Transcript
Computer, machine that performs tasks, such as calculations or electronic communication,
under the control of a set of instructions called a program. Programs usually reside within the
computer and are retrieved and processed by the computer’s electronics. The program results are
stored or routed to output devices, such as video display monitors or printers. Computers perform
a wide variety of activities reliably, accurately, and quickly.
Personal Computer (PC), computer in the form of a desktop or laptop device designed for use
by a single person. PCs function using a display monitor and a keyboard. Since their introduction
in the 1980s, PCs have become powerful and extremely versatile tools that have revolutionized
how people work, learn, communicate, and find entertainment. Many households in the United
States now have PCs, thanks to affordable prices and software that has made PCs easy to use
without special computer expertise. Personal computers are also a crucial component of
information technology (IT) and play a key role in modern economies worldwide.
The usefulness and capabilities of personal computers can be greatly enhanced by connection to
the Internet and World Wide Web, as well as to smaller networks that link to local computers or
databases. Personal computers can also be used to access content stored on compact discs (CDs)
or digital versatile discs (DVDs), and to transfer files to personal media devices and video
players.
Personal computers are sometimes called microcomputers or micros. Powerful PCs designed for
professional or technical use are known as work stations. Other names that reflect different roles
for PCs include home computers and small-business computers. The PC is generally larger and
more powerful than handheld computers, including personal digital assistants (PDAs) and
gaming devices.
Workstation, in computer science, in general, a combination of input, output, and computing
hardware that can be used for work by an individual. More often, however, the term refers to a
powerful stand-alone computer of the sort used in computer-aided design and other applications
requiring a high-end, usually expensive, machine ($10,000 to $100,000) with considerable
calculating or graphics capability. Sometimes, workstation is also used to refer to a
microcomputer or terminal connected to a network. See also Computer-Aided Design/Computer-
Aided Manufacturing.
Minicomputer, a mid-level computer built to perform complex computations while dealing
efficiently with a high level of input and output from users connected via terminals.
Minicomputers also frequently connect to other minicomputers on a network and distribute
processing among all the attached machines. Minicomputers are used heavily in transaction-
processing applications and as interfaces between mainframe computer systems and wide area
networks. See also Office Systems; Time-Sharing.
Mainframe Computer, a high-level computer designed for the most intensive computational
tasks. Mainframe computers are often shared by multiple users connected to the computer via
terminals. The most powerful mainframes, called supercomputers, perform highly complex and
time-consuming computations and are used heavily in both pure and applied research by
scientists, large businesses, and the military.
Mainframe computers have more memory, speed, and capabilities than workstations and are
usually shared by multiple users through a series of interconnected computers.
The most powerful mainframe computers, called supercomputers, process complex and time-
consuming calculations, such as those used to create weather predictions. Large businesses,
scientific institutions, and the military use them. Some supercomputers have many sets of CPUs.
These computers break a task into small pieces, and each CPU processes a portion of the task to
increase overall speed and efficiency. Such computers are called parallel processors. As
computers have increased in sophistication, the boundaries between the various types have
become less rigid. The performance of various tasks and types of computing have also moved
from one type of computer to another. For example, networked PCs can work together on a given
task in a version of parallel processing known as distributed computing.
Supercomputer, computer designed to perform calculations as fast as current technology allows
and used to solve extremely complex problems. Supercomputers are used to design automobiles,
aircraft, and spacecraft; to forecast the weather and global climate; to design new drugs and
chemical compounds; and to make calculations that help scientists understand the properties of
particles that make up atoms as well as the behavior and evolution of stars and galaxies.
Supercomputers are also used extensively by the military for weapons and defense systems
research, and for encrypting and decoding sensitive intelligence information.
Supercomputers are different than other types of computers in that they are designed to work on
a single problem at a time, devoting all their resources to the solution of the problem. Other
powerful computers such as mainframes and workstations are specifically designed so that they
can work on numerous problems, and support numerous users, simultaneously. Because of their
high cost—usually in the hundreds of thousands to millions of dollars—supercomputers are
shared resources. Supercomputers are so expensive that usually only large companies,
universities, and government agencies and laboratories can afford them.
II.
HOW SUPERCOMPUTERS WORK
The two major components of a supercomputer are the same as any other computer—a central
processing unit (CPU) where instructions are carried out, and the memory in which data and
instructions are stored. The CPU in a supercomputer is similar in function to a standard personal
computer (PC) CPU, but it usually has a different type of transistor technology that minimizes
transistor switching time. Switching time is the length of time that it takes for a transistor in the
CPU to open or close, which corresponds to a piece of data moving or changing value in the
computer. This time is extremely important in determining the absolute speed at which a CPU
can operate. By using very high performance circuits, architectures, and, in some cases, even
special materials, supercomputer designers are able to make CPUs that are 10 to 20 times faster
than state-of-the-art processors for other types of commercial computers.
Supercomputer memory also has the same function as memory in other computers, but it is
optimized so that retrieval of data and instructions from memory takes the least amount of time
possible. Also important to supercomputer performance is that the connections between the
memory and the CPU be as short as possible to minimize the time that information takes to travel
between the memory and the CPU.
A supercomputer functions in much the same way as any other type of computer, except that it is
designed to do calculations as fast as possible. Supercomputer designers use two main methods
to reduce the amount of time that supercomputers spend carrying out instructions—pipelining
and parallelism. Pipelining allows multiple operations to take place at the same time in the
supercomputer’s CPU by grouping together pieces of data that need to have the same sequence
of operations performed on them and then feeding them through the CPU one after the other. The
general idea of parallelism is to process data and instructions in parallel rather than in sequence.
In pipelining, the various logic circuits (electronic circuits within the CPU that perform
arithmetic calculations) used on a specific calculation are continuously in use, with data
streaming from one logic unit to the next without interruption. For instance, a sequence of
operations on a large group of numbers might be to add adjacent numbers together in pairs
beginning with the first and second numbers, then to multiply these results by some constant, and
finally to store these results in memory. The addition operation would be Step 1, the
multiplication operation would be Step 2, and the assigning of the result to a memory location
would be Step 3 in the sequence. The CPU could perform the sequence of operations on the first
pair of numbers, store the result in memory and then pass the second pair of numbers through,
and continue on like this. For a small group of numbers this would be fine, but since
supercomputers perform calculations on massive groups of numbers this technique would be
inefficient, because only one operation at a time is being performed.
Pipelining overcomes the source of inefficiency associated with the CPU performing a sequence
of operations on only one piece of data at a time until the sequence is finished. The pipeline
method would be to perform Step 1 on the first pair of data and move it to Step 2. As the result
of the first operation move to Step 2, the second pair of data move into Step 1. Step 1 and 2 are
then performed simultaneously on their respective data and the results of the operations are
moved ahead in the pipeline, or the sequence of operations performed on a group of data. Hence
the third pair of numbers are in Step 1, the second pair of numbers are in Step 2, and the first pair
of numbers are in Step 3. The remainder of the calculations are performed in this way, with the
specific logic units in the sequence are always operating simultaneously on data.
The example used above to illustrate pipelining can also be used to illustrate the concept of
parallelism (see Parallel Processing). A computer that parallel-processed data would perform
Step 1 on multiple pieces of data simultaneously, then move these to Step 2, then to Step 3, each
step being performed on the multiple pieces of data simultaneously. One way to do this is to have
multiple logic circuits in the CPU that perform the same sequence of operations. Another way is
to link together multiple CPUs, synchronize them (meaning that they all perform an operation at
exactly the same time) and have each CPU perform the necessary operation on one of the pieces
of data.
Pipelining and parallelism are combined and used to greater or lesser extent in all
supercomputers. Until the early 1990s, parallelism achieved through the interconnection of CPUs
was limited to between 2 and 16 CPUs connected in parallel. However, the rapid increase in
processing speed of off-the-shelf microprocessors used in personal computers and workstations
made possible massively-parallel processing (MPP) supercomputers. While the individual
processors used in MPP supercomputers are not as fast as specially designed supercomputer
CPUs, they are much less expensive and because of this, hundreds or even thousands of these
processors can be linked together to achieve extreme parallelism.
III.
SUPERCOMPUTER PERFORMANCE
Supercomputers are used to create mathematical models of complex phenomena. These models
usually contain long sequences of numbers that are manipulated by the supercomputer with a
kind of mathematics called matrix arithmetic. For example, to accurately predict the weather,
scientists use mathematical models that contain current temperature, air pressure, humidity, and
wind velocity measurements at many neighboring locations and altitudes. Using these numbers
as data, the computer makes many calculations to simulate the physical interactions that will
likely occur during the forecast period.
When supercomputers perform matrix arithmetic on large sets of numbers, it is often necessary
to multiply many pairs of numbers together and to then add up each of their individual products.
A simple example of such a calculation is: (4 × 6) + (7 × 2) + (9 × 5) + (8 × 8) + (2 × 9) = 165.
In real problems, the strings of numbers used in calculations are usually much longer, often
containing hundreds or thousands of pairs of numbers. Furthermore, the numbers used are not
simple integers but more complicated types of numbers called floating point numbers that allow
a wide range of digits before and after the decimal point, for example 5,063,937.9120834.
The various operations of adding, subtracting, multiplying, and dividing floating-point numbers
are collectively called floating-point operations. An important way of measuring a
supercomputer’s performance is in the peak number of floating-point operations per second
(FLOPS or, more commonly, FLOP) that it can do. In the mid-1990s, the peak computational
rate for state-of-the-art supercomputers was between 1 and 200 gigaflops (billion floating-point
operations per second), depending on the specific model and configuration of the supercomputer.
In July 1995, computer scientists at the University of Tokyo, in Japan, broke the 1 teraflop (1
trillion floating-point operations per second) mark with a computer they designed to perform
astrophysical simulations. Named GRAPE-4 (GRAvity PipE number 4), this MPP
supercomputer consisted of 1,692 interconnected processors. In November 1996, Cray Research
debuted the CRAY T3E-900, the first commercially available supercomputer to offer teraflop
performance. In 1997 the Intel Corporation installed the teraflop machine Janus at Sandia
National Laboratories in New Mexico. Janus is composed of 9,072 interconnected processors.
Scientists use Janus for classified work such as weapons research as well as for unclassified
scientific research such as modeling the impact of a comet on the Earth.
In 2007 the International Business Machines Corporation (IBM) announced that it was
introducing the first commercial supercomputer capable of petaflop performance. A petaflop is
the equivalent of 1,000 trillion, or 1 quadrillion, floating-point operations per second. Known as
the Blue Gene/P, the supercomputer uses nearly 300,000 processors connected by a high-speech
optical fiber network. It can be expanded to include nearly 900,000 processors, enabling it to
achieve a performance speed of 3 petaflops. The Department of Energy’s Argonne National
Laboratory purchased the first Blue Gene/P in the United States and was expected to use it for
complex simulations in particle physics and nanotechnology.
The definition of what a supercomputer is constantly changes with technological progress. The
same technology that increases the speed of supercomputers also increases the speed of other
types of computers. For instance, the first computer to be called a supercomputer, the Cray-1
developed by Cray Research and first sold in 1976, had a peak speed of 167 megaflops. This is
only a few times faster than standard personal computers today, and well within the reach of
some workstations.