific Machine Learning technology, and spearheaded by Alan Edelman, a professor of applied mathematics in MIT’s Department of Mathematics, CliMA will be able to harness far more data than the current models can handle.”

Julia Computing’s Avik Sengupta Recognized by Best Startup UK: Avik Sengupta (Julia Computing VP Engineering) has been recognized by Best Startup UK as one of London’s Most Impressive and Successful VPs in Cloud Computing. Click here to learn more.

Julia Computing’s Keno Fischer Celebrates Nvidia Open Sourcing Kernel Drivers: Nvidia has open-sourced Linux kernel GPU modules. Keno Fischer, Julia Computing co-founder and CTO (R&D) was among the first to celebrate: “Congratulations to Nvidia for finally open sourcing their kernel drivers. Long time coming, but absolutely the right move. Looking forward to sending some [pull requests] :)” More information is available here.

Julia Computing’s Chris Rackauckas Talks Differential Equations with MIT News: Chris Rackauckas, Julia Computing Director of Modeling and Simulation, discussed differential equations, scientific machine learning (SciML) and more as part of a Q&A with MIT News. Click here for more.

SciMLCon Recordings Now Available Online: If you missed or want to rewatch the first annual SciMLCon, the full proceedings are now available online. Click here to watch.

Talk Julia Podcast: The Talk Julia weekly podcast continued with several new episodes:

• Episode 15: The Julia REPL is Amazing (with Miguel Raz)

• Episode 16: Fast Optimization Using JuMP.jl (with Miles Lubin)

• Episode 17: Julia for Data Analysis (with Bogumił Kamiński)

• Episode 18: Plotting in Julia (Plots.jl, GadFly.jl, and More)

• Episode 19: Is Julia Better Than JAX For Machine Learning?

Learn Julia with Us - Your First Julia Code: Julia Gender Inclusive continues the Learn Julia with Us series with hosts Kyla McConnell and Julia Müller.

• Episode 3: Strings and Arrays

• Episode 4: Number Types

Julia and Julia Computing in the News

• MIT Sloan CIO Symposium: MIT Sloan CIO Symposium Selects Finalists for 2022 Innovation Showcase

• MIT News: Computing Our Climate Future

• MIT News: Chris Rackauckas on the Equations at the Heart of Practically Everything

• Nature Computational Science: And the Turing Award Goes to …

• Proceedings of the National Academy of Sciences: Circadian Pacemaker Neurons Display Cophasic Rhythms in Basal Calcium Level and in Fast Calcium Fluctuations

• The Register: Climate Model Code Is So Outdated, MIT Starts from Scratch

• The Register: Nvidia Open-Sources Linux Kernel GPU Modules

• Best Startup UK: London’s 11 Most Impressive & Successful VP’s in the Cloud Computing Space

• CIO: Essential Data Science Tools for Elevating your Analytics Operations

• Analytics India: Is MATLAB Losing Its Charm?

Julia Blog Posts

• Toolips Is Almost Ready! (Emmett Boudreau)

• Basic Get Requests And Data Interpretation In Julia (Emmett Boudreau)

• Some Major Ways To Make Julia Lightning Fast (Emmett Boudreau)

• Julia’s Strings Are Superior (Emmett Boudreau)

• Creating CSS Animations With Julia (Emmett Boudreau)

• The Where Keyword in Julia And How To Use It (Emmett Boudreau)

• 5 Useful Julia Syntax Rules To Try Out (Emmett Boudreau)

• Different Paradigm Approaches Of The Multiple Dispatch Paradigm (Emmett Boudreau)

• We’ve Been Writing Julia Wrong… Speed Up Julia With Annotations (Emmett Boudreau)

• Odd-Data Ecosystem Update — And Still Big Plans (Emmett Boudreau)

• Servables 2.0 And The Cool Stuff It Offers (Emmett Boudreau)

• Testing Julia (Bogumił Kamiński)

• My First Twitch Live Streaming Session (Bogumił Kamiński)

• Some Special Cases of Method Dispatch in Julia (Bogumił Kamiński)

• Set vs Vector Lookup in Julia: A Closer Look (Bogumił Kamiński)

• An Exercise in DataFrames.jl Transformation Mini Language (Bogumił Kamiński)

• Values' Mutability in Julia (Bogumił Kamiński)

• Creating a Reproducible Favicon (Rik Huijzer)

• TSPSolver.jl: Using Bonobo.jl to Solve Our First Instance (Ole Kröger)

• How to Calculate Realized Volatility (Dean Markwick)

• Modeling Microstructure Noise Using Hawkes Processes (Dean Markwick)

• Pruning the Expression Tree with Recursive Value Identification (Mathieu Besançon)

• Doing Small Network Scientific Machine Learning in Julia 5x Faster than PyTorch (Chris Elrod, Niklas Korsbo, Chris Rackauckas)

• SuiteSparseGraphBLAS.jl: An Introduction (Will Kimmerer)

• OneAPI.jl Status Update (Tim Besard)

• MinGPT in Julia using Flux! (Can Candan)

• Drawing Vector Graphics with Julia can be Awesome (Davis Barreira)

• Some CUDA Programming Fun in Julia (Can Candan)

• RelationalAI Raises $122M to Redefine How Intelligent Data Apps Are Built (RelationalAI)

Upcoming Julia Events

• Virtual Meetup: Julia Meetup with Boulder Data Science, Machine Learning and AI May 19

• Virtual Meetup: Coffee Meeting (Online) with Julia Gender Inclusive May 22

• Cambridge, MA: 2022 Innovation Showcase with Julia Computing at MIT Sloan CIO Symposium May 22-23

• Denver: Advanced Research Projects Agency - Energy (ARPA-E) Innovation Summit with Julia Computing May 23-25

• Virtual Meetup: Machine Learning and Julia with Machine Learning Utah and MX Technologies May 24

• Webinar: Stipple - Building An Interactive App for Data Exploration and Model Explanation with Jeremie Bouchard (Julia Computing) May 26

• Virtual Conference: Intel oneAPI Developer Summit at International Supercomputing Conference with Tim Besard and Jacob Vaverka (Julia Computing) May 27

• Virtual Meetup: Coffee Meeting (Online) with Julia Gender Inclusive May 29

• New York: Julia Finance Seminar with Stefan Karpinski and Deepak Vinchhi (Julia Computing) Jun 1

• Atlanta: American Control Conference with Chris Rackauckas (Julia Computing) Jun 8-10

• Ljubljana: Population Approach Group Europe (PAGE) with Julia Computing Jun 28-Jul 1

• San Francisco: Design Automation Conference (DAC) with Keno Fischer (Julia Computing) Jul 10-14

• Pittsburgh: Society for Industrial and Applied Mathematics (SIAM) with Julia Computing Jul 11-15

• Virtual Workshop: Joint Automated Repository for Various Integrated Simulations (JARVIS) - National Institute of Standards and Technology (NIST) - Artificial Intelligence for Materials Science (AIMS) with Chris Rackauckas (Julia Computing) Jul 12-14

• Virtual Conference: JuliaCon with Julia Computing Jul 27-29

• Dallas: American Modelica Conference with Julia Computing Oct 26-28

• Aurora: American Conference on Pharmacometrics (ACoP) with Julia Computing Oct 30-Nov 2

• New Orleans: Conference on Neural Information Processing Systems (NeurIPS) with Julia Computing Nov 28-Dec 9

Recent Julia Online Events

• Virtual Meetup: Coffee Meeting (Online) with Julia Gender Inclusive Apr 12

• Virtual Meetup: Elementary Economics with Julia with Konstantinos Michailidis and Julia User Group Freiburg Apr 14

• Virtual Meetup: Learn Julia with Us: Strings & Arrays with Kyla McConnell, Julia Müller and Julia Gender Inclusive Apr 14

• Lund: Data-Driven Modeling and Learning for Cancer Immunotherapy with Chris Rackauckas and Fredrik Bagge Carlson (Julia Computing) at Focus Period Lund Apr 19-May 20

• Leiden: Quantitative Systems Pharmacology Conference with Julia Computing Apr 20-22

• Austin: Accurate and Efficient Physics-Informed Learning Through Differentiable Simulation with Chris Rackauckas (Julia Computing) at the University of Texas at Austin Oden Institute for Computational Engineering and Sciences Apr 26

• Oak Ridge: The Continuing Advances of Differentiable Simulation with Chris Rackauckas (Julia Computing) at Oak Ridge National Laboratory Artificial Intelligence for Robust Engineering and Science Apr 26-28

• Webinar: JuliaSim - Model Predictive Control (MPC) and Proportional-Integral-Derivative (PID) Control with Fredrik Bagge Carlson (Julia Computing) Apr 27

• Virtual Meetup: Inverse Kinematics with RigidBodyDynamics.jl with Boulder Data Science, Machine Learning & AI Apr 28

• Copenhagen: Julia Meetup Copenhagen with Copenhagen Julia Meetup Group May 2

• Virtual Meetup: Learn Julia with Us: Number Types with Kyla McConnell, Julia Müller and Julia Gender Inclusive May 12

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.