Prague, Czech Republic – Julia Computing’s Avik Sengupta (VP Engineering) and Coillte’s Kevin O’Brien (Forestry Resource Modeller) will lead a workshop on “Machine Learning in Julia” at the Machine Learning Prague conference on March 20, 2020.
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 works with GPUs, TPUs, multithreading and parallel processing to deliver seamless unlimited scalability from a single CPU to thousands of nodes, cores and threads in the public or private cloud. Julia has run at petascale on 9,300 Knights Landing (KNL) nodes with 650,000 cores and 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 has been downloaded more than 13 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 is used by hundreds of firms worldwide in engineering, biotechnology, pharmaceutical research, aviation, manufacturing and medicine for image and pattern recognition, flight path planning, risk analysis, optimization and more. Examples include:
Path BioAnalytics: Path BioAnalytics is a computational biotech company using precision medicine for drug discovery and development and treatment of disease. By switching to Julia, Path BioAnalytics decreased computation 65x, increased accuracy 55% and significantly reduced their code base.
Lincoln Labs: Lincoln Labs works with the US Federal Aviation Administration (FAA) to develop and deploy the next generation Airborne Collision Avoidance System (ACAS-X). They use Julia to compute 650 billion decision points within an optimized logic table to identify failures. Julia reduced the time required to conduct these computations by several years.
Brazilian National Institute for Space Research: Brazil’s space mission planning research institute uses Julia to plan space missions. They leverage Julia’s superior speed and ease of use to build a simulator, create multidisciplinary design optimization (MDO) tools for space mission planning and design a attitude and orbit control subsystem (AOCS).
Contextflow: Contextflow uses Julia for artificial intelligence to search and analyze medical images to improve the speed and accuracy of medical diagnosis and treatment. Julia reduced the time required for image searching from up to 20 minutes to less than 2 seconds.
Aviva: One of Europe’s largest insurers uses Julia for risk analysis, including Solvency II compliance. According to Tim Thornham, Aviva’s Director of Financial Modeling, “Solvency II compliant models in Julia are one thousand times faster, use 93% fewer lines of code and took one-tenth the time to implement” compared with their legacy system.
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