Entries filed under “Computing Research”

Over at Lawrence Livermore National Laboratory, Donald B Johnston writes that researchers at LLNL and Rensselaer Polytechnic Institute have set a high performance computing speed record that opens the way to the scientific exploration of complex planetary-scale systems.

In a paper to be published in May, the joint team will announce a record-breaking simulation speed of 504 billion events per second on LLNL’s Sequoia Blue Gene/Q supercomputer, dwarfing the previous record set in 2009 of 12.2 billion events per second. Participants included Peter Barnes, Jr. and David Jefferson of LLNL and CCNI Director and computer science professor Chris Carothers and Justin LaPre of Rensselaer. The records were set using the ROSS (Rensselaer’s Optimistic Simulation System) simulation package developed by Carothers and his students, and using the Time Warp synchronization algorithm originally developed by Jefferson.

This is an exciting time to be working in high-performance computing, as we explore the petascale and move aggressively toward exascale computing,” Carothers said. “We are reaching an interesting transition point where our simulation capability is limited more by our ability to develop, maintain and validate models of complex systems than by our ability to execute them in a timely manner.”

The calculations were completed while Sequoia was in unclassified “early science” service as part of the machine’s integration period. The system is now in classified service for the National Nuclear Security Administration’s Advanced Simulation and Computing program for stewardship of the nation’s nuclear weapons stockpile.

Read the Full Story.

Disruptive changes often originate from science labs, says David Power, head of HPC at Boston LTD.

Path-breaking findings coming from the pure sciences – new materials, chemical or physical properties, methods learnt from biological systems, etc. – often open up game-changing alternatives with the potential to disrupt the smooth flow of technological progress. And in the words of telecommunications expert and faculty at the Illinois Institute of Technology, Dr Suresh Borkar: “For continued progress, cross-disciplinary advances are needed in many areas including materials sciences, physical sciences, chemical sciences, biological sciences and mathematics.”

With this in mind, I have decided to celebrate the contributions of science to the field of computing, by discussing how pure science research could transform technology in the future and bring us closer to quantum computing.

Combining physics, mathematics and computer science, quantum computing has transformed from a visionary idea to one of the most fascinating areas of quantum mechanics in the last two decades. The circuits on a microprocessor will be measured on an atomic scale,’ explains Venkata Ramana, senior vice president, Hinditron-Cray India. ‘Quantum computers will harness the power of atoms and molecules to perform memory and processing tasks significantly faster than any silicon-based computer.”

The word ‘quantum’ is always used to refer to something immeasurably large. So when quantum physics finally meets computer engineering, just imagine what the resulting computer will be like! Today’s conventional computers represent information using two states, ‘0’ and ‘1.’ In contrast, quantum computers operate with more than two states. They encode information as quantum bits, or qubits, which can exist in superposition and because a quantum computer can manipulate information in multiple states simultaneously, it has the potential to be millions of times more powerful than today’s top supercomputers.

The good news is that scientists have already built basic quantum computers that can perform certain calculations, as proof-of-concept. A practical quantum computer is still years away. Most research in this field is still highly theoretical today,’ adds Ramana.

When quantum computing finally comes of age, points out Dr Suresh Borkar, we will have secure quantum computers, quantum routers and quantum Internet based on photonic networks with advanced encoding. He further explains that quantum computers would use quantum particles instead of binary bits – and this includes the use of impurities in materials, rare metal atoms and crystalline structures.

In 2012, a multinational team of researchers built a basic quantum computer inside a diamond. The team, funded by the US Army, tapped the impurities inside diamonds to build their quantum computer. The spins of two stray subatomic particles – a nitrogen nucleus and an electron – were used as the two qubits. Since electronics is susceptible to decoherence, the team also incorporated a level of protection using microwave pulses to continually switch the direction of electron spin rotation.

They also demonstrated the quantum properties of the computer using Grover’s Algorithm – a test developed in 1996 at Bell Labs to show the promise of quantum computing. The test involves searching an unsorted database, akin to searching for a name in a phone book when you have only the phone number. Generally, an average person or computer would find this in X/2 tries, if ‘X’ is the total number of choices. However, with superposition, a quantum computer can do this much faster. The new diamond computer picked the correct choice on first try, 95 per cent of the time.

One of the researchers commented that this demonstration suggests a pathway to increasingly complex quantum machines – ones that use qubit control protocols to circumvent the expected limitations from real materials. Could there be a better example of the progress that Dr Suresh Borkar expects to see from ‘cross disciplinary advances’? In this case, indeed, transcending conventional material sciences.

This story appears here as part of a cross-publishing agreement with Scientific Computing World.

Extreme weather events like Superstorm Sandy can cost lives and billions of dollars in damages.

A side effect of America’s growth has been the tendency to put more people, infrastructure and assets in harm’s way, and when a storm comes through, that increased exposure drives up economic losses,” said author Benjamin Preston, deputy director of ORNL’s Climate Change Science Institute, who studied historical data from more than 3,000 U.S. counties and used predictive modeling in the assessment.

Preston projected that current annual U.S. disaster losses of $10 billion to $13 billion could increase by a factor of 1.8 to 3.9 by 2050. Read the Full Story.

A simulated radar image of a storm produced by CM1. The hook-like appendage in the southwest corner is an indication of a developing vortex.

Over at the National Institute for Computational Sciences, Scott Gibson writes that researchers are using HPC to enhance tornado prediction capabilities.

We hope that with a more accurate prediction and improved lead time on warnings, more people will heed the warnings, and thus loss of life and property will be reduced,” said Amy McGovern of the University of Oklahoma. McGovern is working to revolutionize the ability to anticipate tornadoes by explaining why some storms generate tornadoes and others don’t, and by developing advanced techniques for analyzing data to discover how the twisters move in both space and time.

To run each of McGovern’s simulations, graduate student Brittany Dahl is using 6,000 processor cores and 10 compute service units (hours) on the Kraken supercomputer. Read the Full Story.