As part of the Computational Research Division’s strategic emphasis on increasing the role of computation in all aspects of scientific discovery, the group last week hosted a one-day workshop on Machine Learning for Science. The generation of data is now often outstripping the abilities of researchers to manage, analyze and understand the data. Machine learning, the development and use of advanced techniques to automatically classify data, detect patterns or extract results, is arguably the most widely used methodology to deal with data of this size and complexity. The workshop looked at increasing the role of machine learning in the areas of climate research, cosmology, materials, microtomography and metagenomics. More>
Posts Tagged ‘Computational Research Division’
Keith Jackson, a member of the Computational Research Division’s Advanced Computing Group, passed away on Sept. 18 after a 20-month battle with cancer. He was at the Lab for 15 years. His research spanned the development of Python interfaces for the Globus Toolkit® to working on Mickey Hart’s project to ‘sonify’ the universe. Donations in Jackson’s honor can be made to the Make-A-Wish Foundation, American Cancer Society, the Leukemia Foundation, or any organization that provides musical instruments and/or instruction for school children.
Over the next century, most of the continents are on track to become considerably warmer, with more hot extremes and fewer cold extremes. Precipitation will increase in some parts of the world but will decrease in other parts. These are some of the conclusions reached by authors of the recently released Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). Michael Wehner of the Computational Research Division and William Collins of the Earth Sciences Division were lead authors of the chapters on long-term climate change projections and climate models, respectively. More>
As part of DOE’s focus on supercomputing in September, Computational Research Director and applied mathematician David Brown answers five questions on how math makes supercomputers even more powerful tools for scientific discovery. More>
Energy scientists hope new plant varieties will yield large amounts of biomaterial, which new types of microbes will quickly and cheaply convert into clean-burning fuel. To achieve these goals, researchers will need novel algorithms that enable supercomputers to sift through the combined genomes of several hundred plants or microbes in search of useful genes. With support from a DOE Early Career Award, Berkeley Lab Computational Researcher Aydın Buluç will develop faster and more energy-efficient data-mining algorithms in the quest for new biofuels. More>
As the first Simons Institute Research Fellow (Theoretical Foundations of Big Data Analysis) at Berkeley Lab, Sang-Yun Oh will be working with the Computational Research Division’s Future Technologies Group to develop large-scale data analysis methodologies and algorithms. Established at UC Berkeley in July 2012, the Simons Institute aims to explore deep, unsolved problems about the nature and limits of computation by bringing together some of the world’s leading researchers in computer science and related fields. The Institute offers about 16 fellowships each semester in connection with a specific program, and several joint fellowships with partner institutions, including Berkeley Lab. More>
New computational techniques developed at Berkeley Lab may help save scientists from drowning in their own data. Computational researchers have figured out how to streamline the analysis of enormous scientific datasets. The analysis — called Distributed Merge Trees — uses the same techniques that make complex subway systems understandable at a glance. More>
About 50 students from the East Bay Consortium of Educational Institutions visited Berkeley Lab on last week to learn about careers in science, technology, engineering and mathematics. Deb Agarwal of the Computational Research Division welcomed the group and gave a brief overview of the Lab. Andy Nonaka (CRD) talked about his research in computational cosmology; Ben Bowen (Life Sciences Division) discussed mass spectrometry and Susan Amrose (EETD) explained engineering for economic and social development. The visit culminated with a tour of the Advanced Light Source led by Christine Beavers, Bruce Rude, Thomas Scarvie and Doug Taube. CRD’s Sarah Poon (pictured) organized the visit.
[Berkeley Science Review] Like the planet they simulate, climate models are changing. As scientific computing technology improves, models are getting larger and more complicated in order to make better predictions. However, with greater predictive power comes greater demand for power. In fact, scaling up the current generation of models to meet the need for reliable local-level predictions could require as much power as a city of 100,000 inhabitants. To avoid this large carbon footprint, CRD’s Michael Wehner (left) and other scientists have been warning that “the computational power required for extreme-scale modeling accurate enough to inform critical policy decisions requires a new breed of extreme-scale computers.” More>
In op-ed in Live Science discusses a new study by the Centers for Disease Control and Prevention (CDC) showing that deaths caused by heat are on the rise in United States. The article includes comments by climate scientists Michael Wehner and Daithi Stone of the Computational Research Division. More>