Newsletter February 2019

Julia Computing is pleased to announce the launch of
JuliaAcademy, the new Julia Computing
training platform for 3 types of learning: self-directed, online
instructor-led and in-person onsite training.

JuliaAcademy courses include: Intro
to Julia, Machine Learning and Artificial Intelligence in Julia,
Parallel Computing in Julia, Deep Learning with Flux, Optimization with
JuMP and Machine Learning with Knet.

JuliaAcademy provides:

  1. Self-directed training – all online, learn at your own pace

  2. Instructor-led online training – live two-day courses taught by Julia Computing instructors

  3. In-person training – contact us at info@juliacomputing.com to schedule customized in-person training for your organization

Register now for instructor-led online courses:

JuliaTeam:
JuliaTeam is an
enterprise solution that makes it as easy to use and develop Julia
packages inside your company as it is in the open source world. The
current release of JuliaTeam integrates with your corporate
authentication systems and eliminates the headaches of installing and
using public Julia packages behind a corporate firewall. JuliaTeam also
gives IT and management insight and control over what packages
developers are using, helping ensure quality and security.

Upcoming
JuliaTeam
releases will include these features as well:

  • Read and search docs for all internal and external packages in a single place

  • Create and manage private package registries

  • Publish and test private packages as easily as public ones, making sure new versions work seamlessly with all the other versions of packages that your teams are using

  • Benchmark your code to make sure it runs as efficiently as possible and stays fast

  • Download a summary of licenses of all the software you depend on

JuliaTeam makes
Julia development at your company as easy, effective and fun as open
source.

For more information, contact us.

Julia Ranks #4 Top Machine Learning Language on GitHub:
GitHub
reports that Julia ranks #4 on the list of the top machine learning
projects by contribution and #6 on the list of top machine learning
languages on GitHub.

Julia for Medicine: MIT
News
reports that the Julia Lab at MIT is working with the University of
Maryland School of Pharmacy and other partners to speed drug approval
using patient health data and sophisticated data analysis.

JuliaCon 2019: JuliaCon 2019 will be
held July 22-26 at the University of Maryland, Baltimore. Call for
Proposals and Early Bird Ticket
Sales are open now.

JuMP-dev Annual Workshop: The third annual JuMP-dev
workshop takes place
March 12-14 in Santiago, Chile.
Registration
is free and talk proposal
submissions
are encouraged.

Julia and Julia Computing in the News

  • PLOS: “[I]t is encouraging to see several contributions describing open-source tools in this field, including a comprehensive package in Julia”

  • ZDNet: “Other big movers include … MIT-created up-and-comer Julia, which was up from 47th last January to 37th today.”

  • SD Times: “Other interesting positive moves of 2018 [include] … Julia (#47 to #37)”

  • House of Bots: “Julia programming language is fastest growing … charts rapid rise in 2018-19”

  • SIAM News: “Jeff Bezanson, Stefan Karpinski, and Viral B. Shah of Julia Computing are the 2019 recipients of the James H. Wilkinson Prize for Numerical Software.”

  • Heise: Julia-Sprachschöpfer Erhalten James H. Wilkinson Prize for Numerical Software

  • HPC Wire: “Julia can offer high performance at scale using hundreds of thousands of processor cores for compute.”

  • MIT News: “Julia Lab joins team to speed up drug approval process”

  • Outsourcing Pharma: “The Health Analytics Collective will be led by the Julia Lab”

  • GitHub: “Julia, R, and Scala all appear in the top 10 for machine learni)g projects”

  • HackerRank 2019 Developer Skills Report: 11.5% of developers want to learn Julia in 2019

  • ZDNet: “Julia … made its public debut in 2012 and over the past year has quickly climbed the ranks of the world’s most popular languages.”

  • JAXenter: “TensorFlow, Python, and Julia helped make 2018 the year of machine learning on GitHub”

  • DevClass: “Julia devs keep up momentum with 1.1 release”

  • SDTimes: “Julia 1.1 has been officially released”

  • ZDNet: “Downloads of Julia have grown 78% since January 2018, from 1.8 million to 3.2 million downloads”

  • DevClass: “Julia, R, and Scala all appear in the top 10 for machine learning projects”

  • JAXenter: “Solve differential equations with new Julia library”

  • Solutions Review: The Julia data ecosystem lets you load multidimensional datasets, perform aggregations, joins and preprocessing operations in parallel, and save them to a disk. Julia has foreign function interfaces for C/Fortran, C++, Python, R, and Java, and it can be embedded into other programs through an embedding API. The language works with an array of databases and integrates with the Hadoop ecosystem as well.”

  • Heise: “Julia 1.1 ist fertiggestellt”

  • Devellopez: “Le langage de programmation Julia gagne de plus en plus en popularité au sein de la communauté scientifique”

  • Analytics Insight: “Julia combines the functionality from different well-known languages like Python, R, Matlab, SAS and Stata with the speed of C++ and Java.”

  • InsideHPC: “One of my favorites is Julia language. It has a wonderful interface to GPUs via the JuliaGPU project. Unlike Python, it doesn’t have a GIL, as it is compiled and built for parallelism, nor does it have structure by indentation. It has a native GPU compiler built in to its LLVM stack, meaning that it can optimize not merely for the CPUs, but also for the GPUs. It is rapidly maturing, so there are a few rough spots, but I expect tools like this to become more standard for HPC applications.”

  • VentureBeat: Top machine learning projects on GitHub: #4 Julia

  • iProgrammer: Data science with Julia

  • TechNotification: Top Five New Programming Languages to Learn in 2019

  • FierceBiotech: “MMS teams with MIT’s Julia Lab and University of Maryland to create Health Analytics Collective”

  • TechRepublic: “Highly rated machine-learning repositories include Flux.jl, Knet.jl and Metalhead.jl”

  • House of Bots: “Highly rated machine-learning repositories include MachineLearning.jl, MLKernels.jl and LightML.jl”

Julia Blog Posts

Upcoming Julia Events

Recent Julia Events

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, Barnes & Noble, BlackRock, Capital One,
Charles River Analytics, Citigroup, Comcast, Cooper Tire & Rubber,
Disney, Facebook, Gallup, Genentech, General Electric, Google, Huawei,
Johnson & Johnson, Match, McKinsey, NBCUniversal, Nielsen, OKCupid,
Oracle, Pandora, Peapod, Pfizer, Raytheon, Zillow, Brown, Emory,
Harvard, Johns Hopkins, Massachusetts General Hospital, Penn State, UC
Davis, University of Chicago, University of Virginia, Argonne National
Laboratory, Lawrence Berkeley National Laboratory, Los Alamos National
Laboratory, National Renewable Energy Laboratory, Oak Ridge 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 JuliaAcademy, JuliaTeam, JuliaPro or JuliaBox

  • 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 3
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.