February 16, 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 with a Why We Use Julia, 10 Years Later retrospective. So far, nearly 100 Julia users from a wide range of backgrounds including data science, finance, robotics, pharmaceuticals, neuroscience, entomology, quantum physics, astronomy, environmental science and energy have each contributed a short paragraph (or more) about how they came to use Julia, why they use Julia to replace Python, C, C++, Fortran, MATLAB, SAS and R, what they have accomplished using Julia and why they continue to love the language.
Originally developed at MIT, the free and 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 6,800+ registered packages. Over 1,500 universities worldwide are using and teaching 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 US Federal Reserve and every US national energy laboratory.
Selected highlights from Why We Use Julia, 10 Years Later include:
“Come for the speed, stay for the community.” Elliot Saba
“5 years ago, in a first for a dynamic language, we pushed Julia over the Petaflop barrier (a feat that is much easier now ;)) running more than a million simultaneous threads of Julia on one of the world’s largest computers.” Keno Fischer
“The code was so clean and nice 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 Sanders
“I stumbled into Julia while trying to do a crazy data transformation in R that was taking forever. I was instantaneously hooked! The syntax is so easy …” Jose Storopoli
“I am tremendously grateful to have come across the language, as well as its community and all the wonderful people that have helped me on this journey. It is not an exaggeration to say that much of my career successes I owe to the language.” George Datseris
“I remember working on an R script that needed to loop through 33 million rows of data, doing a complicated … computation that would take 18 hours to run. Literally during one of these 18 hour runs, I saw the Julia announcement post and was immediately desperate for the kind of simple performance it promised. I read the initial manual over a weekend, rewrote my script the following Monday morning, and it ran in 5 minutes. I thought for sure I had made some kind of early termination mistake, but no, it was really just that fast.” Jacob Quinn
“Best programming decision I ever made :)” Simon Danisch
“I would not be surprised, if, within the next 10 years, Julia is dubbed ‘the language of science’.” Ranjan Anantharaman
“Using Julia is one of the best choices I made concerning my numerics and code development.” Ronny Bergmann
“Without the Julia community it is unlikely I would have completed my PhD (and I certainly wouldn't have my current job).” Frames Catherine White
“This language is awesome.” Tobias Knopp
“Since 2019 I do all my coding in Julia, I love the syntax, I do not miss R at all.” Arturo Erdely
“I was hooked. Almost 3 years later I've found that Julia has been my go-to language for nearly everything. The ease of use, speed and community keep bringing me back for more.” Matt Brzezinkski
“Julia is the language I was longing 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 awesome and amazing!” Qingyu Qu
About Julia and Julia Computing
Julia Computing's mission is to develop products that bring Julia's superpowers to its customers. Julia Computing's flagship product is JuliaHub, a secure, software-as-a-service platform for developing Julia programs, deploying them, and scaling to thousands of nodes. It provides the power of a supercomputer at the fingertips of every data scientist and engineer. In addition to data science workflows, JuliaHub also provides access to cutting-edge products such as Pumas for pharmaceutical modeling and simulation, JuliaSim for multi-physics modeling and simulation, and Cedar for electronic circuit simulation, combining 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 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 by users at more than 10,000 companies 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 and the 2019 Sidney Fernbach Award. 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.