We wanted to thank all Julia users and well wishers for the support and for being part of the Julia Community, and to give an update on some exciting developments for February 2018:
JuliaBox is now available at scale with parallel computing capabilities. JuliaBox runs in the cloud on dozens, hundreds or thousands of nodes, depending on your requirements. As always, there is no download required with JuliaBox - you can run it straight from your browser using a Jupyter notebook. Full JuliaBox documentation including examples and reference information for parallel functionality is available here. For pricing, a free 2 week trial, or more information about parallel computing with JuliaBox, please contact us and let us know how many nodes you require.
The free version of JuliaBox continues to be fully supported for current and new users with the latest version of Julia, package updates, new features and improved memory, flexibility and reliability.
Julia Computing continues to undertake a number of innovative consulting and custom development projects involving artificial intelligence, machine learning and deep learning. Julia’s machine learning capabilities are integrated with JuliaDB, making it possible to ingest data from a variety of sources, apply machine learning and generate insights quickly. Julia Computing employs many of the core developers of Julia and its machine learning packages. Please contact us if you are interested in partnering with Julia Computing on projects involving artificial intelligence, machine learning or deep learning.
Celeste: Julia Computing partnered with the National Energy Research Scientific Computing Center (NERSC), Lawrence Berkeley National Laboratory, UC Berkeley, MIT Julia Lab and Intel to classify 188 million astronomical objects in just 14.6 minutes using one of the ten largest and most powerful supercomputers in the world.
Path BioAnalytics: Julia Computing and Path BioAnalytics are using deep learning and image processing techniques to identify organoids for precision medicine.
Drishti Eye Hospitals: Julia Computing partnered with Drishti Eye Hospitals and developed a deep learning algorithm to diagnose diabetic retinopathy, which affects more than 126 million patients worldwide.
Please see our Case Studies for many other examples of how Julia can be used to solve challenges you face.
Introduction to Solving Differential Equations with Chris Rackauckas: Please join Chris Rackauckas and Julia Computing for a live YouTube training on Solving Differential Equations in Julia Tuesday Feb 6 at 10 am PST / 1 pm EST / 6 pm GMT / 7 pm CET / 11:30 pm IST.
JuliaCon is coming to University College London Aug 7-11, 2018.
Everyone who is interested is strongly encouraged to submit a proposal, regardless of level of experience with Julia or as a speaker. JuliaCon thrives on having talks ranging from introductory to advanced. If you are reading this and work with Julia in any form, you are encouraged to submit a proposal.
Proposals may be submitted for talks, lightning talks, workshops, posters and package collaboration. Other ideas and suggestions, such as a topic or focus for a hackathon, are also welcome. Please click
here for more details, proposal advice and submission.
If you are willing to mentor a first-time speaker including providing feedback on abstracts or presentations, discussing presentation skills and more, please sign up here.
JuliaCon 2018 offers mentorship for first-time speakers and presenters. Details are available here. Please indicate in your proposal submission if you would be interested in mentorship.
JuliaCon 2018 has corporate sponsorship opportunities available. JuliaCon 2018 will be held Aug 7-11, 2018 at University College London.
Julia Computing led a 5-day training at Bangalore’s M.S. Ramaiah Institute of Technology in machine learning and artificial intelligence using Julia. The training was extremely successful and one of many to come in India, the US and worldwide.
Julia Computing was part of the Celeste team that was awarded the HPC Innovation Award by Hyperion Research. The Celeste team leveraged 650,000 cores with 1.3 million threads to analyze 56 terabytes of data and classify 188 million astronomical objects in 14.6 minutes using one of the ten largest and most powerful supercomputers in the world.
Julia Computing’s Keno Fischer and NERSC’s Prabhat participated in a podcast interview on Ad Astra about Celeste. Tune in to hear how the Celeste team classified 188 million astronomical objects in just 14.6 minutes.
Julia Computing co-founders Alan Edelman (Julia Computing Chief Scientist and MIT Professor of Applied Mathematics) and Viral Shah (Julia Computing CEO) were interviewed by Factor Daily. Alan explains: “We can take machine learning everywhere but it’s not going to be one size fits all.”
Alan Edelman and Viral Shah joined Chintan Mehta at iSPIRIT to discuss deep learning. The event was streamed live on YouTube.
Stanford University’s Irán Román published a course in Spanish on artificial intelligence with neural networks using Julia: “Algoritmos de Inteligencia Artificial con Redes Neuronales Artificiales.
Do you work at or know of an institution 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 200 Julia jobs currently listed on Indeed.com, including jobs at Google, Facebook, IBM, KPMG, Ernst & Young, Booz Allen Hamilton, Comcast, Zulily, National Renewable Energy Research Laboratory, Los Alamos National Laboratory, Brown, Princeton, Columbia, Notre Dame, MIT, University of Chicago and many more.
Invenia Labs is hiring Julia developers for their Cambridge, UK and Winnipeg, Canada offices.
Penn State University’s Department of Astronomy and Astrophysics Center for Exoplanets and Habitable Worlds (CEHW) is looking to hire a Postdoc Researcher and Assistant Research Professor with Julia experience.
There are 26 Julia Meetup groups worldwide with more than 5 thousand 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.
Palo Alto, CA: Intro to Julia Tutorial with Julia Computing, Stanford Society of Women Engineers and Stanford Women in Computer Science at Stanford University Feb 5
Global (YouTube): Intro to Solving Differential Equations in Julia with Chris Rackauckas and Julia Computing Feb 6
Berkeley, CA: Intro to Julia with Julia Computing and FEMTech Berkeley at University of California - Berkeley Feb 6
Irvine, CA: SoCal Julia Meetup Feb 8
Bangalore, India: Code the Data Science Web App Using Julia Feb 10
Cambridge, MA: Intro to Julia Tutorial with Julia Computing and Harvard Society of Black Scientists and Engineers at Harvard University Feb 12
Waltham, MA: Intro to Julia Tutorial with Julia Computing at Brandeis University Feb 13
Phoenix, AZ: ARPA-E Energy-Smart Farm Workshop with Julia Computing Feb 13-14
Boston, MA: Intro to Julia Tutorial with Julia Computing and Boston University’s Women in Astronomy Lunch Association at Boston University Feb 14
Global (YouTube): Intro to Julia Tutorial with Julia Computing Feb 15
Boston, MA: Intro to Julia Tutorial with Julia Computing and Simmons College Math and Computer Science Liaison at Simmons College Feb 16
Northampton, MA: Intro to Julia Tutorial with Julia Computing and Smithies in Computer Science at Smith College Feb 17
London Meetup, UK: Bouncy Particle Sampler and Visual Studio Code Feb 19
Boston, MA: Intro to Julia Tutorial with Julia Computing and Northeastern University Graduate Women in Science and Engineering at Northeastern University Feb 19
Lorient, France: ROADEF 2018 Julia, JuMP for Operations Research Feb 21-23
Warsaw: Obliczenia Równolege w Julia Feb 27
Berlin: Nonsmooth Optimization Using Proximal Algorithms in Julia Feb 27
Global (YouTube): Intro to JuliaDB with Julia Computing Feb 28
Columbus, OH: Intro to Julia Tutorial with Julia Computing and the Ohio State University Association of Computing Machinery Committee on Women at Ohio State University Feb 28
Granville, OH: The Two Language Problem: Why it Matters for Data Scientists and How Julia Solves It with Julia Computing and Data Analytics at Denison University at Denison University Mar 1
Granville, OH: Intro to Julia Tutorial with Julia Computing and Data Analytics at Denison University at Denison University Mar 2
Chicago, IL: Intro to Julia Tutorial with Julia Computing, University of Chicago Association of Computing Machinery Committee on Women at the University of Chicago Mar 9
Washington, DC: ARPA-E Energy Innovation Summit with Julia Computing March 13-15
Exeter, UK: Go, Julia and Expanding Your Toolbox March 14
San Francisco, CA: Introduction to Julia for Data Analytics with Julia Computing at University of San Francisco School of Management Mar 23
Mexico City, Mexico: Intro to Julia for Engineers with Julia Computing at Universidad Panamericana Apr 23-27
London, UK: JuliaCon 2018 Aug 7-11
Please contact us if you wish to:
Julia is the fastest high performance open source computing language for data, analytics, algorithmic trading, machine learning, artificial intelligence, and many other domains. 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. For example, Julia has run at petascale on 650,000 cores with 1.3 million threads to analyze over 56 terabytes of data using Cori, the world’s sixth-largest supercomputer. With more than 1.8 million downloads and +101% annual growth, Julia is one of the top programming languages developed on GitHub. Julia adoption is growing rapidly in finance, insurance, machine learning, energy, robotics, genomics, aerospace, medicine and many other fields.
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. Julia Computing offers the following products:
To learn more about how Julia users deploy these products to solve problems using Julia, please visit the Case Studies section on the Julia Computing Website.
Julia users, partners and employers hiring Julia programmers in 2018 include Amazon, Apple, BlackRock, Booz Allen Hamilton, Capital One, Comcast, Disney, Ernst & Young, Facebook, Ford, Google, IBM, Intel, KPMG, Microsoft, NASA, Oracle, PwC, Uber, and many more.
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Julia Computing's mission is to create and deliver products that make Julia easy to use, easy to deploy and easy to scale. We operate out of Boston, London and Bangalore, and we serve customers worldwide.
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