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Julia Computing Awarded Funding in the ARPA-E DIFFERENTIATE Program

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Julia Computing Awarded Funding in the ARPA-E DIFFERENTIATE Program

Julia Computing Awarded Funding in the ARPA-E DIFFERENTIATE Program

Julia Computing Awarded Funding in the ARPA-E DIFFERENTIATE Program

Date Published

Dec 9, 2019

Dec 9, 2019

Contributors

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Date Published

Dec 9, 2019

Contributors

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Cambridge, MA – Julia Computing has been awarded funding by the US Department of Energy Advanced Research Projects Agency-Energy (ARPA-E) to “develop a neural component machine learning tool to reduce the total energy consumption of heating, ventilation and air conditioning (HVAC) systems in buildings.”

Funding was awarded as part of the Design Intelligence Fostering Formidable Energy Reduction and Enabling Novel Totally Impactful Advanced Technology Enhancements (DIFFERENTIATE) program.

According to the US Department of Energy, “As of 2012, buildings consume 40 percent of the nation’s primary energy, with HVAC systems comprising a significant portion of this consumption. It has been demonstrated that the use of modeling and simulation tools in the design of a building can yield significant energy savings—up to 27 percent of total energy consumption. However, these simulation tools are still too slow to be practically useful. Julia Computing seeks to improve upon these tools using the latest computing and mathematical technologies in differentiable programming and composable software to enhance the ability of engineers to design more energy efficient buildings.”

Julia Computing CEO Viral Shah further explains, “Differentiable programming represents a broad generalization of AI technologies. This capability of combining scientific insights with learning from data will make it possible for Julia to improve the design processes that lead to energy savings across the board.”

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 11 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 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.

Julia Computing was founded in 2015 by all the creators of Julia to provide products including JuliaTeamJuliaSure and JuliaRun to businesses and researchers using Julia.

Authors

JuliaHub, formerly Julia Computing, was founded in 2015 by the four co-creators of Julia (Dr. Viral Shah, Prof. Alan Edelman, Dr. Jeff Bezanson and Stefan Karpinski) together with Deepak Vinchhi and Keno Fischer. Julia is the fastest and easiest high productivity language for scientific computing. Julia is used by over 10,000 companies and over 1,500 universities. Julia’s creators won the prestigious James H. Wilkinson Prize for Numerical Software and the Sidney Fernbach Award.

Authors

JuliaHub, formerly Julia Computing, was founded in 2015 by the four co-creators of Julia (Dr. Viral Shah, Prof. Alan Edelman, Dr. Jeff Bezanson and Stefan Karpinski) together with Deepak Vinchhi and Keno Fischer. Julia is the fastest and easiest high productivity language for scientific computing. Julia is used by over 10,000 companies and over 1,500 universities. Julia’s creators won the prestigious James H. Wilkinson Prize for Numerical Software and the Sidney Fernbach Award.

Authors

JuliaHub, formerly Julia Computing, was founded in 2015 by the four co-creators of Julia (Dr. Viral Shah, Prof. Alan Edelman, Dr. Jeff Bezanson and Stefan Karpinski) together with Deepak Vinchhi and Keno Fischer. Julia is the fastest and easiest high productivity language for scientific computing. Julia is used by over 10,000 companies and over 1,500 universities. Julia’s creators won the prestigious James H. Wilkinson Prize for Numerical Software and the Sidney Fernbach Award.

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