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Primeur weekly 2020-08-10

Focus

HPC markets show temporary negative COVID-19 ripple effect but will be back on track after crisis fades, says Intersect360 Research analyst Addison Snell ...

EPCC led EIDF will train 100.000 citizens over the next decade to take part in the Edinburgh International Data Facility powered by HPE ...

Exascale supercomputing

Jülich Supercomputing Centre to introduce new AI project AlphaNumerics Zero ...

GE Research uses Summit supercomputer for groundbreaking study on wind power ...

US Department of Energy to provide $57,5 million for science computing teams ...

Quantum computing

Solving materials problems with a quantum computer ...

International quantum research to take a leap forward ...

Northern Arizona University partners in $26 million NSF initiative to establish new Center for Quantum Networks ...

Focus on Europe

Atos partners with University of Oxford on largest AI supercomputer in the UK ...

JURECA data-centric module to replace JURECA Cluster ...

Open source for a global 'energiewende' ...

Skoltech supercomputer helps scientists reveal most influential parameters for crop ...

Middleware

NCCS debuts centralized storage with curated Earth science datasets ...

Hardware

Nanyang Technological University Singapore scientists build ultra-high-speed Terahertz wireless chip ...

Flash Memory Summit partners with TechTarget to extend digital reach ...

Tachyum shows Prodigy running existing x86, ARM, and RISC-V software ...

Panasas launches the new PanFS with dynamic data acceleration technology to support diverse and changing workflows in HPC and AI ...

Todd Younkin appointed President and CEO of Semiconductor Research Corporation (SRC) ...

CENIC extends 400G capabilities to coastal path between Los Angeles and Sunnyvale ...

Applications

A computational framework for solving linear inverse problems takes a parallel computing approach ...

Unequal neutron-star mergers create unique 'bang' in simulations ...

BSC researchers study mobility in Spain during the COVID-19 pandemic period using data from the Facebook and Google apps ...

Study identifies top reasons for sewer line failure ...

New spin-off created by BSC researchers to accelerate the development of new chemicals ...

Argonne researchers use Theta for real-time analysis of COVID-19 proteins ...

ALCC programme awards ALCF computing time to 24 projects ...

ALCC programme awards nearly 6 million Summit node hours across 31 projects ...

Comet supercomputer used to simulate environmental changes in Chesapeake Bay ...

Piotr Roztocki wins 2020 Paul Baran Young Scholar Award for his innovative work ...

Sustainable chemistry at the quantum level ...

Tiniest secrets of integrated circuits revealed with new imaging technique ...

Computing COVID-19's potential cure and treatments in Australia ...

National Science Foundation funds five new XSEDE-allocated systems ...

A computational framework for solving linear inverse problems takes a parallel computing approach


Researchers at the McKelvey School of Engineering at Washington University in St. Louis have developed a new algorithm for solving a common class of problem - known as linear inverse problems - by breaking them down into smaller tasks, each of which can be solved in parallel on standard computers. Image: Shutterstock.
4 Aug 2020 St. Louis - In this era of Big Data, there are some problems in scientific computing that are so large, so complex and contain so much information that attempting to solve them would be too big of a task for most computers. Now, researchers at the McKelvey School of Engineering at Washington University in St. Louis have developed a new algorithm for solving a common class of problem - known as linear inverse problems - by breaking them down into smaller tasks, each of which can be solved in parallel on standard computers.
Jr-Shin Li.

The research, from the lab of Jr-Shin Li, professor in the Preston M. Green Department of Electrical & Systems Engineering, was published July 30 in the journal Scientific Reports .

In addition to providing a framework for solving this class of problems, the approach, called Parallel Residual Projection (PRP), also delivers enhanced security and mitigates privacy concerns.

Linear inverse problems are those that attempt to take observational data and try to find a model that describes it. In their simplest form, they may look familiar: 2x+y = 1, x-y = 3. Many a high school student has solved for x and y without the help of a supercomputer.

And as more researchers in different fields collect increasing amounts of data in order to gain deeper insights, these equations continue to grow in size and complexity.

"We developed a computational framework to solve for the case when there are thousands or millions of such equations and variables", Jr-Shin Li stated.

This project was conceived while working on research problems from other fields involving Big Data. Jr-Shin Li's lab had been working with a biologist researching the network of neurons that deal with the sleep-wake cycle.

"In the context of network inference, looking at a network of neurons, the inverse problem looks like this", stated Vignesh Narayanan, a research associate in Jr-Shin Li's lab: Given the data recorded from a bunch of neurons, what is the 'model' that describes how these neurons are connected with each other?

"In an earlier work from our lab, we showed that this inference problem can be formulated as a linear inverse problem", Vignesh Narayanan stated.

If the system has a few hundred nodes - in this case, the nodes are the neurons - the matrix which describes the interaction among neurons could be millions by millions; that's huge.

"Storing this matrix itself exceeds the memory of a common desktop", stated Wei Miao, a PhD student in Jr-Shin Li's lab.

Add to that the fact that such complex systems are often dynamic, as is our understanding of them. "Say we already have a solution, but now I want to consider interaction of some additional cells", Wei Miao stated. Instead of starting a new problem and solving it from scratch, PRP adds flexibility and scalability. "You can manipulate the problem any way you want."

Even if you do happen to have a supercomputer, Wei Miao said, "There is still a chance that by breaking down the big problem, you can solve it faster."

In addition to breaking down a complex problem and solving in parallel on different machines, the computational framework also, importantly, consolidates results and computes an accurate solution to the initial problem.

An unintentional benefit of PRP is enhanced data security and privacy. When credit card companies use algorithms to research fraud, or a hospital wants to analyze its massive database, "No one wants to give all of that access to one individual", Vignesh Narayanan stated.

"This was an extra benefit that we didn't even strive for", Vignesh Narayanan stated.
Source: Washington University in St. Louis

Back to Table of contents

Primeur weekly 2020-08-10

Focus

HPC markets show temporary negative COVID-19 ripple effect but will be back on track after crisis fades, says Intersect360 Research analyst Addison Snell ...

EPCC led EIDF will train 100.000 citizens over the next decade to take part in the Edinburgh International Data Facility powered by HPE ...

Exascale supercomputing

Jülich Supercomputing Centre to introduce new AI project AlphaNumerics Zero ...

GE Research uses Summit supercomputer for groundbreaking study on wind power ...

US Department of Energy to provide $57,5 million for science computing teams ...

Quantum computing

Solving materials problems with a quantum computer ...

International quantum research to take a leap forward ...

Northern Arizona University partners in $26 million NSF initiative to establish new Center for Quantum Networks ...

Focus on Europe

Atos partners with University of Oxford on largest AI supercomputer in the UK ...

JURECA data-centric module to replace JURECA Cluster ...

Open source for a global 'energiewende' ...

Skoltech supercomputer helps scientists reveal most influential parameters for crop ...

Middleware

NCCS debuts centralized storage with curated Earth science datasets ...

Hardware

Nanyang Technological University Singapore scientists build ultra-high-speed Terahertz wireless chip ...

Flash Memory Summit partners with TechTarget to extend digital reach ...

Tachyum shows Prodigy running existing x86, ARM, and RISC-V software ...

Panasas launches the new PanFS with dynamic data acceleration technology to support diverse and changing workflows in HPC and AI ...

Todd Younkin appointed President and CEO of Semiconductor Research Corporation (SRC) ...

CENIC extends 400G capabilities to coastal path between Los Angeles and Sunnyvale ...

Applications

A computational framework for solving linear inverse problems takes a parallel computing approach ...

Unequal neutron-star mergers create unique 'bang' in simulations ...

BSC researchers study mobility in Spain during the COVID-19 pandemic period using data from the Facebook and Google apps ...

Study identifies top reasons for sewer line failure ...

New spin-off created by BSC researchers to accelerate the development of new chemicals ...

Argonne researchers use Theta for real-time analysis of COVID-19 proteins ...

ALCC programme awards ALCF computing time to 24 projects ...

ALCC programme awards nearly 6 million Summit node hours across 31 projects ...

Comet supercomputer used to simulate environmental changes in Chesapeake Bay ...

Piotr Roztocki wins 2020 Paul Baran Young Scholar Award for his innovative work ...

Sustainable chemistry at the quantum level ...

Tiniest secrets of integrated circuits revealed with new imaging technique ...

Computing COVID-19's potential cure and treatments in Australia ...

National Science Foundation funds five new XSEDE-allocated systems ...