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R&D 100: Oscars of Innovation

Scientific researchers, technology transfer professionals, entrepreneurs and visionary business professionals create the stories of technology commercialization success. Along the way to success awards are won for technology transfer efforts. Since 1978 LLNL has been winning R&D 100 Awards—the “Oscars of Innovation”. Winners each year represent the most revolutionary technologies recently recognized by the market.

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EXUDE Elite | 2024

“EXtreme-power, Ultra-low-loss, Dispersive Element” (EXUDE) technology makes use of Spectral Beam Combining (SBC) of fiber lasers to achieve higher power, exploiting the broad gain bandwidth to enable large numbers of fiber laser channels to be combined with near diffraction-limited beam quality. In the original EXUDE technology, many incoherent laser beams, each with a slightly different wavelength, are superimposed onto a single beam by reflection off of a delicate grating structure. The power in the resulting beam is the sum of the powers of the individual beams. 

Winners: LLNL: Hoang Nguyen (PI), Michael Rushford, Brad Hickman, Candis Jackson, James Nissen, Sean Tardif 
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UMap | 2024

Supercomputer applications face large, complex dataset problems from both the system (complex hierarchy, memory, and storage) and the workload. UMap is an open source user-level library that acts as a tier between the application, the complex datasets, and the system hierarchy.

UMap uniquely exploits the prominent role of complex memories in today’s servers and offers new capabilities to directly access large memory-mapped datasets. For high performance, UMap provides flexible configuration options to customize page handling to each application.

Winners: LLNL: Maya Gokhale (PI), Ivy Peng (now at KTH Royal Institute of Technology), Marty McFadden, Elena Green, Roger Pearce, Keita Iwabuchi, Karim Youssef 
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UnifyFS | 2024

The UnifyFS file system enables HPC science applications to perform I/O operations many times faster than they could with traditional methods. UnifyFS is an ephemeral (or temporary) file system that utilizes fast storage tiers on supercomputers to quickly store and access application data so that applications can produce their results in less time.

Winners: LLNL: Kathryn Mohror (PI), Cameron Stanavige, Chen Wang, Hariharan Devarajan, Ned Bass, Tony Hutter ORNL: Sarp Oral (PI), Michael Brim, Ross Miller, Seung-Hwan Lim, Feiyi Wang, Swen Boehm, Jenna DeLozier NCSA: Celso Mendes, Craig Steffen Former LLNL: Adam Moody, Danielle Sikich Former ORNL: Hyogi Sim, Joseph Moore 
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CANDLE: CANcer Distributed Learning Environment | 2023

CANDLE is an artificial intelligence-based computer code that brings together machine learning, deep learning and cancer research to accelerate the discovery of new cancer therapies and treatments. 

Winners: Argonne National Laboratory: Rick Stevens, Tom Brettin, Justin Wozniak, Emily Dietrich; Lawrence Livermore National Laboratory: Fred Streitz, Brian Van Essen; Oak Ridge National Laboratory: Gina Tourassi, John Gounley; Los Alamos National Laboratory: Tanmoy Bhattacharya, Jamal Mohd Yusof; Frederick National Laboratory for Cancer Research: Eric Stahlberg
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Variorum: Vendor-Agnostic Computing Power Management | 2023

Pushing supercomputers to their limits requires a deeper understanding of power and energy than standard software and operating systems allow. Variorum provides robust interfaces that measure and optimize computation at the physical level: temperature, cycles, energy, and power. With Variorum, administrators and users can efficiently and effectively use computing resources.

Learn more: https://computing.llnl.gov/projects/variorum

Winners: LLNL: Tapasya Patki, Stephanie Brink, Barry Rountree, Eric Green, Kathleen Shoga, Aniruddha Marathe.
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ZFP: Fast, Accurate Data Compression for Modern Supercomputing Applications | 2023

The zfp software library provides a comprehensive solution to both lossy and lossless data compression. zfp reduces the storage space of high-precision floating-point data without sacrificing accuracy. It was designed to be a compact number format for storing data arrays in-memory in compressed form while supporting high-speed random access.

Learn more: https://computing.llnl.gov/projects/zfp

Winners: LLNL: Peter Lindstrom, Danielle Asher, Stephen Herbein, Matthew Larsen, Mark Miller, Markus Salasoo
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HELD Gratings: High Energy Low-Dispersion (HELD) Multilayer Dielectric (MLD) Gratings for Ultrafast Laser Systems | 2022

HELD Gratings, a novel design of multi-layer dielectric pulse compression gratings, enables a new class of high-energy, 10 PW ultrafast laser systems for extremely high and unprecedented peak power. Meter-scale HELD Gratings have the potential to facilitate future 100 PW-class ultrafast laser systems.

Winners: LLNL: Hoang T. Nguyen, Brad Hickman, Candis Jackson, James Nissen, Sean Tardif; National Energetics: Erhard Gaul; Institute of Physics of the Czech Academy of Sciences: Daniel Kramer and Irena Havlíčková
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Multifunctional, 3D-Printable Inks for Energy Products (Energy Inks) | 2022

Energy Inks meet 3D printing material flow conditions while optimizing functional properties of the extruded material, requirements difficult to obtain simultaneously. Such functional inks enable the design of customizable, easily integrated components, and, therefore, next-generation high-performance energy devices including those not possible to produce using current methods.

Winners: LLNL: Marcus Worsley and Swetha Chandrasekaran; MilliporeSigma: Adam Raw and Monica Jung de Andrade | Collaborative support- UC Santa Cruz: Yat Li and Dun Lin; LLNL: Patrick Campbell, Maira Ceron-Hernandez, Alyssa Troksa, Josh Kuntz, and Wyatt Du Frane.
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Tailored Glass Using Direct Ink Writing Technology | 2022

Tailored Glass by DIW augments Direct Ink Writing additive manufacturing to print silica-based optics and glass components with customizable forms and spatially varying material properties. Flow of multiple glass-forming inks is finely controlled to achieve the desired structure and optical properties. Subsequent heat treatment renders a dense, transparent glass product.

Winners: LLNL: Rebecca Dylla-Spears, Du Nguyen, Nikola Dudukovic, Koroush Sasan, Jungmin Ha, Timothy Yee, Rebecca Walton, Tyler Fears, Megan Ellis, Michael Johnson, and Oscar Herrera
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Flux: A Fully Hierarchical Workload Manager for Supercomputing Workflows | 2021

Flux is a next-generation workload management software framework for high-performance computing (HPC). It combines fully hierarchical resource management with graph-based scheduling to improve the performance, portability, flexibility, and manageability of scheduling and execution of complex scientific workflows on HPC systems both at the system and user level.

 

Winners: LLNL: Dong H. Ahn, Albert Chu, Jim Garlick, Mark Grondona, Stephen Herbein, Daniel Milroy, Christopher Moussa, Tapasya Patki, Thomas R.W. Scogland, Becky Springmeyer; University of Tennessee, Knoxville: Michela Taufer    
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Multiplicity Counter for Thermal and Fast Neutrons (MC-TF) | 2021

The Multiplicity Counter for Thermal and Fast Neutrons (MC-TF) is a field-deployable device that first responders can use to quickly assess in real-time and with high confidence the threat level posed by a suspected nuclear weapon. The MC-TF is designed to detect time-correlated fast and thermal neutrons unique to special nuclear material (SNM); the core of a nuclear weapon.

Winners: LLNL: Dr. Sean Walston; Radiation Monitoring Devices: Jaroslav Glodo, Joshua Tower, Charles Sosa; JHUAPL: Dr. William Noonan; DTRA: Dr. Hongguo (Hank) Zhu
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Optical Transconductance Varistor – Revolutionizing the Smart Grid | 2021

The Optical Transconductance Varistor (OTV) is a light-triggered semiconductor power switch enabling higher switching speeds than competitors at previously unattainable voltages to facilitate more efficient grid-scale power conversion, reduce expensive, environmentally-damaging energy losses, and generate the voltages required for medical proton therapy or air disinfection.

Winners: LLNL: Lars Voss. Paulius Grivickas, Adam Conway, Mihail Bora, George Caporaso, Hoang Nguyen, Lisa Wang, Dave Palmer, Craig Brooksby, Brad Hickman, Steve Hawkins, Rebecca Nikolic, Eric Strang; Opcondys: Kristin Sampayan, Steve Sampayan