Newsletter October 2020 - MIT Researchers Use Julia to Forecast Space Storms for NASA and National Science Foundation

The National Science Foundation and NASA have awarded Julia researchers a grant to study and forecast weather in space. Julia Computing Chief Scientist, Julia co-creator and Director of the Julia Lab at MIT Alan Edelman explains: “I’m very excited that Julia, already fast becoming the language of scientific machine learning, and a great tool for collaborative software, can play a key role in space weather applications.”

Stripe CEO Patrick Collison – ‘Pluto for @JuliaLanguage Is Pretty Cool’: Stripe CEO Patrick Colliison tweeted that ‘Pluto for @JuliaLanguage is pretty cool’, and shared a link and favorable review of Grant Sanderson’s latest MIT lecture. 

JuliaGPU: Julia GPU capabilities continue to expand. Visit JuliaGPU for more information.

Grant Sanderson (3Blue1Brown) MIT Course with Alan Edelman, David Sanders, James Schloss and Benoit Forget Reaches 260k+ YouTube Views: Viewership for MIT’s Introduction to Computational Thinking course continues to grow. All lectures are available for free on YouTube.

Julia for Quantitative Systems Pharmacology (QSP): Julia Computing Director of Applications Engineering Matt Bauman presented a free Webinar on Quantitative Systems Pharmacology Using Julia. Click here to watch.

JuliaHub: JuliaHub from Julia Computing includes effortless parallel computing in the cloud plus package management. For more information, watch the free Webinar on JuliaHub: Single-Click Scaling and Cluster Deployment in the Cloud. Or join Dr. Matt Bauman’s next free Webinar introducing High Performance Computation (HPC) on JuliaHub.

Julia Videos and Podcasts

• Data Exchange Podcast: Evolution and Maturation of Julia (Viral Shah)

• JazzComputing: Julia Computing, ML Dev Productivity & Similarities & Differences Between ML & HPC (Viral Shah)

• American Modelica Conference: Accelerating Modeling and Simulation with Julia (Viral Shah)

• Groxio with Bruce Tate: Julia Language and Why We Love It with Viral Shah (Julia Adoption), Jeff Bezanson, Stefan Karpisnki (Multiple Dispatch) and Huda Nasser (Speed, Graphs and Data, Things Just Work in Julia)

• Software Freedom Day 2020: Julia and the Future of Machine Learning – Differentiable Programming (Dhairya Gandhi)

JuliaMono Font: Cormullion has created a new monospaced font for Julia and other text editing environments that require a wide range of specialist and technical Unicode carriers. The new font is:

• Free

• Open-source

• Suitable for scientific and technical programming as well as for general purpose hacking

• Available for MacOS, Unix, and Windows

• Easy to use, simple, friendly, and approachable

• Distributed with a liberal licence

New Julia Speed Results – 334x Faster than Python for Color Science: Porting color science code from Python to Julia resulted in a 334x speed increase.

The Little Book of Julia Algorithms: Ahan Sengupta and William Lau have published The Little Book of Julia Algorithms, targeted at middle and high school programmers.

Using Time Travel to Remotely Debug Faulty DRAM: Julia Computing CTO (Tools) and co-founder Keno Fischer explains how he used time travel to remotely debug faulty DRAM.

Julia Computing Live Instructor-Led Training Courses: Register today for upcoming Julia training courses from Julia Computing.

Free Julia Computing Webinars: Register today for free Webinars from Julia Computing.

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 info@juliacomputing.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 and Julia Computing in the News

• TechRepublic: Top 5 Programming Languages for Data Scientists to Learn

• Analytics India: Top Technologies To Achieve Security And Privacy Of Sensitive Data In AI Models

• MIT News: MIT-Led Team to Develop Software to Help Forecast Space Storms

• Analytics India: What Is Code Golfing?

• HPCWire: Oracle Cloud Deepens HPC Embrace with Launch of A100 Instances, Plans for Arm, More

• SciTechDaily: Predicting When the Sky Will Bleed – MIT-Led Team to Develop Software to Help Forecast Space Storms

• Analytics Insight: 4 Tips to Secure a Data Scientist Job at Google

• Analytics Insight: The Top 50 Programming Languages to Learn Coding

• Heise: Data Science – Mozilla Stellt Webbasiertes Tool Lodide Ein

Julia Blog Posts

• Javis v0.2 and the Future (Ole Kröger)

• Javis.jl with Animations.jl (Ole Kröger)

• Flexible Performant GEMM Kernels on GPUs (Thomas Faingnaert, Tim Besard, Bjorn De Sutter)

• Notes on Synthesis and Equation Proving for Catlab.jl (Philip Zucker)

• DataFrames.jl vs Pandas, dplyr, and Stata (Bogumił Kamiński)

• Depth (Cormullion)

• Row Aggregation in DataFrames.jl (Bogumił Kamiński)

• Pseudo Broadcasting in DataFrames.jl (Bogumił Kamiński)

• State Space Models Everywhere! Round 1: HSMM (Patrick Aschermayr)

• Using Time Travel to Remotely Debug Faulty DRAM (Keno Fischer)

• Transitioning Code From Closed To Open: A JuliaCon 2020 Discussion Between Julia Users In Industry (Jarrett Revels)

• My First Encounter with Julia (Ritobrata Ghosh)

• GSoC 2020: ZXCalculus.jl, ZX-Calculus in Julia (Chen Zhao)

• On the Performance and Design of BioSequences Compared to the Seq Language (Jakob Nybo Nissen, Ben J. Ward)

• First Impressions of Julia from an R User (David Neuzerling)

• Graphs and C-sets I: What Is a Graph? (Evan Patterson)

• Graphs and C-sets II: Half-Edges and Rotation Systems (Evan Patterson)

• On the Implementation of C-sets (Owen Lynch)

• Modeling Frameworks: What Is a Scientific Model? (James Fairbanks)

• JuliaMono – A Monospaced Font for Scientific and Technical Computing (Cormullion)

• CUDA.jl 2.0 (Tim Besard)

• Julia Base Is DataFrames.jl Best Friend (Bogumił Kamiński)

• From Python to Julia and Learning by Doing – A Case Study with an Opinion Dynamics Model Simulation (Unchitta Kan)

• Bayesian Inference in State Space Models – Part 1 (Patrick Aschermayr)

Upcoming Julia Online Events

• Online Meetup: Julia Meetup featuring Zachary Sunberg’s Reinforcement Learning in Julia with Boulder Data Science, Machine Learning and AI October 8

• Webinar: High Performance Computation (HPC) on JuliaHub with Matt Bauman (Julia Computing) October 13

• Online Meetup: Pluto – Simple Reactive Notebooks for Julia with Julia User Group Freiburg October 13

• Virtual Conference: R in Pharma with Viral Shah (Julia Computing) and Vijay Ivaturi (Pumas-AI) October 13-15

• 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

• Webinar: Parallel Computing for Enterprises in Julia with Alan Edelman (Julia Computing) October 23

• Online Training: Parallel Computing Using Julia with Matt Bauman (Julia Computing) October 29-30

• Virtual Conference: American Conference on Pharmacometrics with Julia Computing November 9-13

• Virtual Conference: SPLASH 2020 with Matt Bauman and Jeff Bezanson (Julia Computing) November 15-20

• Virtual Conference: Task Based Algorithms and Applications panel at SC20 with Keno Fischer (Julia Computing) November 18

• Webinar: Building Production Applications Using Julia with Avik Sengupta (Julia Computing) November 19

• Online Meetup: R Coffee Break – Vorstellung von Julia (Programmiersprache) with Wiesbaden R User Group November 25

• Online Meetup: Workshop – Ein Machine Learning Task in drei Sprachen: R, Python, Julia with Wiesbaden R User Group December 1

• Webinar: Quantitative Systems Pharmacology Using Pumas with Matt Bauman (Julia Computing) December 4

• Webinar: High Performance Computation (HPC) on JuliaHub with Matt Bauman (Julia Computing) December 8

• Webinar: Financial Modeling on Large Streaming Datasets with Josh Day (Julia Computing) December 10

Recent Julia Online Events

• Virtual Conference: ODSC Europe with Julia Computing September 17-19

• Virtual Conference: Software Freedom Day Panjab University with Dhairya Gandhi (Julia Computing) September 19

• Virtual Conference: American Modelica with Viral Shah (Julia Computing) September 23

• Webinar: Quantitative Systems Pharmacology Using Julia with Matt Bauman September 24

• Webinar: Pharmacology and Pharmacometrics Using Pumas with Vijay Ivaturi (Pumas-AI) October 1

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.