Supercomputer

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A supercomputer is a computer that led the world (or was close to doing so) in terms 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. Page 95 identifies the article as . 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 The Columbia Difference Tabulator - 1931 to refer to large custom-built Tabulating machines IBM made for Columbia University.

Overview Concise industry history 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 IBM and Hewlett-Packard, who had purchased many of the 1980s companies to gain their experience, although Cray Inc. still specializes in building supercomputers.

was the world's fastest computer from 1985 to 1989.

The term supercomputer itself is rather fluid, and today's supercomputer tends to become tomorrow's normal 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" central processing units, some being commercial off-the-shelfs and others being custom designs. (This is commonly and humorously referred to as the attack of the killer micros in the industry.) Today, parallel designs are based on "off the shelf" server-class microprocessors, such as the PowerPC, Itanium, or x86-64, and most modern supercomputers are now highly-tuned computer clusters using commodity processors combined with custom interconnects.

Software tools Software tools for distributed processing include standard Application programming interfaces such as Message Passing Interface and Parallel Virtual Machine, and open source-based software solutions such as Beowulf (computing) and openMosix which facilitate the creation of a supercomputer from a collection of ordinary workstations or servers. Technology like ZeroConf can be used to create ad hoc computer clusters for specialized software such as Apple Computer Shake (software) compositing application. An easy programming language for supercomputers remains an open research topic in computer science.

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), computational chemistry (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. Oftentimes 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 accelerate the remaining bottleneck (engineering)s.

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 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 CPU bound problems into IO 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
Data striping (the first instance of what was later called redundant array of independent disks)
filesystem

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 FLOPS. 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 or Unix. Linux is the most popular since 2004 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 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 have a UNIX flavor 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. Special-purpose Fortran compilers can often generate faster code than C (programming language) or C++ compilers, so Fortran remains the language of choice for scientific programming, and hence for most programs run on supercomputers. To exploit the parallelism of supercomputers, programming environments such as Parallel Virtual Machine and Message Passing Interface for loosely connected clusters and OpenMP for tightly coordinated shared memory machines are being used.

Modern supercomputer architecture at NASA's Advanced Supercomputing Facility at Ames Research Center|right|300px

As 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).
An 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 November 2006, the fastest machine is Blue Gene/L. This machine is a cluster of 65,536 computers, each with two processors, each of which processes two data streams concurrently. By contrast, Columbia (supercomputer) is a cluster of 20 machines, each with 512 processors, each of which processes two data streams concurrently.

As of 2005, Moore's Law and economy of scale are the dominant factors in supercomputer design:a single modern desktop PC is now more powerful than a 15-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 2.66Ghz will outperform a multimillion dollar cray C90 supercomputer used in the early 1990s, lots of workloads requiring such a supercomputer in the 1990s can now be done on workstations costing less than 4000 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 Field-programmable gate array chips or even custom Very-large-scale integration 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:

IBM Deep Blue, for playing chess
Reconfigurable computing machines or parts of machines
GRAvity PipE, for astrophysics and molecular dynamics
Deep Crack, for breaking the Data Encryption Standard cipher

The fastest supercomputers today Measuring supercomputer speed The speed of a supercomputer is generally measured in "FLOPS" (FLoating Point Operations Per Second), commonly used with an SI prefix such as tera-, combined into the shorthand "TFLOPS" (1012 FLOPS, pronounced teraflops), or peta-,combined into the shorthand "PFLOPS" (1015 FLOPS, pronounced petaflops.) This measurement is based on a particular benchmark (computing) 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.

The Top500 list Since 1993, the fastest supercomputers have been ranked on the Top500 list according to their LINPACK benchmark results. The list does not claim to be unbiased or definitive, but it is the best current definition of the "fastest" supercomputer available at any given time.

Current fastest supercomputer system

As of August 2007, the IBM Blue Gene/L at LLNL is the fastest operational supercomputer, with a sustained processing rate of 280 TFLOPS.On June 26, 2007, IBM unveiled Blue Gene/P, the second generation of the Blue Gene supercomputer. These computers can sustain one PFLOPS. IBM has announced that several customers will install these systems later in 2007. One of these is likely to become the fastest deployed supercomputer at that time.

The MDGRAPE-3 supercomputer, which was completed in June 2006, reportedly reached one PFLOPS calculation speed, though it may not qualify as a general-purpose supercomputer as its specialized hardware is optimized for molecular dynamics simulations. See:

Quasi-supercomputing Some types of large-scale distributed computing for embarrassingly parallel problems take the clustered supercomputing concept to an extreme.

One such example is the BOINC platform, a host for a number of distributed computing projects. On March 27th 2007, BOINC recorded a processing power of over 530.7 TFLOPS through 1,797,000 plus computers on the network . The largest project, SETI@home, reported processing power of 276.3 TFLOPS through 1,390,000 plus computers .

Another distributed computing project, Folding@home, reported nearly 1.3 PFLOPS of processing power in late September 2007. A little over 1 PFLOPS of this processing power is contributed by clients running on PlayStation 3 systems.

Great Internet Mersenne Prime Search's distributed Mersenne Prime search achieves currently 23 TFLOPS (as of October 2007).

Google's search engine Google platform may be faster with estimated total processing power of between 126 and 316 TFLOPS. The New York Times estimates that the Googleplex and its server farms contain 450,000 servers. The New York Times, June 14, 2006

Research and Development On September 9, 2006 the United States Department of Energy National Nuclear Security Administration (NNSA) selected IBM to design and build the world's first supercomputer to use the Cell Broadband Engine™ (Cell B.E.) processor aiming to produce a machine capable of a sustained speed of up to 1,000 trillion calculations per second, or one PFLOPS.

In India, a project is under the leadership of Narendra Karmarkar is also developing a supercomputer that can reach one PFLOPS.

CDAC is also building a supercomputer that can reach one PFLOPS by 2010. C-DAC 's Param programme sets to touch 10 teraflops by late 2007 and a petaflops by 2010.

Another project is Cyclops64.

Timeline of supercomputers This is a list of the record-holders for fastest general-purpose supercomputer in the world, and the year each one set the record.For entries prior to 1993, this list refers to various sources. From 1993 to present, the list reflects the Top500 listing.

{]|Atanasoff–Berry Computer|align=right|30 OPS|Iowa State University, Ames, Iowa, United States|-|Telecommunications Research Establishment Heath Robinson (codebreaking machine)|align=right|200 OPS|Bletchley Park|[Tommy Flowers Colossus computer|align=right|5 kOPS|Post Office Research Station, Dollis Hill
|[University of Pennsylvania ENIAC
(before 1948+ modifications) ], Maryland, United States
|-|1954 [IBM NORC|align=right|67 kOPS|Naval Surface Warfare Center Dahlgren Division, Dahlgren, Virginia, Virginia, United States|-|1956 [TX-0, [Lexington, Massachusetts, Massachusetts, United States|-|1958 [AN/FSQ-7 sites across the [continental United States and 1 site in Canada (52 computers)]|UNIVAC UNIVAC LARC|align=right|250 kFLOPS |Lawrence Livermore National Laboratory, California, United States|-|1961|align=right|1.2 MFLOPS|[Los Alamos National Laboratory, New Mexico, United States|-|1964|align=right|3 MFLOPS|rowspan="3" valign="top"|[Lawrence Livermore National Laboratory, California, United States|-|1969|align=right|36 MFLOPS|-|[1974|align=right|100 MFLOPS|-|[1975 [ILLIAC IV, [California, United States|- valign="top"|1976|align=right|250 MFLOPS|[Los Alamos National Laboratory, New Mexico, United States (80+ sold worldwide)|-|1981|align=right|400 MFLOPS|(numerous sites worldwide)|-|[1983/4|align=right|941 MFLOPS|[Los Alamos National Laboratory; Lawrence Livermore National Laboratory; Battelle Memorial Institute; Boeing|[M-13 (computer)|align=right|2.4 GFLOPS|Scientific Research Institute of Computer Complexes, Moscow, Soviet Union|-|1985/8|align=right|3.9 GFLOPS|[Lawrence Livermore National Laboratory, California, United States|-|1989-G/8|align=right|10.3 GFLOPS|[Florida State University, Florida, United States|-|1990 SX-3/44R|align=right|23.2 GFLOPS|[NEC Corporation Fuchu Plant, Fuchu, Japan|[Thinking Machines Connection Machine-5/1024|align=right|65.5 GFLOPS|Los Alamos National Laboratory; National Security Agency [Numerical Wind Tunnel, [Tokyo, Japan [Intel Paragon XP/S 140|align=right|143.40 GFLOPS|Sandia National Laboratories, New Mexico, United States|-|1994 [Numerical Wind Tunnel, [Tokyo, Japan|[Hitachi, Ltd. SR2201/1024|align=right|220.4 GFLOPS|University of Tokyo, Japan/[Tsukuba CP-PACS/2048], University of Tsukuba, Tsukuba, Japan|[Intel ASCI Red/9152], New Mexico, United States|-|1999 [ASCI Red/9632]|IBM ASCI White, [California, United States|-|2002 [Earth Simulator, [Yokohama-shi, Japan|rowspan="3" valign="top"|[IBM Blue Gene|align=right|70.72 TFLOPS |United States Department of Energy/IBM, United States|- valign="top"|rowspan="2"|2005/[United States National Nuclear Security Administration,
Lawrence Livermore National Laboratory, California, United States|-|align=right|280.6 TFLOPS |-|}

See also General concepts, history

Beowulf cluster
Distributed computing
Flash mob computer
Grid computing
High-performance computing (HPC)
History of computing
MOSIX
Parallel computing
Metacomputing
Quantum computer

Other classes of computer

Minisupercomputer
Mainframe computer
Superminicomputer
Minicomputer
Microcomputer

Supercomputer companies in operation These companies make supercomputer hardware and/or software, either as their sole activity, or as one of several activities.

Cray Inc.
Fujitsu
Groupe Bull
CDAC
IBM
Microsoft Cluster Server
nCUBE
NEC Corporation
Quadrics
Sun Microsystems
Silicon Graphics

Defunct supercomputer companies These companies have either folded, or no longer operate in the supercomputer market.

Control Data Corporation
Convex Computer
Kendall Square Research
MasPar
Meiko Scientific
Sequent Computer Systems
Thinking Machines

Notes

External links Information resources

TOP500 Supercomputer list
LinuxHPC.org Linux High Performance Computing and Clustering Portal
WinHPC.org Windows High Performance Computing and Clustering Portal
Cluster Resources
Cluster Builder
CDAC
Microsoft Windows Compute Cluster Server (CCS)
Infiscale Cluster Portal - Free GPL HPC Resources
Supercomputing Online Homepage for the World's High-Performance Computing, Networking & Storage Professionals

Supercomputing centers, organizations Organizations

DEISA Distributed European Infrastructure for Supercomputing Applications, a facility integrating eleven European supercomputing centers.
EPCC Edinburgh Parallel Computing Centre. Based in the University of Edinburgh.
NAREGI Japanese NAtional REsearch Grid Initiative involving several supercomputer centers
Research Computing Services ( web site) at the University of Manchester.
TeraGrid, a national facility integrating nine US supercomputing centers

Centers

ARSC Arctic Region Supercomputing Center at University of Alaska Fairbanks
BSC Barcelona Supercomputing Center - Spanish national supercomputing facility and R&D center
CESCA Supercomputing Centre of Catalonia - Centre de Supercomputacio de Catalunya
CESGA Galicia Supercomputing Center - Centro de Supercomputación de Galicia
CINECA CINECA Interuniversity Consortium, Italy
CSAR UK national supercomputer service operated by Manchester Computing
GSIC Global Scientific Information and Computing Center at the Tokyo Institute of Technology
HPCx UK national supercomputer service operated by EPCC and Daresbury Lab
IRB
NASA Advanced Supercomputing facility
National Center for Atmospheric Research (NCAR)
National Center for Supercomputing Applications (NCSA)
Ohio Supercomputer Center (OSC)
Pittsburgh Supercomputing Center operated by University of Pittsburgh and Carnegie Mellon University.
San Diego Supercomputer Center (SDSC)
SARA (Stichting Academisch Rekencentrum Amsterdam), Amsterdam, The Netherlands
System X at Virginia Polytechnic Institute and State University
Texas Advanced Computing Center (TACC)
WestGrid
TCHPC Trinity Centre for High Performance Computing. Based in the University of Dublin.
DCSC Danish Centre for Scientific Computing. Based at the University of Copenhagen.
PSNC (Poznan Supercomputing and Networking Center), Poznan, Poland

Specific machines, general-purpose

Linux NetworX press release: Linux NetworX to build "largest" Linux supercomputer
ASCI White press release
Article about Japanese "Earth Simulator" computer
"Earth Simulator" website (in English)
NEC high-performance computing information
Superconducting Supercomputer

Specific machines, special-purpose

Papers on the GRAPE special-purpose computer
More special-purpose supercomputer information
Information about the APEmille special-purpose computer
Information about the apeNEXT special-purpose computer
Information about the QCDOC project, machines

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supercomputer • noun a particularly powerful mainframe computer. Perform another search of the Compact Oxford English Dictionary . About this dictionary