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“Minimalist Machine Learning” Algorithms

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Berkeley Lab mathematicians have developed a new approach to machine learning aimed at experimental imaging data. Rather than relying on the tens or hundreds of thousands of images used by typical machine learning methods, this new approach “learns” much more quickly and requires far fewer images. » Read More

Delivering Efficient Parallel I/O with HDF5

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In this podcast, CRD's Suren Byna and NERSC's Quincey Koziol talk about delivering efficient parallel I/O with HDF5 on exascale computing systems. » Read More

CRD Researchers Help Make Blockchains More Robust

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In the last few years, researchers at Berkeley Lab, UC Davis and University of Stavanger in Norway have developed a new protocol, called BChain, which makes private blockchain even more robust. The researchers are also working with colleagues at Berkeley Lab and beyond to adapt this tool to support applications that are of strategic importance to the Department of Energy’s Office of Science. » Read More

Big Scientific Array Data Analysis with ArrayUDF

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In 2017, ArrayUDF helped researchers in the LIGO collaboration identify two colliding neutron stars, a never before seen cosmic event that is providing valuable insights into the origin of the universe’s heavy elements. » Read More

News

cells slideCAM.crop

Berkeley Lab “Minimalist Machine Learning” Algorithms Analyze Images from Very Little Data

February 21, 2018

Berkeley Lab mathematicians have developed a new approach to machine learning aimed at experimental imaging data. Rather than relying on the tens or hundreds of thousands of images used by typical machine learning methods, this new approach “learns” much more quickly and requires far fewer images.

IMG 5707

Delivering Efficient Parallel I/O with HDF5 on Exascale Computing Systems

February 2, 2018

In an interview with Department of Energy's ECP communications team, Berkeley Lab's Suren Byna and Quincey Koziol talk about delivering efficient parallel I/O with HDF5 on exascale computing systems.


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Berkeley Lab Researchers Contribute to Making Blockchains Even More Robust

January 30, 2018

In the last few years, researchers at Berkeley Lab, UC Davis and University of Stavanger in Norway have developed a new protocol, called BChain, which makes private blockchain even more robust. The researchers are also working with colleagues at Berkeley Lab and beyond to adapt this tool to support applications that are of strategic importance to the Department of Energy’s Office of Science.

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Berkeley Lab’s ArrayUDF Tool Turns Large-scale Scientific Array Data Analysis Into a Cakewalk

January 2, 2018

A novel scalable framework developed by CRD researchers is improving scientific productivity by allowing researchers to run user-defined custom analysis operations on large arrays of data with massively parallel supercomputers, while leaving complex data management and performance optimization tasks up to the underlying system.