Distributed Computing: What Is It and Can It Be Useful

Distributed Computing: What Is It and Can It Be Useful

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Distributed Computing: What Is It and Can It Be Useful

A Brief Introduction

You can define distributed computing many different ways. Various vendors have created and marketed distributed computing systems for years, and have developed numerous initiatives and architectures to permit distributed processing of data and objects across a network of connected systems. They have developed a virtual environment where you can harness idle CPU cycles and storage space of tens, hundreds, or thousands of networked systems to work together on a particularly processing-intensive problem. The growth of such processing models has been limited, however, due to a lack of compelling applications and by bandwidth bottlenecks, combined with significant security, management, and standardization challenges. A number of new vendors have appeared to take advantage of the promising market; including Intel, Microsoft, Sun, and Compaq that have validated the importance of the concept.1 Also, an innovative worldwide distributed computing project whose goal is to find intelligent life in the universe--SETI@Home--has captured the imaginations, and desktop processing cycles of millions of users and desktops.
How It Works

The most powerful computer in the world, according to a recent ranking, is a machine called Janus, which has 9,216 Pentium Pro processors2. That's a lot of Pentiums, but it's a pretty small number in comparison with the 20 million or more processors attached to the global Internet. If you have a big problem to solve, recruiting a few percent of the CPUs on the Net would gain you more raw power than any supercomputer on earth. The rise of cooperative-computing projects on the Internet is both a technical and a social phenomenon. On the technical side, the key requirement is to slice a problem into thousands of tiny pieces that can be solved independently, and then to reassemble the answers. The social or logistical challenge is to find all those widely dispersed computers and persuade their owners to make them available.
In most cases today, a distributed computing architecture consists of very lightweight software agents installed on a number of client systems, and one or more dedicated distributed computing management servers. There may also be requesting clients with software that allows them to submit jobs along with lists of their required resources. An agent running on a processing client detects when the system is idle, notifies the management server that the system is available for processing, and usually requests an application package.

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The client then receives an application package from the server and runs the software when it has spare CPU cycles, and sends the results back to the server. The application may run as a screen saver, or simply in the background, without impacting normal use of the computer. If the user of the client system needs to run his own applications at any time, control is immediately returned, and processing of the distributed application package ends.3 This must be essentially instantaneous, as any delay in returning control will probably be unacceptable to the user.
What are some Applications

The following scenarios are examples of some types of application tasks that can be set up to take advantage of distributed computing.
Prime Numbers. For two decades, the weapon of choice in this elite sport was a supercomputer—preferably the latest model from Cray Research. Beginning in 1979, the prime-number pursuit was dominated by David Slowinski and his colleagues at Cray (which is now a division of Silicon Graphics).4 The Cray team had to keep topping their own records, because they had so little competition elsewhere. In 1996, however, a new largest prime was found with an unpretentious desktop PC. The discoverer was a member of an Internet consortium who attacked the problem collectively with a few thousand computers. In August of 1997 another member of the same group found a still larger prime, which stands as the current record. Slowinski, being a good sport, offered one of his supercomputers to verify the discoveries.5
Golomb rulers. Imagine a six-inch ruler with marks inscribed not at the usual equal intervals but at 0, 1, 4 and 6 inches. Taking all possible pairs of marks, you can measure six distinct distances: 1, 2, 3, 4, 5 and 6 inches. A ruler on which no two pairs of marks measure the same distance is called a Golomb ruler, after Solomon W. Golomb of the University of Southern California, who described the concept 25 years ago.6 The 0-1-4-6 example is a perfect Golomb ruler, in that all integer intervals from 1 to the length of the ruler are represented. On rulers with more than four marks, perfection is not possible; the best you can do is an optimal Golomb ruler, which for a given number of marks is the shortest ruler on which no intervals are duplicated.7
Aliens. If the prospect of finding a bigger prime number or a smaller Golomb ruler won't induce you to pledge your CPU, perhaps the chance to discover an extragalactic civilization might. That's where SETI@home comes in. SETI@home is the project of Dan Werthimer of the University of California at Berkeley and several colleagues.8 Their plans are ambitious; they seek a mass audience. The client software they envision would run as a screen saver, starting up automatically whenever a machine is left idle. As the program churned away on the data analysis, it would also display a series of images related to the project, such as a representation of the data currently being examined or a map showing the progress of the sky survey recorded with the radio telescope of the Arecibo Observatory in Puerto Rico.9
A search for extraterrestrial intelligence has been going on at Arecibo for almost two decades. The telescope slowly scans the sky, detecting emissions over a broad range of radio wavelengths. A special-purpose signal-processing computer applies a Fourier transform to the data to pick out narrow-bandwidth signals, which could be the alien equivalent of "I Love Lucy." The astronomers would like to put the data through a more thorough analysis, but computing capacity is a bottleneck. With enough computers on the job, the Arecibo data could be sliced into finer divisions of bandwidth and frequency. Moreover, the analysis software could check for other kinds of regularities, such as signals that pulsate or that "chirp" through a sequence of frequencies. The task is well suited to Internet computing in that only small blocks of data need to be passed back and forth over the network, but a great deal of computing is needed on each block.
Health Sciences and Genomes. Many of today's distributed system vendors are aiming squarely at the life sciences market, which has a sudden need for massive computing power. As a result of sequencing the human genome, the number of identifiable biological targets for today's drugs is expected to increase from about 500 to about 10,000. Pharmaceutical firms have repositories of millions of different molecules and compounds, some of which may have characteristics that make them appropriate for inhibiting newly found proteins. The process of matching all these "ligands" to their appropriate targets is an ideal task for distributed computing, and the quicker it's done, the quicker and greater the benefits will be. Another related application is the recent trend of generating new types of drugs solely on computers.10
Complex financial modeling, weather forecasting, and geophysical exploration are on the radar screens of these vendors, as well as car crash and other complex simulations. The possibilities for the uses seem limited only by the minds that can theorize their needs.
Fiscally Feasible?
Now the big question – How do we pay for this? One way proposed is through a commodity market in CPU cycles. If you have 100 computers with nothing to do nights and weekends, you offer the spare capacity at an asking price expressed in millicents per trillion instructions or dollars per Pentium-year, or some such fabricated unit. Meanwhile someone with a big batch of numbers to crunch enters a bid for a stated quantity of computation, measured in the same units. An automated clearinghouse matches up buyers and sellers.
It could be fun to watch the fluctuations of such a market. When some Hollywood studio needs half the processors in the galaxy to render scenes for the next Star Wars saga, prices shoot up. Over academic holidays, excess capacity brings on a seasonal slump. The market is likely to be volatile, because CPU cycles are like electricity or fresh asparagus: ‘You can't stockpile them for later use.' Trading in CPU cycles is not a new idea. As early as 1968 Ivan Sutherland wrote of a "futures market in computer time"—although his market consisted of only a whiteboard and colored pens.11

In the end, given a free flow of computations through all those 100 million nodes, I hope that we as a civilization can find a better use for this machine than what Janus had as a primary function - to simulate the explosion of nuclear weapons. I can foresee the pharmaceutical companies developing anti-cancer drugs; medical science developing diagnostic procedures for debilitating diseases, then finding cures; for meteorological and seismological agencies predicting and planning for natural disasters; for global economy analysis that aids in preventing food, grain and medical shortages in less-developed countries, which could then alleviate the need for the current deadly civil wars throughout the world. Granted these are very altruistic, and perhaps not events that all happen in my lifetime, but I have to believe that my idle CPU cycles can help in some small way. I have been utilizing the SETI@HOME software for awhile with no system problems or corruptions. Have I made any world changing discoveries or found the cure for any ailment – No. But at least I can say "I'm trying".
1. Distrubted.net Website http://www.distributed.net/
2. Distributed Computing Publisher: Springer-Verlag Heidelberg ISSN: 0178-2770 (Paper) 1432-0452 (Online) http://springerlink.metapress.com/
3. Grid.org, Website, http://www.grid.org/home.htm
4. Shoch, John F., and Jon A. Hupp. 1982. The "Worm" programsearly experience with a distributed computation. Communications of the ACM 25:172-180 http://doi.acm.org/10.1145/358453.358455
5. Ibid.
6. Golomb, Solomon W. 1972. How to number a graph. In Graph Theory and Computing, ed. Ronald C. Read. New York: Academic Press. http://commsci.usc.edu/faculty/golomb.html
7. Dollas, Apostolos, William T. Rankin and David McCracken. 1998. A new algorithm for Golomb ruler derivation and proof of the 19 mark ruler. IEEE Transactions on Information Theory 44:379-382. http://www.ieee.org/portal/index.jsp
8. SETI@Home, Website, http://setiathome.ssl.berkeley.edu
9. Ibid.
10. Parabon Computation, Inc. Website, http://www.parabon.com/
11. Sutherland, Ivan E. 1968. A futures market in computer time. Communications of the ACM 11:449-451. http://doi.acm.org/10.1145/363347.363396
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