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Expanded Frontera supercomputer to support urgent computing

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IMAGE: The Frontera expansion added nearly 400 Dell EMC PowerEdge R640 server nodes, housed in 11 racks.
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Credit: TACC
Frontera the 9th fastest supercomputer in the world, deployed at The University of Texas at Austin s Texas Advanced Computing Center (TACC) has expanded thanks to a supplemental award from the National Science Foundation (NSF), which funded the system, and a substantial contribution from Dell Technologies and Intel.
The expansion will contribute to TACC s urgent computing capabilities, accelerating life sciences research during the COVID-19 pandemic and supporting rapid responses to emergencies like hurricanes, earthquakes, tornadoes, floods, and other large-scale disasters. ....

United States , Dell Poweredge , Trish Damkroger , Jeremy Ford , Dan Stanzione , Manish Parashar , National Oceanographic , Atmospheric Administration , National Science Foundation , Office For Advanced Cyberinfrastructure , Us Geological , Texas Advanced Computing Center , Dell Technologies , Gen Intel Xeon Scalable Platinum Processors , Advanced Cyberinfrastructure , Space Shuttle Challenger , During Hurricane Ike , Deepwater Horizon , High Performance Computing , Intel Xeon Scalable , Biomechanics Biophysics , Molecular Biology , Plate Tectonics , Algorithms Models , Technology Engineering Computer Science , Computer Science ,

Positive reinforcements help algorithm forecast underground natural reserves

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Texas A&M University researchers have designed a reinforcement-based algorithm that automates the process of predicting the properties of the underground environment, facilitating the accurate forecasting of oil and gas reserves.
Within the Earth s crust, layers of rock hold bountiful reservoirs of groundwater, oil and natural gas. Now, using machine learning, researchers at Texas A&M University have developed an algorithm that automates the process of determining key features of the Earth s subterranean environment. They said this research might help with accurate forecasting of our natural reserves.
Specifically, the researchers algorithm is designed on the principle of reinforcement or reward learning. Here, the computer algorithm converges on the correct description of the underground environment based on rewards it accrues for making correct predictions of the pressure and flow expected from boreholes. ....

United States , Hao Li , Siddharth Misra , Harold Vance Department Of Petroleum Engineering , University Of Oklahoma , United States Department Of Energy , Texasam University , Department Of Geology , Harold Vance Department , Petroleum Engineering , United States Department , Energy Sources , Mathematics Statistics , Algorithms Models , ஒன்றுபட்டது மாநிலங்களில் , ஹ்ம் லி , சித்தார்த் மிஸ்ரா , ஹரோல்ட் வான்ஸ் துறை ஆஃப் பெட்ரோலியம் பொறியியல் , பல்கலைக்கழகம் ஆஃப் ஓக்லஹோமா , ஒன்றுபட்டது மாநிலங்களில் துறை ஆஃப் ஆற்றல் , துறை ஆஃப் புவியியல் , ஹரோல்ட் வான்ஸ் துறை , பெட்ரோலியம் பொறியியல் , ஒன்றுபட்டது மாநிலங்களில் துறை , ஆற்றல் ஆதாரங்கள் , கணிதம் புள்ளிவிவரங்கள் ,

Models to predict dengue, zika and yellow fever outbreaks are developed by researchers

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IMAGE: Monkey being examined in Manaus area. Scientists will monitor areas in which these diseases are endemic to investigate the factors that trigger outbreaks
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Credit: CREATE-NEO
By Maria Fernanda Ziegler | Agência FAPESP – Yellow fever was the first human disease to have a licensed vaccine and has long been considered important to an understanding of how epidemics happen and should be combated. It was introduced to the Americas in the seventeenth century, and high death rates have resulted from successive outbreaks since then. Epidemics of yellow fever were associated with the slave trade, the US gold rush and settlement of the Old West, the Haitian Revolution, and construction of the Panama Canal, to cite only a few examples. ....

Rio Preto , Santa Catarina , Amazon Basin , Brazil General , Mato Grosso , Estado Do Rio , Estado De Mato Grosso , Panama Canal , Panama General , Lacerda Nogueira , Barbaraa Han , Mauriciol Nogueira , Maria Fernanda Ziegler , Livia Sacchetto , Betaniap Drumond , National Institute For Research , University Of Amazonas , Cary Institute Of Ecosystem , Massachusetts Institute Of Technology , University Of Texas Medical Branch , University Of Mato Grosso , Heitor Vieira Dourado Foundation For Tropical Medicine , Mexico State University , Rio Preto Medical School , Gorgas Memorial Institute For Health Studies , Us National Institutes Of Health ,

Researchers develop speedier network analysis for a range of computer hardware

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Graphs data structures that show the relationship among objects are highly versatile. It s easy to imagine a graph depicting a social media network s web of connections. But graphs are also used in programs as diverse as content recommendation (what to watch next on Netflix?) and navigation (what s the quickest route to the beach?). As Ajay Brahmakshatriya summarizes: graphs are basically everywhere.
Brahmakshatriya has developed software to more efficiently run graph applications on a wider range of computer hardware. The software extends GraphIt, a state-of-the-art graph programming language, to run on graphics processing units (GPUs), hardware that processes many data streams in parallel. The advance could accelerate graph analysis, especially for applications that benefit from a GPU s parallelism, such as recommendation algorithms. ....

Saman Amarasinghe , Changwan Hong , Ajay Brahmakshatriya , Daniel Ackerman , Artificial Intelligence Laboratory , National Science Foundation , Department Of Electrical Engineering , News Office , Us Department Of Energy , International Symposium On Code Generation , Adobe Research Shoaib Kamil , Defense Advanced Research Projects Agency , Applications Driving Architectures Center , Electrical Engineering , Computer Science , International Symposium , Code Generation , Professor Saman Amarasinghe , Career Development Assistant Professor , Software Technology Julian Shun , Yunming Zhang Phd , Adobe Research , Defense Advanced Research Projects , Mathematics Statistics , Algorithms Models , Technology Engineering Computer Science ,

Seeing stable topology using instabilities

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IMAGE: The spatial intensity profile of a laser beam propagating in a nonlinear medium spontaneously becomes nonuniform due to the process of modulational instability.
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Credit: Institute for Basic Science
We are most familiar with the four conventional phases of matter: solid, liquid, gas, and plasma. Changes between two phases, known as phase transitions, are marked by abrupt changes in material properties such as density. In recent decades a wide body of physics research has been devoted to discovering new unconventional phases of matter, which typically emerge at ultra-low temperatures or in specially-structured materials. Exotic topological phases exhibit properties that can only change in a quantized (step-wise) manner, making them intrinsically robust against impurities and defects. ....

South Korea , Daria Smirnova , Sergej Flach , Daniel Leykam , Aleksandra Maluckov , Ekaterina Smolina , Australian National University , Institute For Basic Science , Russian Academy Of Sciences , Institute Of Applied Physics , Theoretical Physics , Complex Systems , Basic Science , Applied Physics , Russian Academy , Physical Review , Chemistry Physics Materials Sciences , Algorithms Models , தெற்கு கொரியா , ஆஸ்திரேலிய தேசிய பல்கலைக்கழகம் , நிறுவனம் க்கு அடிப்படை அறிவியல் , ரஷ்ய கலைக்கழகம் ஆஃப் அறிவியல் , நிறுவனம் ஆஃப் பயன்படுத்தப்பட்டது இயற்பியல் , கோட்பாட்டு இயற்பியல் , சிக்கலான அமைப்புகள் , அடிப்படை அறிவியல் ,