Julia users and developers are invited to complete the annual Julia User & Developer Survey now. Click here to respond, make your voice heard and be counted as part of the Julia community. The survey is available in English, Chinese, Japanese and Spanish. Chinese users may also choose to respond via qq using this link. The survey is available now and you are encouraged to respond right away. The results of last year’s survey are available here.
Stack Overflow Developer Survey: The annual Stack Overflow Developer Survey is also open now. Click here to participate.
JuliaCon 2021 - Free and Online - July 28-30 - Register Today
Free Registration: JuliaCon 2021 will be free and online. Last year’s JuliaCon brought together 30,000 online participants from over 115 countries. Click here to register.
Sponsorship: JuliaCon is an excellent opportunity for sponsors to support and show their support for Julia. Platinum, gold and silver sponsorships are available. Current and recent JuliaCon sponsors include RelationalAI, Julia Computing, PumasAI, Conning, QuEra, KAUST, NumFOCUS, 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, Jeffrey Sarnoff, Alfred P. Sloan Foundation, Replit, Maven, Gambit, Tangent Works, Alan Turing Institute, EVN, Maven and Voxel8.
JuliaHub from Julia Computing: 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. A free JuliaHub tutorial from Dr. Matt Bauman (Julia Computing) is available on YouTube.
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. Dr. Chris Rackauckas presented Accelerating Simulation of Stiff Nonlinear Systems Using Continuous-Time Echo State Networks with JuliaSim. Click here for more information.
Pumas from Pumas-AI: Pumas is a healthcare analytics platform facilitating quantitative capabilities across the drug development cycle. It is designed from the ground up in Julia to allow 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 development partner and reseller of Pumas. Click here for more information.
Free Webinars from Julia Computing: Register today to participate in a free Julia Computing Webinar. Each free Webinar is one hour.
|Webinar||Presenter(s)||Length of Webinar||Date||Time||Registration Link||Cost|
|Machine Learning with Multi-GPU Training||Dr. Matt Bauman, Julia Computing Director of Applications Engineering||1 hour||June 23||12 noon - 1 pm Eastern (US)||Register||Free|
|Pluto Notebook Support on JuliaHub||Dr. Matt Bauman, Julia Computing Director of Applications Engineering||1 hour||July 15||12 noon - 1 pm Eastern (US)||Register||Free|
Julia 1.6 Addresses Latency Issues: LWN’s Lee Phillips reports that Julia version 1.6 “significantly reduces time to first plot” which was the number one technical complaint about Julia in last year’s Julia User & Developer Survey.
Julia Used for LIDAR Laser Systems: Researchers at the Leibniz Institute for Atmospheric Physics in Germany are using Julia to measure atmospheric temperature and wind speed. Dr. Josef Höffner explains: “We perform complex data acquisition and control, with 30 high speed signals, using three Spectrum Instrumentation cards, operating in closed loop operation 24/7. Our laser makes 500 pulses per second and we have to calculate, in real time, what has to happen next and adjust the controls. For that we have to get the result quickly. That means fast electronics, fast evaluation and then fast control of the hardware. We have found Julia offers a unique combination of speed and dynamic programming, simplifying the software development.”
Income Tax Analysis Using Julia: Hallison Paz (Programação Dinâmica) features in this YouTube video using Julia for income tax analysis.
Julia and Julia Computing in the News
LWN: Julia 1.6 Addresses Latency Issues
EENews Europe: Test Systems Add Julia Support for High Performance AI Analysis
Finextra: Algorithms in the Financial Services industry - The Right Choice for the Right Problem
Heise: Data Science: DataFrames.jl Ist Julias Antwort auf Pythons Pandas
MIT News: Undergraduates Explore Practical Applications of Artificial Intelligence
ELE Times: Spectrum Instrumentation Pioneers “Julia” SDK for High-Performance Applications
The Cowboy Channel: Spectrum Instrumentation Pioneers "Julia" SDK for High-Performance Applications
DataQuest: Meet Julia - Software Language for Faster Developments in AI, Medicine and Robotics
Analytics India: Julia DataFrames 1.0 Released with an Improved Solution for Data Analysis
Nature: Reactive, Reproducible, Collaborative - Computational Notebooks Evolve
Analytics India: Basics Of Julia Programming Language For Data Scientists
ZDNet: This Old Programming Language Is Suddenly Hot Again. But its Future Is Still Far from Certain
EOS: A Tectonic Shift in Analytics and Computing Is Coming
Analytics Insight: Meet Julia - the Programming Language of the Future
I Programmer: Apache Arrow 4 Adds New C++ Compute Functions
Julia Blog Posts
Go Does Not Need a Java Style GC (Erik Engheim)
Julia GPU Programming with WSL2 (Fabian Becker)
Learn With Me: Julia - Introduction (#1) (Fabian Becker)
Learn With Me: Julia - Tools and Learning Resources (#2) (Fabian Becker)
Learn With Me: Julia - Structs and Binary I/O (#3) (Fabian Becker)
Learn With Me: Julia - Bitwise Operators (#4) (Fabian Becker)
DataFrames.jl: Why Do We Have Both Subset and Filter Functions? (Bogumił Kamiński)
The Hardest Part of DataFrames.jl Development Process (Bogumił Kamiński)
A New Tutorial on DataFrames.jl (Bogumił Kamiński)
Advanced Reshaping in DataFrames.jl (Bogumił Kamiński)
DataFrames.jl Joins: matchmissing=:notequal (Bogumił Kamiński)
Animations with Plots.jl (Josh Day)
Performance Tips (Josh Day)
Big CSVs (Josh Day)
Blurb: Forward Sample Exploration in Soss (Chad Scherrer)
Reading Data from the Web with CSV.jl, DataFrames.jl and Chain.jl (Julius Krumbiegel)
Julia Macros for Beginners (Julius Krumbiegel)
Hello, World! I'm Dispatch (Miguel Raz Guzmán Macedo)
Bringing Calcium to Julia (Fredrik Johansson)
JuliaLang on M1 Chip – It Works! (Julia Frank)
Upcoming Julia Online Events
Online Workshop: Introduction to Julia for Statistics and Data Science with Statistical Society of Australia, Victoria Branch Jul 8-9
Virtual Conference: JuliaCon 2021 Jul 28-30
Recent Julia Online Events
Webinar: CUDA.jl 3.0 Features: Concurrent and Parallel GPU Programming with Dr. Tim Besard (Julia Computing) May 25
Julia Jobs, Fellowships and Internships
Liquid Analytics: Liquid Analytics is looking for Julia programmers:
Senior Machine Learning Computer Scientist: Modeling Business Problems with Julia
Senior Polyglot Software Engineer: Build Complex Machine Learning and Graph Systems with Julia
Software Engineer - Automation: Build Web Services, Applications and Microservices with Julia
Computational and Applied Mathematician: Probabilistic and Differential Programming with Julia
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:
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 for businesses and researchers using Julia.