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4.1 QCD and the Beginning of CP


The Caltech Concurrent Computation Project started with QCD,  or Quantum Chromodynamics,  as its first application. QCD is discussed in more detail in Sections 4.2 and 4.3, but here we will put in the historical perspective. This nostalgic approach is developed in [Fox:87d], [Fox:88oo] as well as Chapters 1 and 2 of this book.

We show, in Table 4.1, fourteen QCD simulations, labelled by representative physics publications, performed within CP using parallel machines. This activity started in 1981 with simulations, using the first four-node 8086-8087-based prototypes of the Cosmic Cube. These prototypes were quite competitive in performance with the VAX 11/780 on which we had started (in 1980) our computational physics program within high energy physics  at Caltech. The 64-node Cosmic Cube  was used more or less continuously from October, 1983 to mid-1984 on what was termed by Caltech, a ``mammoth calculation'' in the press release shown in Figure 4.2. This is the modest, four-dimensional lattice calculation reported in line 3 of Table 4.1. As trumpeted in Figures 4.1 and 4.2, this was our first major use of parallel machines and a critical success on which we built our program.

Table 4.1: Quantum Chromodynamic (QCD) Calculations Within CP

Our 1983-1984 calculations totalled some 2,500 hours on the 64-node Cosmic Cube and successfully competed with 100-hour CDC  Cyber 205 computations that were the state of the art at the time [Barkai:84b], [Barkai:84c], [Bowler:85a], [DeForcrand:85a]. We used a four-dimensional lattice with grid points, with eight gluon field values defined on each of the 110,592 links between grid points. The resultant 884,736 degrees of freedom seem modest today as QCD practitioners contemplate lattices of order simulated on machines of teraFLOP  performance [Aoki:91a]. However, this lattice was comparable to those used on vector supercomputers at the time.

A hallmark of this work was the interdisciplinary team building hardware, software, and parallel application. Further, from the start we stressed large supercomputer-level simulations where parallelism would make the greatest initial impact. It was also worth noting that our use of comparatively high-level software paid off-Otto and Stack were able to code better algorithms [Parisi:83a] than the competing vector supercomputer teams. The hypercube could be programmed conveniently without use of microcode or other unproductive environments needed on some of the other high-performance machines of the time.

Our hypercube calculations used an early C plus message-passing programming approach which later evolved into the Express system described in the next chapter. Although not as elegant as data-parallel C and Fortran (discussed in Chapter 13), our approach was easier than hand-coded assembly, which was quite common for alternative high-performance systems of the time.

Figures 4.1 and 4.2 show extracts from Caltech and newspaper publicity of the time. We were essentially only a collection of 64 IBM PCs. Was that a good thing (as we thought) or an indication of our triviality (as a skeptical observer commenting in Figure 4.1 thought)? 1985 saw the start of a new phase as conventional supercomputers and availability increased in power and NSF and DOE allocated many tens of thousands of hours on the CRAY X-MP  (2, Y-MP) and ETA-10 to QCD simulations. Our final QCD hypercube calculations in 1989 within CP used a 64-node JPL Mark IIIfp with approximately performance. Since this work, we switched to using the Connection Machine  CM-2, which by 1990 was the commercial standard in the field. CP helped the Los Alamos group of Brickner and Gupta (one of our early graduates!) to develop the first CM-2 QCD codes, which in 1991 performed at on the full size CM-2 [Brickner:91a], [Liu:91a].

Caltech Scientists Develop `Parallel' Computer Model By LEE DEMBART
Times Science Writer Caltech scientists have developed a working prototype for a new super computer that can perform many tasks at once, making possible the solution of important science and engineering problems that have so far resisted attack.

The machine is one of the first to make extensive use of parallel processing, which has been both the dream and the bane of computer designers for years.

Unlike conventional computers, which perform one step at a time while the rest of the machine lies idle, parallel computers can do many things at the same time, holding out the prospect of much greater computing speed than currently available-at much less cost.

If its designers are right, their experimental device, called the Cosmic Cube, will open the way for solving problems in meteorology,  aerodynamics,  high-energy physics, seismic  analysis, astrophysics  and oil exploration, to name a few. These problems have been intractable because even the fastest of today's computers are too slow to process the mountains of data in a reasonable amount of time.

One of today's fastest computers is the Cray 1, which can do 20 million to 80 million operations a second. But at $5 million, they are expensive and few scientists have the resources to tie one up for days or weeks to solve a problem.

``Science and engineering are held up by the lack of super computers,'' says one of the Caltech inventors, Geoffrey C. Fox, a theoretical physicist. ``They know how to solve problems that are larger than current computers allow.''

The experimental device, 5 feet long by 8 inches high by 14 inches deep, fits on a desk top in a basement laboratory, but it is already the most powerful computer at Caltech. It cost $80,000 and can do three million operations a second-about one-tenth the power of a Cray 1.

Fox and his colleague, Charles L. Seitz, a computer scientist, say they can expand their device in coming years so that it has 1,000 times the computing power of a Cray.

``Poor old Cray and Cyber (another super computer) don't have much of a chance of getting any significant increase in speed,'' Fox said. ``Our ultimate machines are expected to be at least 1,000 times faster than the current fastest computers.''

``We are getting to the point where we are not going to be talking about these things as fractions of a Cray but as multiples of them,'' Seitz said.

But not everyone in the field is as impressed with Caltech's Cosmic Cube as its inventors are. The machine is nothing more nor less than 64 standard, off-the-shelf microprocessors wired together, not much different than the innards of 64 IBM personal computers working as a unit.

``We are using the same technology used in PCs (personal computers) and Pacmans,'' Seitz said. The technology is an 8086 microprocessor capable of doing 1/20th of a million operations a second with 1/8th of a megabyte of primary storage. Sixty-four of them together will do 3 million operations a second with 8 megabytes of storage.

Currently under development is a single chip that will replace each of the 64 8-inch-by-14-inch boards. When the chip is ready, Seitz and Fox say they will be able to string together 10,000 or even 100,000 of them.

Computer scientists have known how to make such a computer for years but have thought it too pedestrian to bother with.

``It could have been done many years ago,'' said Jack B. Dennis, a computer scientist at the Massachusetts Institute of Technology who is working on a more radical and ambitious approach to parallel processing than Seitz and Fox. He thinks his approach, called ``dataflow,''  will both speed up computers and expand their horizons, particularly in the direction of artificial intelligence .

Computer scientists dream of getting parallel processors to mimic the human brain , which can also do things concurrently.

``There's nothing particularly difficult about putting together 64 of these processors,'' he said. ``But many people don't see that sort of machine as on the path to a profitable result.''

What's more, Dennis says, organizing these machines and writing programs for them have turned out to be sticky problems that have resisted solution and divided the experts.

``There is considerable debate as to exactly how these large parallel machines should be programmed,'' Dennis said by telephone from Cambridge, Mass. ``The 64-processor machine (at Caltech) is, in terms of cost-performance, far superior to what exists in a Cray 1 or a Cyber 205 or whatever. The problem is in the programming.''

Fox responds that he has ``an existence proof'' for his machine and its programs, which is more than Dennis and his colleagues have to show for their efforts.

The Caltech device is a real, working computer, up and running and chewing on a real problem in high-energy physics. The ideas on which it was built may have been around for a while, he agreed, but the Caltech experiment demonstrates that there is something to be gained by implementing them.

For all his hopes, Dennis and his colleagues have not yet built a machine to their specifications. Others who have built parallel computers have done so on a more modest scale than Caltech's 64 processors. A spokesman for IBM said that the giant computer company had built a 16-processor machine, and is continuing to explore parallel processing.

The key insight that made the development of the Caltech computer possible, Fox said, was that many problems in science are computationally difficult because they are big, not because they are necessarily complex.

Because these problems are so large, they can profitably be divided into 64 parts. Each of the processors in the Caltech machine works on 1/64th of the problem.

Scientists studying the evolution of the universe have to deal with 1 million galaxies. Scientists studying aerodynamics  get information from thousands of data points in three dimensions.

To hunt for undersea oil, ships tow instruments through the oceans, gathering data in three dimensions that is then analyzed in two dimensions because of computer limitations. The Caltech computer would permit three-dimensional analysis.

``It has to be problems with a lot of concurrency in them,'' Seitz said. That is, the problem has to be split into parts, and all the parts have to be analyzed simultaneously.

So the applications of the Caltech computer for commercial uses such as an airline reservation system would be limited, its inventors agree.

Figure 4.1: Caltech Scientists Develop ``Parallel'' Computer Model [Dembart:84a]


Large-scale calculations in basic physics have been successfully run on the Cosmic Cube, an experimental computer at Caltech that its developers and users see as the forerunner of supercomputers of the future. The calculations, whose results are now being published in articles in scientific journals, show that such computers can deliver useful computing power at a far lower cost than today's machines.

The first of the calculations was reported in two articles in the June 25 issue of . In addition, a second set of calculations related to the first has been submitted to for publication.

The June articles were:

-``Pure Gauge SU(3) Lattice Theory on an Array of Computers,'' by Eugene Brooks, Geoffrey Fox, Steve Otto, Paul Stolorz, William Athas, Erik DeBenedictis, Reese Faucette, and Charles Seitz, all of Caltech; and John Stack of the University of Illinois at Urbana-Champaign, and

-``The SU(3) Heavy Quark Potential with High Statistics,'' by Steve Otto and John Stack.

The Cosmic Cube consists of 64 computer elements, called nodes, that operate on parts of a problem concurrently. In contrast, most computers today are so-called von Neumann machines, consisting of a single processor that operates on a problem sequentially, making calculations serially.

The calculation reported in the June took 2,500 hours of the computation time on the Cosmic Cube. The calculation represents a contribution to the test of a set of theories called the Quantum Field Theories, which are mathematical attempts to explain the physical properties of subatomic particles known as hadrons, which include protons and neutrons.

These basic theories represent in a series of equations the behavior of quarks, the basic constituents of hadrons. Although theorists believe these equations to be valid, they have never been directly tested by comparing their predictions with the known properties of subatomic particles as observed in experiments with particle accelerators.

The calculations to be published in probe the properties, such as mass, of the glueballs that are predicted by theory.

``The calculations we are reporting are not earth-shaking,'' said Dr. Fox. ``While they are the best of their type yet done, they represent but a steppingstone to better calculations of this type.'' According to Dr. Fox, the scientists calculated the force that exists between two quarks. This force is carried by gluons, the particles that are theorized to carry the strong force between quarks. The aim of the calculation was to determine how the attractive force between quarks varies with distance. Their results showed that the potential depends linearly on distance.

``These results indicate that it would take an infinite amount of energy to separate two quarks, which shows why free quarks are not seen in nature,'' said Dr. Fox. ``These findings represent a verification of what most people expected.''

The Cosmic Cube has about one-tenth the power of the most widely used supercomputer, the Cray-1,  but at one hundredth the cost, about $80,000. It has about eight times the computing power of the widely used minicomputer, the VAX 11/780. Physically, the machine occupies about six cubic feet, making it fit on the average desk, and uses 700 watts of power.

Each of the 64 nodes of the Cosmic Cube has approximately the same power as a typical microcomputer, consisting of 16-bit Intel 8086 and 8087 processors, with 136K bytes of memory storage. For comparison, the IBM Personal Computer uses the same family of chips and typically possesses a similar amount of memory. Each of the Cosmic Cube nodes executes programs concurrently, and each can send messages to six other nodes in a communication network based on a six-dimensional cube, or hypercube. The chips for the Cosmic Cube were donated by Intel Corporation, and Digital Equipment Corporation contributed supporting computer hardware. According to Dr. Fox, a full-scale extension of the Quantum Field Theories to yield the properties of hadrons would require a computer 1,000 times more powerful than the Cosmic Cube-or 100 computer projects at Caltech are developing hardware and software for such advanced machines.

Figure 4.2: Caltech's Cosmic Cube Performing Mammoth Calculations [Meredith:84a]

It is not surprising that our first hypercube calculations in CP did not need the full MIMD structure of the machine. This was also a characteristic of Sandia's pioneering use of the 1024-node nCUBE-[Gustafson:88a]. Synchronous applications like QCD are computationally important and have a simplicity that made them the natural starting point for our project.

next up previous contents index
Next: 4.2 Synchronous Applications Up: 4 Synchronous Applications I Previous: 4 Synchronous Applications I

Guy Robinson
Wed Mar 1 10:19:35 EST 1995