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Asad Rizwan (03465596166) Sauood Danish Luqman Khan Abdullah Asad Sumra Jahangir Abbasi Anila Khanum NUML ISLAMABAD PAKISTAN PRESENTED BY:


A supercomputer is an extremely fast data-processing oriented computer. Supercomputers are also called "high-performance computers" because of their capability to crunch power measuring in gigaflops or billions of floating point operations. Supercomputers are used to solve complex computational problems, process hundreds of billions of calculations per second and simulate complex commercial research laboratories' and military sciences' experiments. INTRODUCTION


HISTORY A supercomputer is a computer that is at the frontline of current processing capacity, particularly speed of calculation. Supercomputers were introduced in the 1960s and were designed primarily by Seymour Cray at Control Data Corporation (CDC), which 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). In the 1980s a large number of smaller competitors entered the market, in 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 Hewlett-Packard, who had purchased many of the 1980s companies to gain their experience. Since October 2010, the Tianhe-1A supercomputer has been the fastest in the world; it is located in China .






SIGNIFICANCE Supercomputers with their faster-speed Central Processing Units (CPUs) are designed to do calculations and solve other computational problems faster than conventional powerful computers. They make use of a high-level of parallelism to enhance the processing speed. Supercomputers were earlier developed for weapons design research and development, national security purposes and university-led theoretical projects. Latest advances in power, performance and productivity have ensured that they are now also being retooled to run complex and varied mainstream industry and consumer applications.


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.


SUPER COMPUTER CHALLENGES, TECHNOLOGIES A supercomputer consumes large amounts of electrical power, almost all of which is converted into heat, requiring cooling. For example, Tianhe-1A consumes 4.04 Megawatts of electricity. The cost to power and cool the system is usually one of the factors that limit the scalability of the system. (For example, 4MW at $0.10/KWh is $400 an hour or about $3.5 million per year). Information cannot move faster than the speed of light between two parts of a supercomputer. For this reason, a supercomputer that is many meters 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 is a device for 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.


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 ( S ingle I nstruction M ultiple D ata) 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 Supercomputers today most often use variants of Linux. as shown by the graph to the right. 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. In a similar manner, 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 computer systems such as Cray's Unicos or Linux.




PROGRAMMING The parallel architectures of supercomputers often dictate the use of special programming techniques to exploit their speed. The base language of supercomputer code is, in general, Fortran or using special libraries to share data between nodes. In the most common scenario, environments such as PVM and MPI for loosely connected clusters and Open MP for tightly coordinated shared memory machines are used. Significant effort is required to optimize a problem for the interconnect characteristics of the machine it will be run on; the aim is to prevent any of the CPUs from wasting time waiting on data from other nodes. The new massively parallel GPGPUs have hundreds of processor cores and are programmed using programming models such as CUDA and Open CL.


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, Werewolf , 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 that often creates disruptive technology .


MODERN SUPERCOMPUTER ARCHITECTURE Supercomputers today often have a similar top-level architecture consisting of 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, wherein 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).


MODERN SUPERCOMPUTER ARCHITECTURE (Cont…) 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 October 2010 the fastest supercomputer in the world is the Tianhe-1A system at National University of Defense Technology with more than 21000 computers, it boasts a speed of 2.507 pet flops, over 30% faster than the world's next fastest computer, the Cray XT5 "Jaguar". In February 2009, IBM also announced work on "Sequoia," which appears to be a 20 pet flops supercomputer. This will be equivalent to 2 million laptops (whereas Roadrunner is comparable to a mere 100,000 laptops). It is slated for deployment in late 2011.The Sequoia will be powered by 1.6 million cores (specific 45-nanometer chips in development) and 1.6 pet bytes of memory. It will be housed in 96 refrigerators spanning roughly 3,000 square feet (280 m 2 ).


MODERN SUPERCOMPUTER ARCHITECTURE (Cont…) Moore's Law and economies of scale are the dominant factors in supercomputer design. The design concepts that allowed past supercomputers to out-perform desktop machines of the time tended to be gradually 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 be done on workstations costing less than 4,000 US dollars as of 2010. Supercomputing is taking a step of increasing density, allowing for desktop supercomputers to become available, offering the computer power that in 1998 required a large room to require less than a desktop footprint. In addition, many problems carried out by supercomputers are particularly suitable for parallelization (in essence, splitting up into smaller parts to be worked on simultaneously) and, in particular, 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 code breaking .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 D. E. Shaw Research Anton, for simulating molecular dynamics QPACE, for simulations of the strong interaction (Lattice QCD)


MEASURING SUPERCOMPUTER SPEED In general, the speed of a supercomputer is measured in "FLOPS" ( Floating Point Operations Per Second ), commonly used with an SI prefix such as tera, combined into the shorthand "TFLOPS" (10 12 FLOPS, pronounced teraflops ), or peta, combined into the shorthand "PFLOPS" (10 15 FLOPS, pronounced pet flops .) This measurement is based on a particular benchmark, which does LU decomposition of a large matrix. This mimics a class of real-world problems, but is significantly easier to compute than a majority of actual real-world problems. "Pet scale" supercomputers can process one quadrillion (10 15 ) (1000 trillion) FLOPS. Exascale is computing performance in the exaflops range. An exaflop is one quintillion (10 18 ) FLOPS (one million teraflops).




CURRENT FASTEST SUPERCOMPUTER SYSTEM Tianhe-1A is ranked on the TOP500 list as the fastest supercomputer. It consists of 14,336 Intel Xeon CPUs and 7,168 Nvidia Tesla M2050 GPUs with a new interconnect fabric of Chinese origin, reportedly twice the speed of InfiniBand.Tianhe-1A spans 103 cabinets, weighs 155 tons, and consumes 4.04 megawatts of electricity.


TIMELINE OF SUPERCOMPUTERS 1938 Zuse Z1 1 OPS Konrad Zuse , Berlin, Germany 1941 Zuse Z3 20 OPS Konrad Zuse , Berlin, Germany 1943 Colossus 1 5 kOPS Post Office Research Station, Bletchley Park , UK 1944 Colossus 2 (Single Processor) 25 kOPS Post Office Research Station, Bletchley Park , UK 946 Colossus 2 (Parallel Processor) 50 kOPS Post Office Research Station, Bletchley Park , UK 1946 UPenn ENIAC (before 1948+ modifications) 5 kOPS Department of War Aberdeen Proving Ground, Maryland, USA 1954 IBM NORC 67 kOPS Department of Defense U.S. Naval Proving Ground , Dahlgren, Virginia, USA 1956 MIT TX-0 83 kOPS Massachusetts Inst. of Technology, Lexington, Massachusetts , US


TIMELINE OF SUPER-COMPUTERS(Cont…..) 1958 IBM AN/FSQ-7 400 kOPS 25 U.S. Air Force sites across the continental USA and 1 site in Canada (52 computers) 1960 UNIVAC LARC 250 kFLOPS Atomic Energy Commission (AEC) Lawrence Livermore National Laboratory, California, USA 1961 IBM 7030 "Stretch" 1.2 MFLOPS AEC-Los Alamos National Laboratory , New Mexico, USA 1964 CDC 6600 3 MFLOPS AEC-Lawrence Livermore National Laboratory, California, USA 1969 CDC 7600 36 MFLOPS 1974 CDC STAR-100 100 MFLOPS 1975 Burroughs ILLIAC IV 150 MFLOPS NASA Ames Research Center, California, USA


TIMELINE OF SUPER-COMPUTERS(Cont…..) 1976 Cray-1 250 MFLOPS Energy Research and Development Administration (ERDA ) Los Alamos National Laboratory, New Mexico, USA (80+ sold worldwide) 1981 CDC Cyber 205 400 MFLOPS (~40 systems worldwide) 1983 Cray X-MP/4 941 MFLOPS U.S. Department of Energy (DoE) Los Alamos National Laboratory; Lawrence Livermore National Laboratory; Battelle; Boeing 1984 M-13 2.4 GFLOPS Scientific Research Institute of Computer Complexes, Moscow, USSR 1985 Cray-2/8 3.9 GFLOPS DoE-Lawrence Livermore National Laboratory, California, USA 1989 ETA10-G/8 10.3 GFLOPS Florida State University, Florida, USA 1990 NEC SX-3/44R 23.2 GFLOPS NEC Fuchu Plant, Fuchu, Tokyo , Japan


TIMELINE OF SUPER-COMPUTERS(Cont…..) 1993 Thinking Machines CM-5/1024 59.7 GFLOPS DoE-Los Alamos National Laboratory; National Security Agency, USA 1993 Fujitsu Numerical Wind Tunnel 124.50 GFLOPS National Aerospace Laboratory, Tokyo, Japan 1993 Intel Paragon XP/S 140 143.40 GFLOPS DoE-Sandia National Laboratories, New Mexico, USA 1994 Fujitsu Numerical Wind Tunnel 170.40 GFLOPS National Aerospace Laboratory, Tokyo, Japan 1996 Hitachi SR2201/1024 220.4 GFLOPS University of Tokyo, Japan Hitachi/Tsukuba CP-PACS/2048 368.2 GFLOPS Center for Computational Physics, University of Tsukuba, Tsukuba, Japan 1997 Intel ASCI Red/9152 1.338 TFLOPS DoE -Sandia National Laboratories, New Mexico, USA 1999 Intel ASCI Red/9632 2.3796 TFLOPS DoE-Sandia National Laboratories, New Mexico, USA


TIMELINE OF SUPER-COMPUTERS(Cont…..) 2000A IBM ASCI White 7.226 TFLOPS DoE-Lawrence Livermore National Laboratory, California, USA 2002 NEC Earth Simulator 35.86 TFLOPS Earth Simulator Center, Yokohama, Japan 2004 IBM Blue Gene/L 70.72 TFLOPS DoE/IBM Rochester, Minnesota, USA 2005 BM Blue Gene/L 136.8 TFLOPS DoE/U.S. National Nuclear Security Administration, Lawrence Livermore National Laboratory, California, USA 2007 IBM Blue Gene/L 280.6 TFLOPS DoE/U.S. National Nuclear Security Administration, Lawrence Livermore National Laboratory, California, USA 2008 IBM Roadrunner DoE-Los Alamos National Laboratory, New Mexico, USA 1.105 PFLOPS


TIMELINE OF SUPER-COMPUTERS(Cont…..) 2009 Cray Jaguar 1.759 PFLOPS DoE-Oak Ridge National Laboratory, Tennessee, USA 2010 Tianhe-IA 2.566 PFLOPS National Supercomputing Center, Tianjin, China


MAJOR VENDORS Tech giants IBM and Hewlett-Packard (HP) are the top two vendors manufacturing a variety of supercomputer systems to suit the requirements of sectors and businesses. IBM's Blue Gene Supercomputer series has facilitated breakthroughs in science, analytics and energy efficiency. IBM's Roadrunner supercomputer is configured to function for the current era of the Internet and cloud computing and will provide enhanced and massive computing power for mainstream applications. HP's Unified Cluster Portfolio supercomputers are used by U.S. Department of Defense (DoD) and other civilian and defense agencies.





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