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Showing posts with label Supercomputer. Show all posts
Showing posts with label Supercomputer. Show all posts

Monday, July 23, 2018

Five Reasons Data Center Liquid Cooling Is on the Rise

Traditionally reserved for mainframes and academic supercomputers, liquid cooling may soon be seeping into more enterprise data centers. New, more demanding enterprise workloads are pushing up power densities, leaving data center managers looking for more efficient alternatives to air-based cooling systems. We’ve asked a number of data center opearators and vendors about the applications that are driving liquid cooling into the mainstream. Some of them didn't want to disclose specific applications, saying they viewed those workloads and the way they’re cooled as a competitive advantage.  #Hyperscale #cloud operators, including @Microsoft, @Alphabet’s @Google, @Facebook, and @Baidu, have formed a group working on an open specification for #liquidcooled server racks without saying that exactly they would use them for. At least one category of workloads in the hyperscalers’ arsenal, however, clearly calls for liquid cooling: #machinelearning systems accelerated by #GPUs, or, in Google’s case, also #TPUs, which the company has said publicly are now cooled using a direct-to-chip liquid cooling design. Despite operators’ caginess around this subject, some usage trends are starting to emerge. If you're supporting any of the following workloads in your data center, liquid cooling may be in your future too:

http://www.datacenterknowledge.com/power-and-cooling/five-reasons-data-center-liquid-cooling-rise

Tuesday, May 1, 2018

Radio Free HPC Looks at New USA Supercomputing Map

In this podcast, the @RadioFree #HPC team looks at the new interactive USA #Supercomputing Map from @Hyperion Research. “The mapped sites include government, academic and industrial HPC data centers, along with HPC vendors. This powerful tool can be used to identify the economic impact of HPC in a user-defined area (state, Congressional district, et al.) or for the United States as a whole, or to understand where HPC jobs are located, as well as who the Congressional district representatives are.” As part of the discussion, Rich recaps Hyperion’s recent HPC User Forum in Tucson. The event featured an extended session on Quantum Computing with presentations by D-Wave Systems, Google, IBM, Intel, Microsoft, NIST, and Rigetti Computing. You can watch them all right here on insideHPC.  After that, we do our Catch of the Week: Henry is concerned about about the privacy implications raised by near-relative DNA methods used to catch the Golden State Killer. Henry notes that Gartner’s claim that AI is going to deliver $3.9 Trillion dollars in Global Business Value by 2022. Shahin reminds us that this week marked the 25th anniversary of the first Mosaic browser. Dan notes that Amazon logged $1.6 Billion in profits for the first quarter, a big jump from last year thanks to substantial growth in AWS. Meanwhile, Microsoft Azure is up 93 percent this quarter as well.
https://insidehpc.com/2018/04/radio-free-hpc-looks-new-usa-supercomputing-map/

Wednesday, April 18, 2018

Why HPC Matters: Understanding Our Universe

Searching for gravitational waves and exploring the physics of black holes and warped space-time is all in a day’s work for teams of researchers in Australia. This is the type of work conducted by the Australian Research Council’s Centre of Excellence for Gravitational Wave Discovery (OzGrav). And it’s the type of work that couldn’t be carried out without the extreme computational power of a supercomputer. In OzGrav’s case, the computational power is delivered via a new $4 million Dell EMC supercomputer launched at Swinburne University of Technology. The supercomputer, named OzSTAR, delivers an astounding peak performance of 1.2 petaflops, making it one of the most powerful supercomputers in Australia. What does that mean in layman’s terms? OzGrav’s director, Professor Matthew Bailes, explains it this way: “In one second, OzSTAR can perform 10,000 calculations for every one of the 100 billion stars in our galaxy.”1 That’s the kind of computational power it takes to shift through an unfathomable amount of data coming from giant telescopes to gain insights that help unlock the secrets of the universe. With this type of scientific research, high performance computing (HPC) is an absolute requirement. For example, researchers couldn’t begin to model the large-scale structure of the universe or simulate the formation and evolution of galaxies without HPC. “We will be looking for gravitational waves that help us learn more about supernovas, the formation of stars, intergalactic gases and more,” Professor Bailes says. “It’s exciting to think that we at OzGrav could make the next landmark discovery in gravitational wave astrophysics — and the Dell EMC supercomputer will allow us to capture, visualize and process the data to make those discoveries.”2 The OzSTAR supercomputer is based on Dell EMC PowerEdge™ R740 compute and data-crunching nodes; a Dell EMC H-Series Networking Fabric, which is powered by the Intel® Omni-Path Architecture (Intel OPA); and Dell EMC HPC Storage with a Lustre parallel file system. “This combination of Dell EMC technologies will deliver the incredibly high computing power required to move and analyze data sets that are literally astronomical in size,” says Andrew Underwood, Dell EMC’s Australia-New Zealand high performance computing lead, who collaborated with Swinburne on the supercomputer design.3 “Brilliant researchers are often only limited by advances in technology,” adds Chris Kelly, Vice President, Compute and Networking Solutions, Dell EMC Asia-Pacific. “With this new supercomputer, Swinburne and OzGrav will be able to embark on a new era of astronomy that could unlock answers to questions mankind has pondered for centuries. It’s an incredibly exciting time for astronomical research.”4 For a closer look at technologies used to create HPC solutions that deliver the extreme computational power needed to explore black holes and warped space-time, visit the Dell EMC Go Ahead. Dream Big. site.

https://www.cio.com/article/3269031/it-industry/why-hpc-matters-understanding-our-universe.html

Sunday, February 25, 2018

Lenovo Unveils Warm Water Cooled ThinkSystem SD650 in Rampup to LRZ Install

This week @Lenovo took the wraps off the #ThinkSystem #SD650 high-density server with third-generation direct water cooling technology developed in tandem with partner Leibniz Supercomputing Center (LRZ) in Germany. The servers are designed to operate using warm water, up to 45°C for general deployments and for special bid projects up to 50°C, lowering datacenter power consumption 30-40 percent compared to traditional cooling methods, according to Lenovo. Nearly 6,500 of the ThinkSystems SD650s featuring Intel Xeon Platinum (Skylake) processors interconnected with Intel Omni-Path Architecture will be put into production at LRZ this year, providing the supercomputing center with 26.7 petaflops of peak performance, housed in a little over 100 racks. The SuperMUC-NG supercomputer will be deployed with Lenovo’s new Lenovo Intelligent Computing Orchestrator (LiCO) and the Lenovo Energy Aware Runtime (EAR) software, a technology that dynamically optimizes system infrastructure power while applications are running.  Lenovo’s Scott Tease holding a ThinkSystem SD650 server “Pretty much all the investments that we made to get to exascale LRZ is taking advantage of in this bid we won with them,” said Scott Tease, executive director, HPC and AI at Lenovo in an on-site briefing at Lenovo’s headquarters in Morrisville, North Carolina, last week. “We will start building systems and start shipping them in March; the floor will be ready by the end of April, and move-in starts in early May. We’ll be ready to do acceptance in September with final customer acceptance in November.” The direct-water cooled design of the SD650 enables 85-90 percent heat recovery; the rest can easily be managed by a standard computer room air conditioner. The hot water coming off the servers can be recycled to warm buildings in the winter, as LRZ does with its petascale SuperMUC cluster, but the technology developed by Lenovo for SuperMUC-NG actually transforms that heat energy back into cooling for networking and storage components. The endothermic magic trick only works with “high quality heat,” Lenovo thermal engineer Vinod Kamath told us, so LRZ’s SD650 servers were designed to be able to consume 50°C inlet temperatures. Water is piped out of the servers at 58-60°C depending on workload and sent through an adsorption chiller, where it is converted to chilled 20°C water suitable for cooling storage and networking components. If you’re using chilled water to cool servers you can’t really take advantage of the economics of the adsorption chiller. With 60°C inlet water, the efficiency of Lenovo’s adsorption chiller is about 60 percent. If your energy source has a higher temperature, say 80-90°C then the extraction is even more efficient, but 60°C is good enough to realize significant savings. Adsorption chilling will be applied to half the nodes of the next-gen LRZ install, generating about 600 kilowatts of chilled water capacity. This translates into more than 100,000 Euros a year in saved energy cost at the European site, where the rate for energy is about 16-18 Eurocents per kilowatt-hour (roughly 2-3 times the cost for similar sites in the United States). Lenovo claims a 45-50 percent energy savings with the endothermic reaction versus a traditional compressor, dropping the datacenter PUE from 1.6 to less than 1.1.

https://www.hpcwire.com/2018/02/22/lenovo-unveils-warm-water-cooled-thinksystem-sd650-rampup-lrz-install/

Wednesday, February 21, 2018

HPE to Deliver Seven Supercomputers to Department of Defense

@Hewlett Packard Enterprise ( #HPE ) has been selected to supply seven new supercomputers for the US Department of Defense ( @DoD) High Performance Computing Modernization Program ( #HPCMP ). All of the systems are HPE SGI 8600 clusters. Four of them will be deployed at the Air Force Research Laboratory ( @AFRL) at Wright-Patterson Air Force Base, while the other three will be installed at the Navy’s DoD Supercomputing Resource Center. The HPE SGI 8600 clusters for the Air Force will be powered by 24-core Intel Xeon Scalable Processors, hooked together with Intel’s Omni-Path fabric. In aggregate, the four clusters will deliver more than 7.3 petaflops of peak performance, backed by over 12 petabytes DDN Lustre storage. The AFRL systems will be used to support research in hypersonics and computational modeling of Air Force weapon systems. The three Navy systems are almost identical, sporting the same 24-core Xeon processors and Omni-Path fabric, along with 12 petabytes of DDN storage. Together, the machines will supply 6.8 petaflops of computational performance. They will be used to support the Navy’s advanced weapons capabilities and global weather modeling. The HPE SGI 8600 is of fairly recent vintage, having been introduced in 2017. Although it doesn’t sport the Apollo brand, the 8600 is included under that HPC-centered portfolio. Rather than being based on the HPE Proliant server, the like the other Apollo products, the 8600 is a derivation of SGI’s ICE XA platform, which HPE upgraded and rebranded last year. Besides offering Intel’s latest Xeon silicon, the system can also be equipped with NVIDIA GPU coprocessors, although none of the Air Force or Navy systems appear to employ this particular option. Other large HPE SGI 8600 systems of note include TSUBAME 3.0, a 12.1-petaflop supercomputer installed at Tokyo Tech, and Electra, a 4.8-petaflop machine deployed at NASA’s Ames Research Center. The 8600 platform can support more than 10,000 nodes, so scaling into multi-petaflop territory is not a problem. The contract for the seven DoD systems is valued at $57 million, which includes the cost of the supercomputing machinery, plus five years of 24/7 support, on-site system administration, and access to applications support personnel from HPE.

https://www.top500.org/news/hpe-to-deliver-seven-supercomputers-to-department-of-defense/

Sunday, February 18, 2018

Hewlett Packard Enterprise Signs Big Supercomputer Deal with Defense Department

The @Defense Department is paying $57 million to @Hewlett Packard Enterprise for supercomputers that it plans to use for tasks like designing helicopters and weather forecasting. The Air Force Research Laboratory and Defense Department’s Supercomputing Resource Center at the Wright-Patterson Air Force Base near Dayton, OH will receive four HPE SGI 8600 supercomputers, as part of the deal. Another three of the same supercomputers will be installed at the Navy Department of Defense Supercomputing Resource Center in southern Mississippi. The Defense Department bought the supercomputers as part of its so-called high-performance computing modernization program, said the program’s chief of staff, Kevin Newmeyer. The program, created in 1992, is intended to ensure that the Defense Department consistently has the most powerful computers for tasks like designing weapons, aircraft, and analyzing weather patterns so that Navy ships can navigate more safely, he said.

http://fortune.com/2018/02/15/hewlett-packard-enterprise-supercomputer-department-defense/

Monday, December 25, 2017

The Doctors of Tomorrow Will Be Supercomputers

A team of researchers from the University of North Carolina Lineberger Comprehensive Cancer Center set out to solve this conundrum, demonstrating their findings back in November. Their solution involves using cognitive computing to sift through the overwhelming amount of data produced by scientific studies and databases in an attempt to “identify potentially relevant clinical trials or therapeutic options for cancer patients based on the genetics of their tumors.” Put simply, they want to use advanced computing techniques to more effectively identify potentially useful cancer treatments. @IBM Watson for #Genomics The researchers’ findings, published in the journal The Oncologist, suggest this new method could help physicians stay on top of current and upcoming scientific literature. To put the method to the test, the researchers enlisted the help of IBM Watson for Genomics to see if it might prove more effective than a panel of cancer experts. The team compared Watson’s ability to pick out treatments related to clinically significant genetic mutations with the findings of the board of cancer experts.  Of the 1,018 cancer cases they analyzed, the molecular tumor board identified actionable genetic alterations in 703 cases. Watson identified the same 703 cases, but also noted potential therapeutic options in 323 additional patients. Of those additions, 96 had not been previously observed to have an actionable mutation. “To be clear, the additional 323 cases of Watson-identified actionable alterations consisted of only eight genes that had not been considered actionable by the molecular tumor board,” said William Kim, MD, corresponding author on the study and an associate professor of medicine and genetics in the UNC School of Medicine. Not Quite Dr. Watson Kim went on to explain the main purpose of the study “was not designed to analyze whether or not this helps patients in regard to [the] outcome as defined by prolonged survival or treatment response.” While some of Watson’s findings were irrelevant (either because the patients didn’t have active cancer or had already died) the physicians of 47 patients with active cancer were notified of Watson’s findings.  The team’s research into cognitive computing is reminiscent of how AI’s machine learning capabilities have been used to understand suicidal behavior and to identify breast lesions that could develop into cancer. Although in terms of process, the research is most similar to astronomers using AI to find gravitational lenses — as both require culling through vast amounts of information that would overwhelm the human mind. This isn’t the only way AI is being used in the medical field, and its applications will continue to expand as the technology is developed. Microsoft already has plans to use AI to find a cure for cancer, and AI has already proven capable of predicting heart attacks more accurately than doctors. These advancements hint at a future in which your trip to the hospital puts you face to face with a robot or supercomputer rather than a flesh and blood human.

https://www.google.com/amp/s/futurism.com/doctors-tomorrow-supercomputers/amp/#ampshare=https://futurism.com/doctors-tomorrow-supercomputers/

Wednesday, October 25, 2017

Microsoft's Cloud Is Getting Some Cray Supercomputing Love

#Supercomputers are coming to @Microsoft ’s #Azure cloud computing service. Microsoft (MSFT, -0.28%) and supercomputer maker @Cray (CRAY, -1.06%) said that they will jointly sell access to Cray’s supercomputers that are hosted in Microsoft’s #datacenters. Now, companies don’t have to operate a Cray supercomputer and run it inside an internal data center. “The way it works, is that a customer will have a dedicated Cray supercomputer in an Azure datacenter, which they pay for over time,” a Cray spokesperson said in an email. “Cray will work with each customer to architect a system, including storage, to match their business and application needs.” The two companies did not say when the supercomputers would be available to use through Microsoft or any pricing details. Organizations like the U.S. Department of Energy typically use supercomputers for crunching tremendous amounts of data for things like predicting natural disasters or weather forecasts. Get Data Sheet, Fortune’s technology newsletter. Although intensive data crunching is generally done by research organizations and government agencies, Microsoft and Cray hope to convince more traditional businesses to use supercomputers, which can handle cutting edge artificial intelligence techniques like deep learning. For example, the two companies said that pharmaceutical firms can use the supercomputers for genome sequencing while automotive companies would be able to simulate crashes. “Our partnership with Microsoft will introduce Cray supercomputers to a whole new class of customers that need the most advanced computing resources to expand their problem-solving capabilities, but want this new capability available to them in the cloud,” Cray CEO Peter Ungaro said in a statement. Besides Microsoft, several other companies pitch their respective technologies as the preferred way to crunch data. Google, for example, built its own computer chip for machine learning tasks that it now rents customers access to through its cloud computing service. Chipmaker Nvidia (NVDA, -2.43%) also rents access to its chips via cloud computing providers for deep learning projects, among other things.

http://fortune.com/2017/10/24/microsoft-cloud-supercomputer-cray/

Wednesday, June 28, 2017

Supercomputing Centers Have Become Showcases for Competing HPC Technologies

Even though there wasn’t much turnover in the latest TOP500 list, a number of new #petascale #supercomputer s appeared that reflect a number of interesting trends in the way #HPC architectures are evolving. For the purposes of this discussion, we’ll focus on three of these new systems: #Stampede2, #TBUBAME 3.0, and #MareNostrum 4. First let’s dispense with the notion that these #supercomputers are mere sequels with their previous namesakes. What they really have in common is their architecturally diversity and their use of the very latest componentry. It’s notable that none of these three systems have been completed yet since they rely on hardware that is not yet generally available or could not be procured in the quantities needed in 2017.

https://www.top500.org/news/supercomputing-centers-have-become-showcases-for-competing-hpc-technologies/

Sunday, May 28, 2017

IBM to Sell Use of Its New 17-Qubit Quantum Computer over the Cloud

#IBM has created a 17- #qubit #quantumcomputer and is making plans to timeshare the machine with other companies via cloud computing. While this is an important step, it isn't quite enough to make quantum computers truly competitive compared to #supercomputers. What will it take to bring quantum computing into the commercial realm—and how long until we get there? Classical computing has been around for many years and has completely transformed the human race. Near instant communication between any two individuals used to be a dream. The idea of large calculations being done faster than you can blink was unimaginable. The concept of free information and education was too much for any University to handle. But it comes as no surprise that, now that these concepts are a reality, we've become dependent on them. This dependence places pressure on the industry to produce more powerful devices with every passing year. This was not an issue in the past since silicon devices were easy to scale down. But, with transistor gates as small as one-atom thick, shrinking may no longer be possible. Silicon, the building block of modern semiconductors, is already being phased out by Intel and future devices using feature sizes of 7nm and smaller will instead be made from materials such as Indium-Gallium-Arsenide (InGaAs).
https://www.allaboutcircuits.com/news/ibm-to-sell-use-of-its-new-17-qubit-quantum-computer-over-the-cloud/

Wednesday, May 24, 2017

Memory-Like Storage Means File Systems Must Change

The term #softwaredefinedstorage is in the new job title that Eric Barton has at #DataDirect Networks, and he is a bit amused by this. As one of the creators of early parallel file systems for supercomputers and one of the people who took the #Lustre file systems from a handful of #supercomputing centers to one of the two main data management platforms for high performance computing, to a certain way of looking at it, Barton has always been doing software-defined storage. The world has just caught up with the idea. Now Barton, who is leaving Intel in the wake of the chip giant ceasing its commercialized Lustre business, wants to help diversify and commercialize the file system that is at the heart of DDN’s Infinite Memory Engine ( #IME ) burst buffer, and so he has taken the job of chief technical officer for #SDN at the high performance storage company. Barton has spent a career that spans more than three decades on the bleeding edge of high-end storage, starting in 1985 with co-founding #MeikoScientific, a maker of parallel #supercomputer s based on transputers (remember those?) rather than ordinary vector or single-threaded processors as we know them. Lawrence Livermore National Lab stepped up and bought one of the Meiko Computing Surface clusters rather than the Connection Machine from Thinking Machines. The Computing Surface needed a file system, and Barton tells The Next Platform that Meiko was so short of staff that he had to write the parallel file system, obviously called PFS, himself. “I didn’t know quite what to do,” Barton recalls. “Solaris had this lovely virtual file system concept, and I thought I could just stripe a file system across other file systems and that will be it. I had one file that I used as the namespace and other file systems where the data was striped across.” This sounds simple enough, but getting a namespace to scale and therefore provide access to data chunks both large and small across the multiple nodes that comprise a parallel file system is a tricky business, indeed. That is why the Lustre file system was born, and that is why #IBM, #SGI, #SunMicrosystems and others also spent a fortune developing parallel file systems over the decades when supercomputer was new and cool.

https://www.nextplatform.com/2017/05/24/memory-like-storage-means-file-systems-must-change/

Monday, March 20, 2017

Chemical Romance -- BASF Tapes Hope On Hewlett Packard Enterprise Supercomputer

For those of a certain age (around 40-years old and onwards), the ' #compactcassette ' was a wonderful thing. Manufacturer brand names including #Memorex, #TDK, #Sony, #AGFA and #BASF are etched into our memory because we carried the soundtrack to our youth around on these tough little plastic units. But those days are gone... and then the CD happened and then the Internet happened and then music streaming happened and so we forgot all about some of those names. All those brands do in fact all still trade to this day (Sony, more obviously than some). Mostly they are all to be found working in areas encompassing digital imaging and media in one form or another. German chemical firm BASF is today known for its work in plastics, biotechnology and chemicals. A chemical (research) romance In this regard then, BASF is now working with Hewlett Packard Enterprise (or #HPE, as we are now encouraged to call it) on a project to develop one of the world's largest #supercomputer s for industrial chemical research. The work itself is being undertaken at BASF's headquarters in the fabulously named Ludwigshafen, Germany. "The new supercomputer will promote the application and development of complex modeling and simulation approaches, opening up completely new avenues for our research at BASF," said Dr. Martin Brudermueller, vice chairman of the board of executive directors and chief technology officer at BASF. This very big supercomputer (in German: sehr große supercomputer) will be based on HPE Apollo 6000 systems, which, in terms of form factor, are 'racks' of computer power typically deployed in High-Performance Computing (HPC) environments. How long is an HPC calculation? Used in practice, complex HPC calculations performed in areas like chemical research can take 'several months' (so say the firms) to actually execute. The new machine aims to reduce months down to days. As part of BASF's wider digitalization strategy, the company also plans to expand its capabilities to run virtual experiments with this supercomputer. BASF says it will use the machine, for example, to simulate processes on 'catalyst surfaces' more precisely or accelerating the design of new polymers with pre-defined properties. Hewlett Packard Enterprise chief executive officer Meg Whitman is on the record saying how pleased she is about the 'prodigious calculations' about the be carried out by BASF. "In today's data-driven economy, high performance computing plays a pivotal role in driving advances in space exploration, biology and Artificial Intelligence." The machine itself will feature Intel Xeon processors as well as high-bandwidth low-latency Intel Omni-Path Fabric and HPE management software. Several 'racks' of HPE computer power strung together, the supercomputer acts as a single system with an effective performance of more than 1 Petaflop (1 Petaflop equals one quadrillion floating point operations per second). With this system architecture, a multitude of nodes can work simultaneously on highly complex tasks. Developed and built by HPE, the new supercomputer will consist of several hundred computer nodes.

https://www.forbes.com/sites/adrianbridgwater/2017/03/20/chemical-romance-basf-tapes-hope-on-hewlett-packard-enterprise-supercomputer/#2c7778c853ce

Tuesday, January 17, 2017

China to develop prototype super, super computer in 2017

China plans to develop a prototype #exascalecomputer by the end of the year, state media said Tuesday, as it seeks to win a global race to be the first to build a machine capable of a billion, billion calculations per second. If successful, the achievement would cement its place as a leading power in the world of supercomputing. The Asian giant built the world's fastest #supercomputer, the #SunwayTaihuLight machine, in June last year, which was twice as fast as the previous number one. It used only locally made microchips, making it the first time a country has taken the top spot without using US technology. Exascale computers are even more powerful, and can execute at least one quintillion (a billion billion) calculations per second. Though a prototype was in the pipeline, a complete version of such a machine would take a few more years to complete, Xinhua news agency cited Zhang Ting, application engineer at the National Supercomputer Center in the port city of Tianjin, as saying. "A complete computing system of the exascale supercomputer and its applications can only be expected in 2020, and will be 200 times more powerful than the country's first petaflop computer Tianhe-1, recognised as the world's fastest in 2010," said Zhang. The exascale computer could have applications in big data and cloud computing work, he added, noting that its prototype would lead the world in data transmission efficiency as well as calculation speed. As of last June, China for the first time had more top-ranked supercomputers than the US, with 167 compared to 165, according to a survey by supercomputer tracking website Top500.org. Of the top 10 fastest computers, two are in China and five in the US as of November, the ranking said. Others are in Japan and Switzerland. China has poured money into big-ticket science and technology projects as it seeks to become a high-tech leader. But despite some gains the country's scientific output still lags behind, and its universities generally fare poorly in global rankings.

http://drudgetoday.com/v2/r?n=0&s=18&c=1&pn=Anonymous&u=https://sg.finance.yahoo.com/news/china-develop-prototype-super-super-113730727.html

Sunday, January 15, 2017

Dell EMC Powers Summit Supercomputer at CU Boulder

In this video researchers at the University of Colorado Boulder describe how the Summit supercomputer from #DellEMC is powering diverse compute and data intensive applications. #supercomputer “The University of Colorado, Boulder supports researchers’ large-scale computational needs with their newly optimized high performance computing system, Summit. Summit is designed with advanced computation, network, and storage architectures to deliver accelerated results for a large range of #HPC and big data applications. Summit is built on Dell EMC PowerEdge Servers, Intel Omni-Path Architecture Fabric and Intel Xeon Phi Knights Landing processors.”
http://insidehpc.com/2017/01/dell-emc-powers-summit-supercomputer-cu-boulder/

Sunday, January 8, 2017

Universal Quantum computers could replace supercomputers within 5 years

Some researchers are predicting that the market for "universal" #quantumcomputers that do everything a #supercomputer can do plus everything a supercomputer can not do — in a chip that fits in the palm of your hand — are on the verge of emerging. The rise of quantum computing may be as important a shift as John von Neumann's stored program-and-data concept. Here are some of the scientists and breakthroughs that will enable this shift. Robert Schoelkopf (Yale, #QuantumCircuits inc) claims a number of "world's firsts," the latest of which is the longest "coherence time" for a quantum superposition

http://www.nextbigfuture.com/2017/01/universal-quantum-computers-could.html?m=1

Friday, January 6, 2017

Google, Microsoft, labs and start-ups will create universal quantum computers in 2017 and achieve quantum supremacy over classical computers

#Google started working on a form of #quantumcomputing that harnesses #superconductivity in 2014. In 2017 or 2018 Google hopes to perform a computation that is beyond even the most powerful ‘classical’ #supercomputers — an elusive milestone known as #quantumsupremacy. Its rival, #Microsoft, is betting on an intriguing but unproven concept, topological #quantumcomputing, and hopes to perform a first demonstration of the technology. The quantum-computing start-up scene is also heating up. Christopher Monroe, co-founded the start-up IonQ in 2015, plans to begin hiring in earnest this year. Physicist Robert Schoelkopf at Yale University in New Haven, Connecticut, who co-founded the start-up Quantum Circuits, and former IBM applied physicist Chad Rigetti, who set up Rigetti in Berkeley, California, say they expect to reach crucial technical milestones soon. The largest trapped ion quantum computer with 20 qubits is being tested in an academic lab led by Rainer Blatt at the University of Innsbruck in Austria. In 2016, Rainer Blatt's and Peter Zoller's research teams have simulated lattice gauge theories in a trapped ion quantum computer. Gauge theories describe the interaction between elementary particles, such as quarks and gluons, and they are the basis for our understanding of fundamental processes. "Dynamical processes, for example, the collision of elementary particles or the spontaneous creation of particle-antiparticle pairs, are extremely difficult to investigate," explains Christine Muschik, theoretical physicist at the IQOQI. "However, scientists quickly reach a limit when processing numerical calculations on classical computers. For this reason, it has been proposed to simulate these processes by using a programmable quantum system."

http://www.nextbigfuture.com/2017/01/google-microsoft-labs-and-start-ups.html?m=1

Thursday, December 1, 2016

Pushing Back Against Cheap and Deep Storage

It is not always easy, but several companies dedicated to the #supercomputing market have managed to retune their wares to fit more mainstream market niches. This has been true across both the hardware and software subsets of high performance computing, and such efforts have been aided by a well-timed shift in the needs of enterprises toward more robust, compute and data-intensive workhorses as new workloads, most of which are driven by dramatic increases in data volumes and analytical capabilities, keep emerging. For #supercomputer makers, the story is a clear one. However, on the storage side, especially for those select few companies that have a unique, proprietary parallel file system and hardware partnerships to roll into appliances, the move to a wider enterprise market base from pure #HPC can be a bit more challenging. Unlike with compute systems for HPC, which are seeing broader reach due to increased computational and data requirements, parallel file systems have something of a tougher row to work, especially with the “cheap and deep” options enabled by software defined or object-based storage. We have talked in depth about how humble HPC roots have propelled some storage companies into the broader enterprise storage foray (DDN is a prime example), and via HPC systems makers that sell storage (think Cray’s Sonexion line with burst buffers and such), but these companies are basing their offerings on commercial-grade distributions of Lustre and GPFS for the most part versus going to fully customized route. This is already a tough sell for some enterprise shops that haven’t had the experience of using high performance parallel file systems as it is, but for companies that have been around for decades with a closed-source file system locked inside an appliance as in the case of Panasas, the enterprise reach seems like a bit more of a stretch—at least, in theory. Actually, according to Tom Shea, COO at Panasas, this might sound logical, but what enterprise-grade commercial HPC shops need is something that can just function out of the box. He says that while there are plenty of sites that choose to deploy Lustre or another file system on their own commodity hardware, the management overhead of this is far more complex than it might appear. He says that users are far less interested in what is under the hood of the Panasas appliance-based approach and far more focused on getting to work on real applications. While open sourcing their file system is not on any foreseeable roadmap (which bucks the trend), their focus will be on building a bolder base of commercial high performance computing users through a focus on scalability, reliability, and manageability—all areas where Shea says the open source, DIY storage approach fails for users with mission-critical applications at scale. As a quick refresher, Panasas got its start in 1999 at the technical direction of co-founder, Garth Gibson, of RAID fame and found significant footing in the emerging HPC market in government and academia in particular, beginning with the PanFS file system and its first scale-out NAS appliances. While it is difficult to tell if the privately-held company is profitable or growing overall, especially after undergoing some major transitions, the company’s Jim Donovan gave some key insight into what growth looks like from a more government/academic focused HPC business to a more enterprise-geared one.

https://www.nextplatform.com/2016/11/29/pushing-back-cheap-deep-storage/

Friday, June 3, 2016

TACC engineers by 2018 will replace the current Stampede supercomputer with new Dell servers running the latest Intel Xeon and Xeon Phi chips

AUSTIN, Texas—The #Dell-based #Stampede #supercomputer at the Texas Advanced Computing Center here, which currently is the 10th-fastest system in the world, is about to get a significant upgrade.

Officials with the center, which is part of the University of Texas at Austin, announced June 2 that the facility will use a $30 million award from the National Science Foundation (NSF) to build a new large-scale supercomputer that will provide twice the peak performance, memory, storage capacity and bandwidth of the current system, which went online in 2013.

Stampede 2 will be built with Dell PowerEdge servers and powered by a mix of the next generation of Intel Xeon chips and the chip maker's many-core Xeon Phi "Knights Landing" processors. It also will use Intel's OmniPath connectivity fabric and the chip maker's upcoming 3D XPoint memory technology. Once it's all in place in 2018, the supercomputer will deliver 18 petaflops of peak performance, twice the amount of the current Stampede. Eighteen petaflops would put the system in the number-two slot on themost recent Top500 list of the world's fastest supercomputers, which was released in November 2015.

http://mobile.eweek.com/servers/dell-based-texas-supercomputer-center-gets-30-million-for-new-system.html