The company, which was founded by the creators of the Julia high-performance programming language, says the funding will be used to further develop and advance its secure, high-performance JuliaHub cloud platform and to grow the Julia ecosystem. JuliaHub makes it easy to develop, deploy, and scale Julia programs and models that data scientists and engineers are adopting at an increasingly rapid pace.
In addition to being a cloud computing product in its own right, says the company, JuliaHub is a platform for other revolutionary applications, such as JuliaSim for multi-physics simulation, JuliaSPICE for circuit simulation, and Pumas for pharmaceutical simulation product from Julia Computing’s partner company, Pumas-AI.
“The wonders of today’s world are created using digital models,” says Bob Muglia, member of the Julia Computing Board of Directors. “The circuits within our smartphones, advanced materials, pharmaceuticals, and aeronautics are all examples of advanced technologies built using digital modeling. Although these advancements have been amazing, the tools and systems that support these efforts are decades-old and cannot take full advantage of the cloud.”
“The Julia Computing team has rocked this world by building JuliaHub, a modern platform for technical and scientific modeling,” says Muglia. “JuliaHub is poised to advance scientific computing and enable solutions that will deliver new generations of products and services that we cannot even imagine today.”
Originally developed at MIT, the Julia programming language has been downloaded more than 29 million times by users worldwide, including thousands of open source developers who have contributed to Julia and its 6,000 registered packages. Over 1,500 universities worldwide are using and teaching Julia, including leading institutions such as MIT, Stanford, and UC Berkeley.
The community has seen exponential growth since Julia was introduced to the public in 2012, says the company. Julia helps scientists and engineers tackle large-scale data science problems, and solves the “two-language problem” by eliminating the two-step process of testing, modeling, and prototyping in a high-level language (such as Python, Matlab, or R), and then rewriting in a second, faster lower-level language (such as C or C++) for production and scaling.
“Technical computing is stuck in a rut today,” says Viral Shah, co-founder and CEO of Julia Computing and co-creator of Julia. “Data scientists and engineers are using products that were designed many decades ago. JuliaHub makes it possible to design new drugs and therapies, develop new batteries, simulate a space mission, and map out the universe, all while using fewer computing resources and reducing data center emissions. We truly are defining the future of data science and simulation, and it is thrilling to help drive these exciting innovations. Reinforced by our latest funding, we look forward to scaling our team and bringing Julia’s superpowers to more industries and applications.”
The fundraising round was led by Dorilton Ventures, with participation from Menlo Ventures, General Catalyst, and HighSage Ventures.
Daniel Freeman, who led the Dorilton Ventures investment, adds, “We are excited to lead this important round and partner with Julia Computing. Julia Computing is at the very center of technical computing, a substantial global market with significant barriers to entry. Julia’s machine learning and AI technologies make it possible to simulate rather than approximate, changing the economics of computational analysis and scientific discoveries. This is a truly transformative business with high potential for success.”
JuliaCon, an annual gathering for the Julia community, takes place July 28-30, and is online and free for everyone this year.
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