Julia Computing celebrates 10 years with a retrospective


February 18, 2022 – Boston, MA – Julia, the fastest and most productive high-level, high-performance programming language for data science, artificial intelligence, machine learning, modeling and simulation, reaches a new milestone this week – the tenth anniversary of Why We Created Julia, the launch announcement that introduced Julia to the world.

The Julia community is celebrating this with a retrospective “Why We Use Julia, 10 Years Later”. So far, nearly 100 Julia users from diverse fields including data science, finance, robotics, pharmacy, neuroscience, entomology, quantum physics, astronomy, environmental science, and energy have each contributed a short paragraph (or more) on how they got to Julia why they use Julia to replace Python, C, C++, Fortran, MATLAB, SAS and R, what they achieved with Julia and why they continue to love the language.

Originally developed at MIT, the free, open-source Julia programming language has been downloaded more than 35 million times, including by thousands of open-source developers who have contributed to Julia and its over 6,800 registered packages. Over 1,500 universities worldwide use and teach Julia, including MIT, Stanford, and UC Berkeley. Companies and organizations using Julia include Amazon, Apple, AstraZeneca, Capital One, FAA, Google, IBM, Intel, JP Morgan, Microsoft, Moderna, NASA, Pfizer, Uber, the Federal Reserve and every national energy laboratory USA.

Select highlights from Why We Use Julia, 10 Years Later include:

“Come for speed, stay for community.” – Elliot Saba

“5 years ago we pushed Julia over the petaflop barrier for the first time for a dynamic language (a feat much easier now ;)) by running more than a million threads of Julia at the same time on one of the largest computers in the world executed.” — Keno Fischer

“The code was so clean and beautiful compared to the horrible Python version! … Julia could easily run 50x faster than almost identical code in Python. From then on I was hooked.” – David Sander

“I stumbled upon Julia trying to do a crazy data transformation in R that took forever. I was instantly hooked! The syntax is so simple…” — Jose Storopoli

“I am incredibly grateful to have come across the language, as well as its community and all the wonderful people who have helped me on this journey. It is no exaggeration to say that I owe much of my professional success to language.” – George Datseris

“I remember working on an R script that had to loop through 33 million rows of data and perform a complicated… calculation that would take 18 hours to execute. Literally during one of those 18 hour runs, I saw the Julia announcement post and was immediately despondent for the kind of simple performance it promised. I read the original manual over a weekend, rewrote my script the following Monday morning, and it was up and running in 5 minutes. I was sure I had made some early exit mistake, but no, it really was that quick.” – Jakob Quinn

“Best programming decision I’ve ever made :)” — Simon Danisch

“I wouldn’t be surprised if Julia is called ‘the language of science’ within the next 10 years.” — Ranjan Anantharaman

“Using Julia is one of the best decisions I’ve made regarding my numerics and code development.” – Ronny Bergmann

“I probably wouldn’t have completed my PhD (and I certainly wouldn’t have my current job) without the Julia community.” – Frames Catherine White

“This language is great.” – Tobias Knopp

“Since 2019 I’ve been doing all my programming in Julia, I love the syntax, I don’t miss R at all.” – Arthur Erdely

“I was hooked. Almost 3 years later, I found that Julia was my language of choice for almost everything. The ease of use, speed, and community keep bringing me back.” – Matt Brzezinkski

“Juliet is the language I’ve longed for.” — Cristóvão Sousa

“In 2020 I switched my work code to Julia and have never looked back since.” – Jakob Nissen

“Julia is the perfect language for scientific computing and beyond.” – Mark Kittisopikul

“The performance is great and amazing!” — Qingyu Qu

About Julia and Julia Computing

Julia Computing’s mission is to create products that bring Julia’s superpowers to their customers. Julia Computing’s flagship product is JuliaHub, a secure software-as-a-service platform for developing Julia programs, deploying them, and scaling them to thousands of nodes. It offers the power of a supercomputer for every data scientist and engineer. In addition to data science workflows, JuliaHub also provides access to top-of-the-line products such as Pumas for pharmaceutical modeling and simulation, JuliaSim for multiphysics modeling and simulation, and Cedar for electronic circuit simulation, which combine traditional simulation with modern SciML approaches.

Julia is the fastest, high-performance, open-source computing language for data, analytics, algorithmic trading, machine learning, artificial intelligence, and other scientific and numerical 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 out-of-the-box parallel computing capabilities and unlimited scalability with minimal effort. Julia has been downloaded by users in more than 10,000 companies and is used in more than 1,500 universities. Julia’s co-creators are the winners of the 2019 James H. Wilkinson Prize for Numerical Software and the 2019 Sidney Fernbach Prize. Julia ran at peta scale on 650,000 cores with 1.3 million threads to over 56 terabytes of data with Cori, one of the ten largest and most powerful supercomputers in the world.

Source: Julia Computing


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