November 16, 2022 – Cambridge, MA – We are pleased to announce that Julia Computing is now JuliaHub.
The JuliaHub platform is designed to accelerate the development and deployment of Julia programs by technical users in a variety of engineering and computational disciplines. JuliaHub makes it easy for Julia users to explore the open source ecosystem to create, share and manage packages, to leverage parallel computing and GPUs for large-scale computations, and to serve Julia applications through web APIs. In addition to being a general purpose platform, JuliaHub also provides a suite of vertical domain-specific products that leverage this platform, including JuliaSim, Pumas, PumasQSP and Cedar. JuliaHub is cloud-first but is also available on-prem and even air-gapped.
“JuliaHub has become the heart of our business and strategy, to the extent that people in the Julia community often think the company is already named JuliaHub. It only makes sense to rename the company to reflect that focus and direction,” explains Stefan Karpinksi, Julia co-creator and JuliaHub co-founder and Chief Product Officer.
What isn’t changing?
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Our participation in the open source Julia project
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JuliaHub powers a game-changing, composable product suite for modeling and simulation. This includes Pumas and PumasQSP for drug development, JuliaSim for modeling and simulation of multi-physical systems, and Cedar for electronic design automation
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JuliaHub is led by the same co-founders: Dr. Viral Shah (CEO), Deepak Vinchhi (COO), Stefan Karpinski (CPO), Dr. Jeff Bezanson (CTO), Keno Fischer (CTO – R&D) and Dr. Alan Edelman (Chief Scientist)
About JuliaHub and Julia
JuliaHub is a fast and easy-to-use code-to-cloud platform that accelerates the development and deployment of Julia programs. JuliaHub users include some of the most innovative companies in a range of industries that include pharmaceutical, automotive, energy, manufacturing, and semiconductor companies.
Julia is a high performance open source programming language that powers computationally demanding applications such in modeling and simulation, drug development, design of multi-physical systems, electronic design automation, big data analytics, scientific machine learning, and artificial intelligence. 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 prestigious James H. Wilkinson Prize for Numerical Software and the Sidney Fernbach Award.
