Tanmay Bakshi in Conversation with Julia Computing’s Viral Shah and Keno Fischer: Tanmay Bakshi invited Julia Computing co-founders Viral Shah and Keno Fischer to discuss Julia - Innovation Starts at the Bottom of the Stack on Tech Life Skills with Tanmay. The full conversation is available here.
Julia at ‘Escape Velocity’ - Jeff Bezanson Talks Julia with Bruce Tate: Julia co-creator and Julia Computing co-founder and CTO (Language) Jeff Bezanson tells Groxio’s Bruce Tate that Julia has reached ‘escape velocity’. Click here to watch the full conversation.
Julia Reaches #28 on TIOBE Index: Julia has reached #28 on the TIOBE Index, #24 on the PYPL Index, #19 on the IEEE Spectrum ranking and ranks #7 in GitHub stars among languages developed on GitHub.
Julia Book by Tom Kwong: Hands-On Design Patterns and Best Practices with Julia by Tom Kwong is available now. Learn how to design and develop high-performance, reusable, and maintainable applications using Julia.
Dash.jl Release: Dash.jl is coming to the Julia registry soon. Click here for the latest information.
COVID-19 Testing Using Julia: Tapestry Pooling uses Julia to test more COVID-19 samples faster, resulting in more testing and faster results.
Visualizing COVID-19 Data Using Julia: Vikas Negi published a blog post on Visualizing COVID-19 Data Using Julia. Click here to learn more.
Julia Is Python + C: Julia Computing CEO and co-founder Viral Shah joined Gadgets Now for a Times Techie Webinar which has been viewed more than 91 thousand times. Shah explains, ““If you’re building a new search engine that’s heavily mathematical, or trying to predict the weather, or discovering a new drug, that’s where you use Julia...It’s for very large data sets and where you are building a complex algorithmic application.”
New Julia Benchmarking: Kel Markert published new Julia benchmarks in Comparing Python and Julia for Hydrologic Modeling. According to Markert, “When running the model once compared to Python, Julia is 914.16% faster!!!”
Julia for Predicting Extreme Events on Financial Markets: Dean Markwick from BestX published an article using Julia to predict the impact of extreme events on equity, fixed income and foreign exchange markets. The article is available to BestX clients.
Best Paper Award from Computers & Chemical Engineering: Computers & Chemical Engineering has selected Graph-Based Modeling and Simulation of Complex Systems to receive the 2019 Best Paper Award. Jordan Jalving, Yankai Cao and Victor Zavala use Plasmo.jl to present graph-based modeling abstractions for cyber-physical systems.
Julia Poised to Dethrone Python for Data Science and Machine Learning: BuiltIn reports that ‘Julia and Swift are poised to dethrone’ Python for data science and machine learning.
Julia Jobs: There are hundreds of Julia jobs currently listed on Indeed.com and Julia Discourse under Jobs. Orchard Ultrasound Innovation is currently looking for a Senior Software Engineer.
Julia Google Summer of Code (GSoC 2020) and Julia Seasons of Contributions (JSoC) Wrap-Up: There are 15 Julia Google Summer of Code projects this year, as well as a number of additional Julia Seasons of Contributions projects. Check out the GSoC 2020 Wrap-Up for more information.
Kirill Zubov GSoC 2020: General Partial Differential Equation Solver Using Neural Networks
Julia Is Faster and Better than R, Matlab and Python for Economic Research: Alvaro Aguirre and Jon Danielsson of the London School of Economics Systemic Risk Centre benchmarked Julia against R, Matlab and Python for economic research. Julia “doesn’t have any historical baggage, and as a result, the code is clean, fast and less error-prone than the others... Julia [is] the best, followed by R, then Matlab, with Python the worst… Julia was designed with speed in mind, taking advantage of modern compiler techniques, and is generally the fastest of the four … Consequently, it doesn’t require the programmer to use complicated techniques for speeding, called code up, resulting in Julia’s code being both more readable and faster... In conclusion, Julia is generally the fastest and requires the least amount of tricky coding to run fast.”
Gridap - An Extensible Finite Element Toolbox in Julia: Santiago Badia and Francesc Verdugo published Gridap - An Extensible Finite Element Toolbox in Julia in the Journal of Open Source Software. Click here for more details.
Julia Computing Live Training Courses and Webinars: Register today for upcoming Julia training courses and Webinars from Julia Computing.
|Event||Event Type||Presenter||Length of Presentation||Dates||Time||Registration Link||Cost|
|Quantitative Systems Pharmacology Using Julia||Webinar||Dr. Matt Bauman, Julia Computing Director of Applications Engineering||1 hour||Thurs Sept 24||12 noon - 1 pm Eastern (US)||Register||Free|
|Pharmacology and Pharmacometrics Using Pumas||Webinar||Dr. Vijay Ivaturi, Chief Scientific Officer Pumas-AI||1 hour||Mon Sept 28||12 noon - 1 pm British Summer Time||Register||Free|
|Intro to Julia||Live Training Course||Avik Sengupta, Julia Computing VP of Engineering||8 hours (4 hours per day x 2 days)||Wed Sept 30 and Thurs Oct 1||11 am - 3 pm British Summer Time||Register||$250|
|Pharmacology and Pharmacometrics Using Pumas||Webinar||Dr. Vijay Ivaturi, Chief Scientific Officer Pumas-AI||1 hour||Thurs Oct 1||12 noon - 1 pm Eastern (US)||Register||Free|
|Intro to Julia||Live Training Course||Dr. Matt Bauman, Julia Computing Director of Applications Engineering||8 hours (4 hours per day x 2 days)||Thurs Oct 15 and Fri Oct 16||11 am - 3 pm Eastern (US)||Register||$250|
|Introduction to Machine Learning and Artificial Intelligence Using Julia||Live Training Course||Dr. Matt Bauman, Julia Computing Director of Applications Engineering||8 hours (4 hours per day x 2 days)||Thurs Oct 22 and Fri Oct 23||11 am - 3 pm Eastern (US)||Register||$500|
|Parallel Computing in Julia||Live Training Course||Dr. Matt Bauman, Julia Computing Director of Applications Engineering||8 hours (4 hours per day x 2 days)||Thurs Oct 29 and Fri Oct 30||11 am - 3 pm Eastern (US)||Register||$500|
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 at email@example.com.
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.
JuliaRun: JuliaRun from Julia Computing helps you scale and deploy Julia using high performance computing (HPC) resources, including large parallel simulations and analyses in the cloud: AWS, Microsoft Azure or Google Cloud. 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.
Julia Computing Is Coming to Your Favorite Online Conferences: Julia Computing is participating in several upcoming online conferences. Please join our Julia talks and workshops or connect with us.
SC20: Task Based Algorithms and Applications panel with Keno Fischer (Julia Computing) November 18
Julia and Julia Computing in the News
Analytics Vidhya: What is Better for Data Science Learning and Work: Julia or Python?
Gadgets Now: Julia is Python + C, Says Creator Viral Shah
InfoQ: Is Julia Production Ready? Q&A with Bogumił Kamiński
VoxEU: Which Programming Language Is Best for Economic Research: Julia, Matlab, Python or R?
Technical.ly: UMB-Born Startup Launches Pharmaceutical Modeling Platform Pumas 1.0
Analytics India: Top 10 Languages That Paid Highest Salaries Worldwide In 2020
Times of India: Microsoft Pulls Plug on Explorer, Once Leading Browser
Open Source for U: With the Internet and Open Source, the World Is Your Playground
UpNewsInfo: Julia is Python + C, Says Creator Viral Shah
PacktHub: Julia Co-Creator, Jeff Bezanson, on What’s Wrong with Julialang and How to Tackle Issues like Modularity and Extension
JaxEnter: Julia - The Programming Language of the Future?
BuiltIn: Python Is About to Get the Squeeze
Julia Blog Posts
The String, or There and Back Again (Bogumił Kamiński)
Subsetting Strings in Julia Using Character Indexing (Bogumił Kamiński)
A Basic SIR Model Using Agent-Based Approach in Julia (Bogumił Kamiński)
Housekeeping August 2020 (Ole Kröger)
ConstraintSolver.jl Refactoring (Ole Kröger)
GPU-Accelerated ODE Solving in R with Julia, the Language of Libraries (Chris Rackauckas)
High Weak Order SDE Solvers (Frank Schäfer)
SciML Ecosystem Update: Neural PDEs, Lie Groups, and Stochastic Delay Differential Equations (Chris Rackauckas)
Alien Facehugger Wasps, a Pandemic, Webcrawlers and Julia (Ömür Özkir)
Analyzing Sources of Compiler Latency in Julia: Method Invalidations (Tim Holy, Jeff Bezanson, and Jameson Nash)
Optionality in the Type Systems of Julia and Rust (Andreas Kröpelin)
CUDA.jl 1.3 - Multi-Device Programming (Tim Besard)
Visualizing COVID-19 Data Using Julia (Vikas Negi)
Comparing Python and Julia for Hydrologic Modeling (Kel Markert)
SciML Ecosystem Update: Koopman Optimization Under Uncertainty, Non-Commutative SDEs, GPUs in R, and More (Chris Rackauckas)
Separating a Column into Multiple Columns in DataFrames.jl (Bogumił Kamiński)
How to Name Things Properly (Tom Kwong)
Yet Another MicroKanren in Julia (Philip Zucker)
A Primer on State Space Models (Patrick Aschermayr)
Checkpoint: Implementing Linear Relations for Linear Time Invariant Systems (Philip Zucker)
Ray Tracing Algebraic Surfaces (Philip Zucker)
GSoC 2020 Wrap-Up (Logan Kilpatrick, Avik Sengupta, & Chris Rackauckas)
Upcoming Julia Online Events
Virtual Conference: ODSC Europe with Julia Computing September 17-19
Virtual Conference: American Modelica with Viral Shah (Julia Computing) September 22-24
Webinar: Quantitative Systems Pharmacology Using Julia with Matt Bauman September 24
Webinar: Pharmacology and Pharmacometrics Using Pumas with Vijay Ivaturi (Pumas-AI) September 28
Webinar: Pharmacology and Pharmacometrics Using Pumas with Vijay Ivaturi (Pumas-AI) October 1
Virtual Conference: American Conference on Pharmacometrics with Julia Computing October 4-7
Online Training: Intro to Julia with Matt Bauman (Julia Computing) October 15-16
Online Training: Introduction to Machine Learning and Artificial Intelligence Using Julia with Matt Bauman (Julia Computing) October 22-23
Online Training: Parallel Computing Using Julia with Matt Bauman (Julia Computing) October 29-30
Virtual Conference: Task Based Algorithms and Applications panel at SC20 with Keno Fischer (Julia Computing) November 18
Online Meetup: Workshop - Ein Machine Learning Task in drei Sprachen: R, Python, Julia with Wiesbaden R User Group December 1
Recent Julia Online Events
Online Meetup: Julia Meetup with Boulder Data Science, Machine Learning and AI August 13
Online Meetup: JuliaCon Afterthought: What Have You Learned from JuliaCon? with Stephan Sahm and Julia User Group Munich August 13
Virtual Conference: Julia Chinese Community 2020 Summer Conference (Julia中文社区2020年夏季会议) August 18-24
Online Meetup: Post-JuliaCon Gathering with Michael Mallari and Julia5280 August 20
Online Meetup: Julia - A Fresh Approach to Technical Computing with Viral Shah (Julia Computing) and PyData Jeddah August 22
Online Meetup: Neural Ordinary Differential Equations with Konstantinos Michailidis, Nicolas Holland and Julia User Group Freiburg August 25
Online Meetup: JuliaConnectoR with Guido Möser and Wiesbaden R User Group August 26
Webinar: Going on a Bull Run: Accelerating Finance with Julia with Matt Bauman (Julia Computing) August 27
Online Meetup: Fall in Love with Julia - Learning Deep Learning in Julia 101 with Julia User Group Munich September 2
Virtual Conference: Virtual AI Summit with Julia Computing September 2-3
Product Demonstration: JuliaHub - Introducing Single Click Scaling and Deployment in the Cloud with Matt Bauman (Julia Computing) September 3
Online Meetup: Julia Meetup with Boulder Data Science, Machine Learning and AI September 10
Julia Jobs, Fellowships and Internships There are hundreds of Julia jobs currently listed on Indeed.com and JuliaLang Discourse. 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, JuliaRun 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.