Topic: Data Science

According to DOE secretary Rick Perry, "Accelerating artificial intelligence and machine learning is crucial to strengthening our country’s economic and national security."

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LLNL’s Center for Applied Scientific Computing looks back at 2018 papers, presentations, and other activities recognizing research and innovation in data science.

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For the 2nd straight year, LLNL's HPC Innovation Center hosted to a Women in Data Science (WiDS) regional event, drawing dozens of attendees from LLNL, local universities, and other Bay Area labs.

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With nearly 100 publications, CASC researcher Jayaraman “Jay” Thiagarajan explores the possibilities of artificial intelligence and machine learning technologies.

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Held in Washington, DC, the Earth System Grid Federation’s 8th annual face-to-face conference was a lively, fruitful affair.

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LLNL employees attended a five-part “Deep Learning 101” course, which introduced the basics of neural networks and machine learning to anyone with a basic knowledge of programming in Python.

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Highlights include CASC director Jeff Hittinger's vision for the center as well as recent work with PruneJuice DataRaceBench, Caliper, and SUNDIALS.

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Rushil Anirudh describes the machine learning field as undergoing a “gold rush.”

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AIMS (Analytics and Informatics Management Systems) develops integrated cyberinfrastructure for big climate data discovery, analytics, simulations, and knowledge innovation.

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Marisa Torres, software developer with LLNL’s Global Security Computing Applications Division, combines her love of biology with coding.

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Highlights include Computation’s annual external review, machine learning for ALE simulations, CFD modeling for low-carbon solutions, seismic modeling, and an in-line floating point compression tool.

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SOAR (Stateless, One-pass Adaptive Refinement) is a view-dependent mesh refinement and rendering algorithm.

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Highlights include the HYPRE library, recent data science efforts, the IDEALS project, and the latest on the Exascale Computing Project.

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At just 5 years old, Marisol Gamboa, the oldest of six siblings to Mexican immigrants, decided she was definitely going to college.

People Highlight

LibRom is a library designed to facilitate Proper Orthogonal Decomposition (POD) based Reduced Order Modeling (ROM).

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Newly developed mathematical techniques reveal important tools for data mining analysis.

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By applying and extending ideas from data mining, image and video processing, statistics, and pattern recognition, we are developing a new generation of computational tools and techniques that are being used to improve the way in which scientists extract useful information from data.

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The sheer size of data poses significant problems in all stages of the visualization pipeline, from offline pre-processing of simulation data, to interactive queries, to real-time rendering. Moreover, visualization data is often unstructured in nature, which further complicates its management and representation. The goal of this project is to develop techniques for reducing bandwidth requirements for large unstructured data, both explicitly, by making use of data compression, and implicitly, by optimizing the layout of the data for better locality and cache reuse.

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New platforms are improving big data computing on Livermore’s high performance computers.

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The Earth System Grid Federation is a web-based tool set that powers most global climate change research.

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LLNL computer scientists use machine learning to model and characterize the performance and ultimately accelerate the development of adaptive applications.

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Researchers are developing enhanced computed tomography image processing methods for explosives identification and other national security applications.

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LLNL and University of Utah researchers have developed an advanced, intuitive method for analyzing and visualizing complex data sets.

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zfp is an open-source C/C++ library for compressed floating-point and integer arrays that support high throughput read and write random access.

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