Author Archives: Julia Computing, Inc.

Julia Day in New York on Oct 7

Julia Computing invites you to attend Julia Day in New York to learn more about how Julia is being deployed by enterprise users.

Julia is quickly becoming the language of choice for numerical computing, statistics, data science and machine learning, and is widely used in quantitative finance, asset management, portfolio management, trading strategy development and execution, risk management and actuarial modelling.

Registration link: Please click here to RSVP

When: Monday October 7th from 6:00 PM to 8:00 PM

Where: Google
111 8th Avenue New York, NY
Between 15th St and 16th St
Water Tower Meeting Space

Agenda

  1. Introduction: Viral Shah & Stefan Karpinski, Julia co-creators and Julia Computing co-founders
  2. JuliaSure, JuliaTeam and JuliaRun: Jon Shepherd, Julia Computing VP Sales
  3. Enterprise user case studies
    1. Conning: David Weiss, Managing Director
    2. State Street / BestX: Elton Pereira
  4. Follow-up networking, drinks and snacks

Newsletter October 2019

Julia Computing at the American Conference on Pharmacometrics: Please visit Julia Computing’s booth at the American Conference on Pharmacometrics (ACoP) Oct 20-23 in Orlando. Julia Computing will present PumasAI/Pumas.jl which leverages the power of Julia for pharmaceutical modeling and simulation.

Julia Day in New York: Julia Computing is hosting Julia Day in New York at Google’s New York headquarters on October 7 from 6-8 pm. Julia co-creators and Julia Computing co-founders Viral Shah and Stefan Karpinski and Julia Computing VP of Sales Jon Shepherd will join Julia enterprise users from Conning and State Street / BestX who will present case studies of Julia enterprise deployment in finance. Register here.

Agenda

  1. Introduction: Viral Shah & Stefan Karpinski, Julia co-creators and Julia Computing co-founders
  2. JuliaSure, JuliaTeam and JuliaRun: Jon Shepherd, Julia Computing VP Sales
  3. Enterprise user case studies
    1. Conning: David Weiss, Managing Director
    2. State Street / BestX: Elton Pereira
  4. Follow-up networking, drinks and snacks

Other Upcoming Julia Computing Events

Julia Computing will be participating in a number of upcoming conferences. Please contact us if you would like to meet with us at any of these events.

  1. Athens: Association for Computing Machinery (ACM) Special Interest Group on Programming Languages (SIGPLAN) Conference on Systems, Programming Languages and Applications: Software for Humanity (SPLASH) with Alan Edelman, Stefan Karpinski and Jeff Bezanson (Julia Computing) Oct 20-25
  2. San Jose: LLVM Developers Meeting with Jameson Nash (Julia Computing) Oct 22-23
  3. Denver: SC19 with Alan Edelman (Julia Computing) Nov 17-22
  4. London: Open Data Science Conference (ODSC) with Avik Sengupta (Julia Computing) Nov 19-22
  5. Montreal: Node + JS Interactive with Jameson Nash (Julia Computing) Dec 11-12

JuliaCon 2020: JuliaCon 2020 will take place July 27-31 at ISCTE – Instituto Universitário de Lisboa (ISCTE-IUL) in Lisbon, Portugal. Stay tuned for more details.

Julia Enterprise Users: Enterprise use of Julia continues to grow. Please contact us for more information about Julia Computing enterprise solutions including JuliaSure, JuliaTeam and JuliaRun. A few examples of Julia enterprise users include:

Julia Computing at New York’s Strata Data Conference: Julia Computing participated in the Strata Data Conference Sept 23-26. Jerry Amaral, Julia Computing Director of US Sales, is pictured below.

New Julia Tool for Genomic Data Visualization Published in Nature: Nature published an article titled VIVA (VIsualization of VAriants): A VCF File Visualization Tool about a new Julia tool for visualizing genomic data:

“VIVA employs the Julia programming language, a high-level, high-performance, dynamic programming language for numerical computing. VIVA is among the first user-level tools of its kind written in the Julia programming language. Additionally, it can be integrated into workflows with other tools hosted by BioJulia, the Julia language community for biologists and bioinformaticians.”

Julia Computing Researches TIOBE Language Ranking: Julia Computing published a blog post titled “Thoughts on TIOBE’s Language Ranking Methodology”, in which we also discuss alternative metrics from PYPL, GitHub, RedMonk and IEEE Spectrum. As of Sept 2019, Julia is ranked #8 in GitHub stars and forks (among languages developed on GitHub), #22 on PYPL, #23 on IEEE Spectrum, #33 on RedMonk and #36 according to the TIOBE index.

Live Online Instructor-Led Julia Training

Sign up now for live instructor-led online courses taught by Julia Computing instructors. Each course is 4 hours per day for two days, for a total of 8 hours of instruction per course.

Course Schedule Cost for 8 hours of live online instruction from Julia Computing instructors
Introduction to Julia Day 1: Wed Nov 13 from 11 am – 3 pm ET Day 2: Thurs Nov 14 from 11 am – 3 pm ET $250
Introduction to Machine Learning and Artificial Intelligence Using Julia Day 1: Wed Nov 20 from 11 am – 3 pm ET Day 2: Thurs Nov 21 from 11 am – 3 pm ET $500
Parallel Computing in Julia Day 1: Tues Nov 26 from 11 am – 3 pm ETDay 2: Wed Nov 27 from 11 am – 3 pm ET $500
Register & Pay

JuliaSure: JuliaSure from Julia Computing provides enterprise Julia users with support and indemnity. Contact us for more information.

JuliaTeam: Julia Computing’s JuliaTeam solution works behind your firewall, enables enterprise governance and collaboration, including management of public and private packages and versions, licenses, indemnity and more. Contact us for more information.

Free Version of JuliaBox Is Ending – Pricing for Paid JuliaBox Starts at Just $7 per Month for Academic Users: In January, we notified the Julia community that Julia’s growth was making free JuliaBox unsustainable, and that we would sunset the free version of JuliaBox. As a result, the free version of JuliaBox will end on Oct 31, 2019. We are grateful to all JuliaBox users – especially our paid users. We encourage you to do the following before Oct 31, 2019:

  1. If you want to continue using JuliaBox, please sign up for the paid version before October 31st, 2019. For academic users, the cost starts at just $7 per month.
  2. If you do not want to continue using JuliaBox, please download and save your code and datasets no later than October 31st, 2019. Your data and your code may no longer be available after October 31st, 2019.
  3. If you think your organization, academic department or university should purchase JuliaBox, please contact the decision-maker at your organization, academic department or university, and explain to that person how and why JuliaBox is important to your work. Pricing information is available online, including the 50% academic discount. For other questions about purchasing a paid subscription to JuliaBox, including setting up a new account for your organization and invoicing, please contact us.

Julia and Julia Computing in the News

  • ZDNet: Julia Programming Language – Users Reveal What They Love and Hate the Most About It
  • PacktHub: Developers from the Swift for TensorFlow Project Propose Adding First-Class Differentiable Programming to Swift
  • PharmaBiz: Pumas-AI Introduces Healthcare Software Based on Julia Programming Language for Researchers & Clinicians
  • Nature: VIVA (VIsualization of VAriants): A VCF File Visualization Tool
  • SelfGrowth: Top Data Science Tools Employers Expect You to Know
  • InfoQ: Advanced Data Visualizations in Jupyter Notebooks

Julia Blog Posts

Upcoming Julia Events

Recent Julia Events

Julia Meetup Groups: There are 37 Julia Meetup groups worldwide with 8,531 members. If there’s a Julia Meetup group in your area, we hope you will consider joining, participating and helping to organize events. If there isn’t, we hope you will consider starting one.

Julia Jobs, Fellowships and Internships

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.

There are more than 300 Julia jobs currently listed on Indeed.com, including jobs at Accenture, Airbus, Amazon, AstraZeneca, AT&T, Barnes & Noble, BlackRock, Capital One, CBRE, Charles River Analytics, Citigroup, Comcast, Conde Nast, Cooper Tire & Rubber, Disney, Dow Jones, Facebook, Gallup, Genentech, General Electric, Google, Huawei, Ipsos, Johnson & Johnson, KPMG, Lockheed Martin, Match, Mathematica, McKinsey, NBCUniversal, Netflix, Nielsen, Novartis, OKCupid, Opendoor, Oracle, Pandora, Peapod, Pfizer, Raytheon, Spectrum, Wells Fargo, Zillow, Brown, BYU, Caltech, Dartmouth, Emory, Harvard, Johns Hopkins, Louisiana State University, Massachusetts General Hospital, MIT, Penn State, Princeton, UC Davis, University of Chicago, University of Delaware, University of Kentucky, UNC-Chapel Hill, USC, University of Virginia, Argonne National Laboratory, Federal Reserve Bank, Lawrence Berkeley National Laboratory, Los Alamos National Laboratory, National Renewable Energy Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory, State of Wisconsin and many more.

Contact Us: Please contact us if you wish to:

  • Purchase or obtain license information for Julia products such as JuliaSure, JuliaTeam, or JuliaRun
  • Obtain pricing for Julia consulting projects for your organization
  • Schedule Julia training for your organization
  • Share information about exciting new Julia case studies or use cases
  • Spread the word about an upcoming conference, workshop, training, hackathon, meetup, talk or presentation involving Julia
  • Partner with Julia Computing to organize a Julia meetup, conference, workshop, training, hackathon, talk or presentation involving Julia
  • 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 more than 10 million times 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. 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.

Thoughts on TIOBE’s Language Ranking Methodology

For those who want to track Julia’s growth, some of the most popular
measures of programming language popularity include
PYPL,
TIOBE,
GitHub,
RedMonk and
IEEE Spectrum.
TechCrunch published a useful discussion of the differences among some of these measures last year and Zhang Liye published some tracking data on Julia’s discourse forum last year.
Here’s a very high-level overview of what the different rankings are based on [1]:

  • PYPL ranking is based on searches for language tutorials using Google.
  • TIOBE measures the number of search engine results for the query term +"X programming" on 25 of the most popular search engines worldwide where X is one of potentially several keywords for each language.
  • GitHub looks at stars and forks of languages developed on GitHub.
  • RedMonk is based on the number of GitHub projects plus the number of questions tagged with a given language on Stack Overflow and is usually presented as a scatterplot of where languages fall on these two dimensions.
  • IEEE Spectrum’s incorporates Google Search, Google Trends, Twitter, GitHub, Stack Overflow, Reddit, Hacker News, CareerBuilder, Dice, and IEEE Xplore Digital Library.

So where does Julia rank? As of September 2019, Julia is:

  • #8 in GitHub stars and forks (among languages developed on GitHub)
  • #22 on PYPL
  • #23 on IEEE Spectrum
  • #33 on RedMonk
  • #36 on TIOBE.

As well as being the lowest, Julia’s ranking on the TIOBE index has been particularly volatile. It jumped 11 places from #50 in July to #39 in August and #36 in September 2019. However, we also saw Julia jump from #50 to #37 from February to March of 2018, only to fall back later. We couldn’t help but wonder “what is going on here?” Since the TIOBE index is the most popular but also the most unpredictable, we decided to do a little digging into their methodology, hoping to better understand the volatility we’ve seen.
The specific search query that TIOBE uses for each language is

+"X programming"

In other words, to determine the popularity of Java, it looks for the verbatim phrase “Java programming” across different search engines and counts the number of “hits” each engine reports for that search phrase. According to TIOBE:

It is important to note that the TIOBE index is not about the best programming language or the language in which most lines of code have been written.

TIOBE is transparent about the issues with their current ranking, and actively solicits comments for improvement: “If you have any suggestions how to improve the index don’t hesitate to send an e-mail to tpci@tiobe.com.” According to TIOBE, the top 5 most requested changes to the TIOBE index include:

  1. Apart from "X programming", also other queries such as "programming with X", "X development" and "X coding" should be tried out.
  2. Add queries for other natural languages (apart from English). The idea is to start with the Chinese search engine Baidu. This has been implemented partially and will be completed in the next few months.
  3. Add a list of all search term requests that have been rejected. This is to minimize the number of recurring mails about Rails, JQuery, JSP, etc.
  4. Start a TIOBE index for databases, software configuration management systems and application frameworks.
  5. Some search engines allow to query pages that have been added last year. The TIOBE index should only track those recently added pages.

We at Julia Computing decided to investigate an additional change as part of their most requested potential change. Since Julia and some other languages are often referred to as “the X language” rather than “X programming”, we wanted to learn how rankings would change for Julia and other languages if we included “X language” as well as “X programming” to calculate rankings. We selected the TIOBE top 40 languages and recalculated the rankings using this combined query (+"X language" OR +"X programming").

In the following graph, we have put TIOBE index rank—based only on the search term “X programming”—on the X-axis, and our revised ranking—including both “X programming” and “X language” as search terms—on the y-axis.

Note that a higher ranking corresponds to a lower number (#1 has the most searches), so we inverted the scale on the graph with the highest rankings (lowest numbers) in the top right corner and the lowest rankings (highest numbers) in the bottom left.

  • The biggest loss is for Groovy, which falls from #11 to #38
  • The biggest gain is for ActionScript which climbs from #38 to #14
  • Dart, F# and Delphi all lose rank
  • Julia, Rust, TypeScript, R and D all gain
    • Julia’s new rank is #28 as per this revised ranking

This result led us to give some thought to the following question: Why is is that some languages (e.g. Julia) are more often referred to as “X language” rather than “X programming language”? We can only speculate about the reasons behind this difference. They may be linguistic—the phrase “X programming” is easier to say or sounds more right for some languages, while “X language” is easier or more concordant for others. For example, “Java programming” is a pretty comfortable phrase, whereas “Java language” is kind of awkward and probably only used when trying to make a distinction between the Java language and one of its implementations. This is similar for C, C++ and many languages on the list. This supports the overall use of the search term “Java programming” or “C programming” as a proxy for the popularity of those languages.

On the other hand, since Julia is a person’s name in much of the world, we often find ourselves writing “the Julia language” to clarify what we’re talking about. This may very well affect the number of hits search engines find on the verbatim phrase “Julia programming”. These results, much like the TIOBE ranking itself, are a bit too noisy and hard to interpret to draw firm conclusions, but it does suggest that TIOBE should probably consider broadening their search terms since people write about different languages in different ways.

Another concern with the current TIOBE ranking, alluded to above, is its volatility-language rankings swing wildly from month to month. Indeed, we found that the same search engine frequently shows wildly different counts for the same search depending on the day. We noticed for example, that Baidu’s search counts seem particularly volatile and higher by an order of magnitude compared to Google or Bing.
Even over the few weeks as we carried out our exercise, we noticed variations on Google that would move a language a few places in ranking. Naturally, one might consider various statistical ways to address this volatility.

We’re glad that TIOBE is interested in hearing from the community, and we will be sharing these thoughts with them. In the meantime, if you have any further thoughts on this analysis or other suggested changes to ranking methodology, we would love to hear from you.

  1. Methodology links for each ranking:

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