Saturday, January 8, 2011

Wipro building India’s fastest supercomputer for space agency



Bangalore: India’s third largest information technology firm, Wipro Ltd, is building what will become the country’s fastest supercomputer for the Indian Space Research Organisation (Isro)—giving the agency critical muscle to crunch large volumes of data as it designs more complex launch vehicles and sets out on ambitious space programmes.
The supercomputer, being built at the Vikram Sarabhai Space Centre (VSSC) in Thiruvananthapuram, will have a processing speed of 200-500 teraflops—one-and-a-half times more powerful than India’s fastest computer now and at least twice faster than Isro’s current supercomputing capability.
One teraflop is the ability to process one trillion mathematical operations in a second.The supercomputer is likely to be commissioned in about three months, said P.S. Veeraraghavan, director of the space centre.
Supercomputers are used in performing complex operations and computer modelling in applications involving large data sets, such as in designing space vehicles that launch satellites or in modelling and predicting the weather.
The existing supercomputer at VSSC has a speed of 70 teraflops. The centre was looking to go up to 200 teraflops, said Veeraraghavan.
Investment for the new supercomputer runs into a few crores, he said, declining to give a specific figure.
Veeraraghavan said the new supercomputer will be used for advanced

computational fluid dynamic (CFD) studies associated with building complex launch platforms.
CFD helps space scientists build virtual prototypes of a launch system, and simulate physical and chemical changes to predict performance, making it directly relevant to designing and developing launch vehicles. Among the systems Isro is working on is a reusable launch vehicle.
VSSC was key in designing and developing launch vehicles such as the workhorse polar satellite launch vehicle and the geosynchronous launch vehicle.
For Wipro, the supercomputer it is building for Isro will help establish the capability of its Supernova range of supercomputers, offered in a partnership with California, US-based Z Research Inc.
Ashok Tripathy, general manager and head (systems and technology division) at Wipro Infotech, said his company is aiming to build a capability of up to 500 teraflops, or 0.5 petaflops, for Isro.
Even at 200 teraflops, Wipro’s supercomputer will top the list of India’s most powerful computers.
The fastest now, at 132.8 teraflops, is Eka at the Computational Research Laboratories Ltd (CRL) in Pune. CRL is a subsidiary of Tata Sons Ltd working in the field of high performance computing services, and research and development. It uses Hewlett-Packard Co.’s (HP) supercomputing technology.
The next fastest in India at 38.1 teraflops is PARAM at the government-owned Centre for Development of Advanced Computing, also in Pune. It is designed for both general science and engineering, and business applications.
“The Eka was made in 2007...we should have doubled our capacity by now, but we’re not making the right investments in terms of money and effort,” said N. Balakrishnan, associate director and head of the Supercomputing Education and Research Centre (SERC) at the Indian Institute of Science in Bangalore.
“We should not stop at this now, but go on. We have the capability to go up to petaflops in this country,” he said.
SERC maintains a list of top supercomputers in India, at http://topsupercomputers-india.iisc.ernet.in, complementing the well-known top 500 list at www.top500.org, avidly followed by supercomputing fans worldwide.
SERC’s listing shows that the combined capability of India’s top 19 supercomputers is 305.9 teraflops, at an average of 16.1 teraflops.
Supercomputing will be increasingly relevant not only in traditional high-technology areas of defence, space and weather, but also in new fields related to biology and biotechnology, said Balakrishnan.
An indigenous supercomputer at 0.5 petaflops would be a significant achievement for India, but will still not make the top 10 of the most advanced supercomputers in the world.
The world’s most powerful supercomputer is the Tianhe-1A, in Tianjin, China, with a staggering speed of 2.57 petaflops, according to 
It displaced the venerable Cray system, the Cray XT5 Jaguar at the US department of energy’s Oak Ridge Leadership Computing Facility in Tennessee, which boasted 1.76 petaflops. The third most powerful is also a Chinese system, the Nebulae, at 1.27 petaflops.
The continued rise of Chinese capability is significant, considering that Eka featured at No. 8 in the global top 500 list in June 2008, but has rapidly headed down since. It currently stands at 47.
The US dominates the list of the world’s fastest 50 supercomputers, with a sprinkling of systems from countries such as France, Germany, Japan, Korea, Brazil, Russia and, of course, China.
International Business Machines Corp. leads the supercomputing market share, followed by Cray Inc. and HP.
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Unveil Android OS 3.0 Honeycomb


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China kickout USA on World Top Supercomputer List

Tianhe-1A1
This world of technology is very interesting because there is no one who claims that in today world of technology that it has the monopoly of their technology. The latest interesting news comes in the world of supercomputers that China kick out the USA from the Top position of the world super computers. The latest supercomputer which China installs takes the sky high position on the world top twice annual ranking of the world extensive superconductive supercomputers list.
In yesterday China release or launch the details regarding the Tianjin National Supercomputer Center’s about the latest supercomputer with name of Tianhe 1A System standard a level or performance of 2.67 Petaflops  (Performance for Tianhe Quadrillion Floating Point Calculations Per Second). The previous world supercomputer which hold by the USA (US Department of Energy (DOE)) has the ability or level of performance of 1.75 Petaflops which is quite low than the latest supercomputer of china.

MOD-656188_Tianjin1
Due to this unbelievable success that gain by China in the form of this supercomputer. So now world top 500 multinational corporations should attract towards China in future because they hold the world high performance superconductive supercomputer. United State (US) Congress and US authorities of Department of Energy so much worried about this news because China innovative minds kickout the USA on the claim of world high performance supercomputer hold.
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In respect of all this, still USA holds the large quantity of supercomputers in the world. The list of holding of supercomputer USA holds 275 supercomputer systems while China holds 24 supercomputer systems but China shows their prominent growth or this achievement to kickout the USA on top spot list it’s a biggest threat to USA and other countries that hold the supercomputer. In latest information 42 countries hold the supercomputers. No doubt, the making and holding of supercomputer is the greatest achievement of any country because it provides the competitive edge in the world of competition.
supercomputer
US authorities and Department of Energy said regarding the response of China Supercomputer performance they spoke that the next generation supercomputer that makes under the tag of IBM may come with 10 petaflops and in 2012 we must exceed the performance of supercomputer into 20 petaflops. Never the less, we must admit the achievement of China because its supercomputer on top of the list now.
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Supercomputer The most Powerful Computer in the World

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Supercomputer

A supercomputer is a computer that is at the frontline of processing capacity, particularly speed of calculation (at the time of its introduction). The term "Super Computing" was first used by "New York World" newspaper in 1929 [cite book |last=Eames |first=Charles |coauthors= Eames, Ray |title=A Computer Perspective |year=1973 |publisher=Harvard University Press |location= Cambridge, Mass |pages = 95 . Page 95 identifies the article as cite news |title= Super Computing Machines Shown |publisher=New York World |date= March 1, 1920 . However the article shown on page 95 references the Statistical Bureau in Hamilton Hall and an article at the Columbia Computing History web site states that such did not exist until 1929. See [http://www.columbia.edu/acis/history/packard.html The Columbia Difference Tabulator - 1931] ] to refer to large custom-built tabulators that IBM had made for Columbia University.
Supercomputers introduced in the 1960s were designed primarily by Seymour Cray at Control Data Corporation (CDC), and led the market into the 1970s until Cray left to form his own company, Cray Research. He then took over the supercomputer market with his new designs, holding the top spot in supercomputing for five years (1985–1990). Cray, himself, never used the word "supercomputer"; a little-remembered fact is that he only recognized the word "computer". In the 1980s a large number of smaller competitors entered the market, in a parallel to the creation of the minicomputer market a decade earlier, but many of these disappeared in the mid-1990s "supercomputer market crash". Today, supercomputers are typically one-of-a-kind custom designs produced by "traditional" companies such as Cray, IBM and HP, who had purchased many of the 1980s companies to gain their experience.
The term "supercomputer" itself is rather fluid, and today's supercomputer tends to become tomorrow's ordinary computer. CDC's early machines were simply very fast scalar processors, some ten times the speed of the fastest machines offered by other companies. In the 1970s most supercomputers were dedicated to running a vector processor, and many of the newer players developed their own such processors at a lower price to enter the market. The early and mid-1980s saw machines with a modest number of vector processors working in parallel become the standard. Typical numbers of processors were in the range of four to sixteen. In the later 1980s and 1990s, attention turned from vector processors to massive parallel processing systems with thousands of "ordinary" CPUs, some being off the shelf units and others being custom designs. Today, parallel designs are based on "off the shelf" server-class microprocessors, such as the PowerPC, Opteron, or Xeon, and most modern supercomputers are now highly-tuned computer clusters using commodity processors combined with custom interconnects.
Common uses
Supercomputers are used for highly calculation-intensive tasks such as problems involving quantum mechanical physics, weather forecasting, climate research (including research into global warming), molecular modeling (computing the structures and properties of chemical compounds, biological macromolecules, polymers, and crystals), physical simulations (such as simulation of airplanes in wind tunnels, simulation of the detonation of nuclear weapons, and research into nuclear fusion), cryptanalysis, and the like. Major universities, military agencies and scientific research laboratories are heavy users.
A particular class of problems, known as Grand Challenge problems, are problems whose full solution requires semi-infinite computing resources.
Relevant here is the distinction between capability computing and capacity computing, as defined by Graham et al. Capability computing is typically thought of as using the maximum computing power to solve a large problem in the shortest amount of time. Often a capability system is able to solve a problem of a size or complexity that no other computer can. Capacity computing in contrast is typically thought of as using efficient cost-effective computing power to solve somewhat large problems or many small problems or to prepare for a run on a capability system.
Hardware and software design
Supercomputers using custom CPUs traditionally gained their speed over conventional computers through the use of innovative designs that allow them to perform many tasks in parallel, as well as complex detail engineering. They tend to be specialized for certain types of computation, usually numerical calculations, and perform poorly at more general computing tasks. Their memory hierarchy is very carefully designed to ensure the processor is kept fed with data and instructions at all times — in fact, much of the performance difference between slower computers and supercomputers is due to the memory hierarchy. Their I/O systems tend to be designed to support high bandwidth, with latency less of an issue, because supercomputers are not used for transaction processing.
As with all highly parallel systems, Amdahl's law applies, and supercomputer designs devote great effort to eliminating software serialization, and using hardware to address the remaining bottlenecks.
Supercomputer challenges, technologies
*A supercomputer generates large amounts of heat and must be cooled. Cooling most supercomputers is a major HVAC problem.
*Information cannot move faster than the speed of light between two parts of a supercomputer. For this reason, a supercomputer that is many metres across must have latencies between its components measured at least in the tens of nanoseconds. Seymour Cray's supercomputer designs attempted to keep cable runs as short as possible for this reason: hence the cylindrical shape of his Cray range of computers. In modern supercomputers built of many conventional CPUs running in parallel, latencies of 1-5 microseconds to send a message between CPUs are typical.
*Supercomputers consume and produce massive amounts of data in a very short period of time. According to Ken Batcher, "A supercomputer turning compute-bound problems into I/O-bound problems." Much work on external storage bandwidth is needed to ensure that this information can be transferred quickly and stored/retrieved correctly. Technologies developed for supercomputers include:
*Vector processing
*Liquid cooling
*Non-Uniform Memory Access (NUMA)
*Striped disks (the first instance of what was later called RAID)
*Parallel filesystems
Processing techniques
Vector processing techniques were first developed for supercomputers and continue to be used in specialist high-performance applications. Vector processing techniques have trickled down to the mass market in DSP architectures and SIMD processing instructions for general-purpose computers.
Modern video game consoles in particular use SIMD extensively and this is the basis for some manufacturers' claim that their game machines are themselves supercomputers. Indeed, some graphics cards have the computing power of several TeraFLOPS. The applications to which this power can be applied was limited by the special-purpose nature of early video processing. As video processing has become more sophisticated, Graphics processing units (GPUs) have evolved to become more useful as general-purpose vector processors, and an entire computer science sub-discipline has arisen to exploit this capability: General-Purpose Computing on Graphics Processing Units (GPGPU).
Operating systems
Supercomputer operating systems, today most often variants of Linux or UNIX, are every bit as complex as those for smaller machines, if not more so. Their user interfaces tend to be less developed, however, as the OS developers have limited programming resources to spend on non-essential parts of the OS (i.e., parts not directly contributing to the optimal utilization of the machine's hardware). This stems from the fact that because these computers, often priced at millions of dollars, are sold to a very small market, their R&D budgets are often limited. (The advent of Unix and Linux allows reuse of conventional desktop software and user interfaces.)
Interestingly this has been a continuing trend throughout the supercomputer industry, with former technology leaders such as Silicon Graphics taking a back seat to such companies as AMD and NVIDIA, who have been able to produce cheap, feature-rich, high-performance, and innovative products due to the vast number of consumers driving their R&D.
Historically, until the early-to-mid-1980s, supercomputers usually sacrificed instruction set compatibility and code portability for performance (processing and memory access speed). For the most part, supercomputers to this time (unlike high-end mainframes) had vastly different operating systems. The Cray-1 alone had at least six different proprietary OSs largely unknown to the general computing community. Similarly different and incompatible vectorizing and parallelizing compilers for Fortran existed. This trend would have continued with the ETA-10 were it not for the initial instruction set compatibility between the Cray-1 and the Cray X-MP, and the adoption of UNIX operating system variants (such as Cray's Unicos and today's Linux.)
For this reason, in the future, the highest performance systems are likely to use a variant of UNIX or a UNIX-like operating system but with incompatible system-unique features (especially for the highest-end systems at secure facilities).
Programming
The parallel architectures of supercomputers often dictate the use of special programming techniques to exploit their speed. Because Fortran has relatively few features and a simple programmatic model, special-purpose compilers can often generate faster code than C or C++ compilersFact|date=June 2008, so Fortran remains the language of choice for scientific programming, and hence for most programs run on supercomputersFact|date=June 2008. To exploit the parallelism of supercomputers, programming environments such as PVM and MPI for loosely connected clusters and OpenMP for tightly coordinated shared memory machines are being used.
Software tools
Software tools for distributed processing include standard APIs such as MPI and PVM, VTL and open source-based software solutions such as Beowulf, WareWulf and openMosix which facilitate the creation of a supercomputer from a collection of ordinary workstations or servers. Technology like ZeroConf (Rendezvous/Bonjour) can be used to create ad hoc computer clusters for specialized software such as Apple's Shake compositing application. An easy programming language for supercomputers remains an open research topic in computer science. Several utilities that would once have cost several thousands of dollars are now completely free thanks to the open source community which often creates disruptive technology in this arena.
Modern supercomputer architecture

thumb|IBM Roadrunner - LANL">
right|300pxAs of November 2006, the top ten supercomputers on the Top500 list (and indeed the bulk of the remainder of the list) have the same top-level architecture. Each of them is a cluster of MIMD multiprocessors, each processor of which is SIMD. The supercomputers vary radically with respect to the number of multiprocessors per cluster, the number of processors per multiprocessor, and the number of simultaneous instructions per SIMD processor. Within this hierarchy we have:
*A computer cluster is a collection of computers that are highly interconnected via a high-speed network or switching fabric. Each computer runs under a separate instance of an Operating System (OS).
*A multiprocessing computer is a computer, operating under a single OS and using more than one CPU, where the application-level software is indifferent to the number of processors. The processors share tasks using Symmetric multiprocessing (SMP) and Non-Uniform Memory Access (NUMA).
*A SIMD processor executes the same instruction on more than one set of data at the same time. The processor could be a general purpose commodity processor or special-purpose vector processor. It could also be high performance processor or a low power processor. As of 2007, the processor executes several SIMD instructions per nanosecond.As of July 2008 the fastest machine is IBM Roadrunner. This machine is a cluster of 3240 computers, each with 40 processing cores. By contrast, Columbia is a cluster of 20 machines, each with 512 processors, each of which processes two data streams concurrently.
Moore's Law and economies of scale are the dominant factors in supercomputer design: a single modern desktop PC is now more powerful than a ten-year old supercomputer, and the design concepts that allowed past supercomputers to out-perform contemporaneous desktop machines have now been incorporated into commodity PCs. Furthermore, the costs of chip development and production make it uneconomical to design custom chips for a small run and favor mass-produced chips that have enough demand to recoup the cost of production. A current model quad-core Xeon workstation running at 2.66 GHz will outperform a multimillion dollar Cray C90 supercomputer used in the early 1990s; most workloads requiring such a supercomputer in the 1990s can now be done on workstations costing less than 4,000 US dollars.
Additionally, many problems carried out by supercomputers are particularly suitable for parallelization (in essence, splitting up into smaller parts to be worked on simultaneously) and, particularly, fairly coarse-grained parallelization that limits the amount of information that needs to be transferred between independent processing units. For this reason, traditional supercomputers can be replaced, for many applications, by "clusters" of computers of standard design which can be programmed to act as one large computer.
Special-purpose supercomputers
Special-purpose supercomputers are high-performance computing devices with a hardware architecture dedicated to a single problem. This allows the use of specially programmed FPGA chips or even custom VLSI chips, allowing higher price/performance ratios by sacrificing generality. They are used for applications such as astrophysics computation and brute-force codebreaking.Historically a new special-purpose supercomputer has occasionally been faster than the world's fastest general-purpose supercomputer, by some measure. For example, GRAPE-6 was faster than the Earth Simulator in 2002 for a particular special set of problems.
Examples of special-purpose supercomputers:
*Belle, Deep Blue, and Hydra, for playing chess
*Reconfigurable computing machines or parts of machines
*GRAPE, for astrophysics and molecular dynamics
*Deep Crack, for breaking the DES cipher
*MDGRAPE-3, for protein structure computation
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