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CRD Staff Receive Three Best Paper Awards in One Week
Several staff in the Computational Research Division’s Performance Algorithms Group were authors on research papers honored at three separate workshops in November. Read More »
Longtime Lab and Pioneering Data Scientist Frank Olken has Died
Frank Olken, a data scientist who spent 36 years at Berkeley Lab tackling the challenge of big data before it became Big Data, died Oct. 18 at age 67. He also worked two stints as a National Science Foundation (NSF) program director in Arlington, Va. Read More »
Jackie Yao, Berkeley Lab’s 2019 Alvarez Fellow
Jackie Yao recently joined CRD as Berkeley Lab’s 2019 Luis W. Alvarez Fellow in Computing Sciences. Her research is focused on developing unprecedented numerical modeling to solve complex multiphysics problems involving electromagnetics, nonlinear magnetics, and acoustics. Read More »
NWB:N Gains Traction in the Neuroscience Community
Berkeley Lab developed Neurodata Without Borders: Neurophysiology, a data standard for neurophysiology research and a software ecosystem that allows neuroscientists to share, archive, use, and build tools for analyzing data, is gaining traction in the neuroscience community. Read More »
Machine Learning Algorithms Help Predict Traffic Headaches
A team of Berkeley Lab computer scientists is working with the California Department of Transportation and UC Berkeley to use high performance computing and machine learning to help improve Caltrans’ real-time decision making when traffic incidents occur. Read More »
Neurodata Without Borders Project Wins 2019 R&D100 Award
Led by Berkeley Lab in collaboration with the Allen Institute for Brain Science and multiple neuroscience labs, the NWB:N project has created a data standard and software ecosystem that is transforming neurophysiology research. Read More »
CRD’s Zhe Bai Selected as a WHPC 2019 Fellow
Zhe Bai, a postdoctoral scholar in the Computational Research Division, has been selected by the Women in HPC organization as a 2019 Fellow. Read More »
Berkeley Lab Part of Two Five-Year, Multi-Million Dollar Quantum Computing Projects
With new funding from the U.S. Department of Energy, Berkeley Lab will lead one project - with CRD's Bert de Jong as the PI - and co-lead the other. Read More »
SMART Algorithm Makes Beamline Data Collection Smarter
CAMERA researchers have been working with beamline scientists at Brookhaven National Laboratory to develop and test SMART, a mathematical method that enables autonomous experimental decision making without human interaction. Read More »
CRD Staff Get Funding for Post-Moore’s Law Computing Research
George Michelogiannakis and Dilip Vasudevan, research scientists in the Computational Research Division, have been awarded funding from the Army Research Office for two post-Moore’s law computing research projects. Read More »
CRD Researchers Nominated for Best Paper at ICPP2019
CRD’s Mauro Del Ben, Osni Marques, and Andrew Canning are developing new Eigensolver algorithms based on an iterative approach using an unconstrained energy functional scheme to improve scaling on parallel computing architectures. Read More »
Industry and CRD Partner to Build Energy Efficiency into Paint Design
Through DOE's HPC4Mfg program, PPG - one of the world's largest paint manufacturers - is collaborating with applied mathematicians in the Computational Research Division on computational models that will help optimize paint design and application to reduce energy consumption. Read More »
Berkeley Lab Researchers Win Best Paper Award at ICCS
Five Berkeley Lab researchers were recently honored with a Best Paper Award at the International Conference on Computational Science, held in Faro, Portugal, June 12-14. Read More »
CRD Staff Share Applied Math Expertise at ICIAM 2019
A number of staff from Berkeley Lab’s Computational Research Division are presenting talks and posters at the International Congress on Industrial and Applied Mathematics in Valencia, Spain, July 15-19, 2019. Read More »
CRD's Shalf Ponders the Future of HPC Architectures in ISC19 Keynote
As he prepared to head to ISC19 to give a keynote address on the topic, CRD's John Shalf shared his thoughts on what the future holds for computing technologies and architectures in the era beyond exascale. Read More »
CAMERA Hosts 2019 Ptycho Developers Workshop
Ptycho-tomography and spectro-ptychography are the most computationally intensive techniques being developed at the Advanced Light Source and light sources around the world. Read More »
ExaStar Takes Astrophysical Research to the Exascale
Within the next few years, exascale computing will take computationally intensive astrophysics research to the next level. However, to harness the power of exascale, researchers will need new code developed specifically for exascale computing. The ExaStar project has researchers from multiple DOE national labs collaborating to develop new exascale-level code. Read More »
To Pump or Not to Pump?
A team of computer and environmental scientists are developing a computational tool that will allow groundwater managers to plan and manage their precious water resources more sustainably, leading to improved resistance to droughts. Read More »
National Academies Taps Cholia for Scientific Workflows Committee
Shreyas Cholia has been invited by the National Academies of Sciences, Engineering, and Medicine to serve as a member for the Realizing Opportunities for Advanced and Automated Workflows in Scientific Research committee. Read More »
CosmoGAN: Training a Neural Network to Study Dark Matter
A Berkeley Lab-led research group is using a deep learning method known as generative adversarial networks to enhance the use of gravitational lensing in the study of dark matter. Read More »
Computational Research Division Hosts UC Merced Grad Students
On May 1, a group of students from UC Merced, all participants in the National Science Foundation’s Interdisciplinary Computational Graduate Education program, visited Berkeley Lab to learn about the many ways computing can be applied to research problems. Read More »
Envisioning the Future of Machine Learning and Data Analytics
Early to mid-career national lab mathematicians met at Berkeley Lab to discuss challenges in machine learning and data analytics and to seed new collaborations. Read More »
CRD Researchers Using Deep Learning to Help VA Identify Suicide Risk in Veterans
Researchers in Berkeley Lab's Computational Research Division are applying deep learning methods and data analytics to electronic health record data to help the Veterans Administration address a host of medical and psychological challenges affecting many of the nation’s 700,000 military veterans. Read More »
UniviStor: Next-generation Data Storage for Heterogeneous HPC
The Proactive Data Containers project team at Berkeley Lab is developing object-oriented I/O services designed to simplify data movement, data management, and data reading services on next-generation HPC architectures. Read More »
IDAES Process Systems Engineering Software Now Open Source
IDAES has released the first open-source version of its next-generation computational framework and model library, created to optimize the design of process systems engineering solutions used to model advanced energy systems. Read More »
