Newsletter December 2019

NVIDIA announced that Julia is “now available through containers for x86 and Arm” and “can be used for GPU programming by writing CUDA kernels in Julia or by using the powerful array programming model.” For more information, please read “Julia Computing and NVIDIA Bring GPU Computing to Arm.”

US Department of Energy Advanced Research Projects Agency-Energy (ARPA-E) has awarded funds to Julia Computing to “develop a neural component machine learning tool to reduce the total energy consumption of heating, ventilation and air conditioning (HVAC) systems in buildings.” Funding was awarded as part of the Design Intelligence Fostering Formidable Energy Reduction and Enabling Novel Totally Impactful Advanced Technology Enhancements (DIFFERENTIATE) program.

Julia Computing’s Alan Edelman Receives Sidney Fernbach Award at SC19 from Institute of Electrical and Electronics Engineers (IEEE): Alan Edelman was awarded the Sidney Fernbach Award for “outstanding breakthroughs in high-performance computing, linear algebra, and computational science and for contributions to the Julia programming language.” Alan is co-creator of Julia, co-founder and Chief Scientist at Julia Computing, director of the Julia Lab at MIT and Professor of Applied Mathematics at MIT. Alan accepted the award at SC19 in Denver, Colorado.

Julia Computing Enterprise Solutions: Contact Julia Computing for more information about putting Julia to work for your organization, deploying Julia more efficiently, effectively and at scale.

  • JuliaSure:: JuliaSure provides enterprise support and indemnity for organizations: using Julia.

  • JuliaTeam: JuliaTeam provides enterprise governance including private and package development, deployment, management, security, support and indemnity.

  • JuliaRun: JuliaRun allows you to scale Julia deployment from a single machine to dozens or hundreds of nodes in a public or private cloud environment, including AWS, Azure or Google Cloud.

Julia Computing Webinar on Private Package Management and Governance with Julia: Please register to participate in a Julia Computing Webinar on Private Package Management and Governance with Julia. The Webinar is led by Julia Computing Senior Research Scientist Matt Bauman and takes place on Wed Dec 4 from 12-1 pm EST.

JuliaBox 30 Day Free Trial: JuliaBox is now available with a 30 day free trial. JuliaBox is the fastest and easiest way to start using Julia right away with no download required. Register today to start your 30 day free trial.

JuliaBox Academic Discount: Hundreds of students and faculty at universities around the world use JuliaBox for classroom instruction and learning. Use free and open source materials to design your own course using Julia. JuliaBox starts at just $7 per month including a 50% academic discount. Sign up online or contact Julia Computing to take advantage of the academic discount or for more information.

Julia 1.3.0: Julia 1.3.0 has been released with a number of new features, including new multithreading capabilities. The release was featured on Hacker News. Click here to download and review release notes.

Machine Learning on Encrypted Data Without Decrypting It: Julia Computing co-founder and CTO (Tools) Keno Fischer published a blog post explaining how Julia can be used for machine learning using encrypted data without decryption. The blog post was featured on Hacker News.

Reliable and Reproducible Binary Artifacts for Julia Packages: Julia Computing’s Elliot Saba, co-founder and CTO (Open Source) Stefan Karpinski and Kristoffer Carlsson published a blog post about changes to the Julia package manager that make it easier to produce reliable and reproducible binary artifacts for Julia packages. This new feature is available as part of the Julia package manager for Julia v1.3.0 and subsequent versions.

AWS Provides Promotional Credits for Julia: Amazon Web Services (AWS) is providing promotional credits for Julia and other open source projects. Visit AWS Open Source for more information.

Julia Joins Google Code-In Contest: Julia has been selected by Google to participate in the Google Code-In program which introduces teens aged 13-17 around the world to open source development. If you know students, parents or teachers who may be interested, please direct them to Google Code-In for more information. Please read the blog post by Julia Computing VP Engineering Avik Sengupta and Logan Kilpatrick.

Julia Day in New York Video Now Available Online: Julia Computing’s Julia Day in New York took place a few weeks ago, and the videos are now available online.

  1. The Story of Julia with Julia Co-Creators and Julia Computing Co-Founders Viral Shah and Stefan Karpinski

  2. Julia Computing Products, Services and Training with Julia Computing VP Sales Jon Shepherd

  3. State Street Case Study with State Street’s Elton Pereira

  4. Conning Case Study with Conning Managing Director David Weiss

Tanmay Teaches Julia for Beginners: Tanmay Bakshi’s Tanmay Teaches Julia for Beginners is now available on Amazon. Tanmay Bakshi is a 15 year old author, AI/ML expert, TED speaker, IBM Champion for Cloud and Google Developer Expert for Machine Learning. His ‘Tanmay Teaches’ YouTube channel has 323 thousand subscribers.

New Julia Benchmarks vs. Python, Matlab and R: Chris Rackauckas published new reproducible benchmarks demonstrating Julia’s superior performance for ordinary differential equations (ODEs) compared with Python, Matlab and R.

Julia’s GPU Performance Benchmarked: Grant McDermott (University of Oregon) reports that Julia’s FixedEffectModels package with GPUs is ‘at least 2x faster than the next-best option’.

International Energy Agency (IEA) Benchmarks Julia: The International Energy Agency published Julia benchmarks demonstrating that Julia’s JuMP package is 400% faster than GNU Mathprog and 680% faster than Python’s Pyomo for energy modeling with the Integrated MARKAL-EFOM System (TIMES).

Julia Ranks #1 in 30, 60, 90 and 120 Day Growth on ModuleCounts.com: Julia ranked first in 30, 60, 90 and 120 day growth on ModuleCounts.com.

Julia for Medicine: Robert Gregg and Jason Shoemaker presented their use of Julia for agent-based modeling of the CGAS pathway at the American Institute for Chemical Engineers annual conference. Gregg and Shoemaker are researchers at the University of Pittsburgh Shoemaker Immunosystems Lab and this technique is used for detecting pathogenic DNA. The paper they presented is Quantifying the Impact of Cellular Heterogeneity on CGAS Pathway Regulation Using Multiscale Agent-Based Modeling.

JuliaNantes Video and Presentations: Presentations and video from the June 17, 2019 Journée Julia et Optimisation at l’Université de Nantes are now available online. Click here to view.

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 and Julia Computing in the News

  • PacktHub: Julia Computing Research Team Runs Machine Learning Model on Encrypted Data Without Decrypting It

  • InsideBigData: Julia – The Programming Language Of The Future

  • I-Programmer: Julia Improves Multithreading

  • JAXenter: Julia v1.3: Reproducible Results, Yggdrasil, & Multi-Threading Changes

  • Analytics India: Is Julia Finally Catching Up with Python & R?

  • DevClass: Julia 1.3 Offers Experimental Approach to Multi-Threading

  • HPCWire: Alan Edelman Wins Sidney Fernbach Award

  • ExecutiveBiz: Galois to Develop Secure Computing Tech Under IARPA Program

  • HostReview: Which Machine Learning Frameworks To Try In 2019-20

  • Nature: Make Code Accessible with these Cloud Services

  • InsideHPC: Deep Learning on Summit Supercomputer Powers Insights for Nuclear Waste Remediation

  • ScienceBlog: Deep Learning Expands Study Of Nuclear Waste Remediation

  • Finextra: The Non-Contradiction of Proprietary Finance and Community Open Source Programming

  • Towards Data Science: Artificial Intelligence & Deep Learning for Medical Diagnosis

  • BioSpace: MMS Holdings Doubles Growth in South Africa Region Amid Burgeoning Pharmaceutical Industry Locally

  • EurekAlert: Deep Learning Expands Study of Nuclear Waste Remediation

  • PacktHub: Julia v1.3 Released with New Multithreading Features, and Much More

  • ZDNet: Programming Languages – Python Overtakes Java on GitHub as Google Dart Use Soars

  • SD Times: News Digest – Amazon Announces Rekognition Custom Labs, Scala.js 1.0.0-RC1, and Julia 1.3

  • Analytics India: Python Just Overtook Java on GitHub, But How Did It Fare Overall?

  • CMU: CMU & Partners Receive ARPA-E Award for Machine Learning-Accelerated Discovery of Energy Materials

  • Tech India Today: 10 Best Programming Languages For Artificial Intelligence (AI) in 2020

  • Analytics India: Julia Computing Uses Homomorphic Encryption for ML. Is It the Way Forward?

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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 11 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.