moses@NADC.NADC.NAVY.MIL (Bill Moses) (02/27/91)
Luigi Rizzo (lr@cs.brown.edu) writes: > TRAM modules are kind of a toy: you buy one (or an evaluation > kit) and don't care too much about the price; then your > interest disappears... > ...those who are really interested in massive use of Transputer, > and do care about their [company|school]'s money, sure they > build their own modules... Jeff Carroll (carroll@ssc-vax.boeing.com) writes: > I think there are two kinds of people who use transputers. > One is the computer scientist who is doing research on parallel > systems, and the other is the scientist or engineer whose > number-crunching application takes too long to run on his PC. > ...the needs of either are likely to be met with a relatively small > transputer network (about the size that will fit into the spare > slots in the user's PC). This brings up a simple question: Who wants massively parallel machines anyhow? Computer Scientists and Engineers experiment with and develop systems - what are they used for? I'm all for research for its own sake, but there are actually people out there who want to apply it. I suppose the questions are more along these lines: What are the foreseen uses of large parallel machines? Is this in line with current research? What should they be used for (besides weather prediction, Mandelbrot sets, etc.)? Just wondering Bill <Moses@NADC.NAVY.MIL>
rbe@yrloc.ipsa.reuter.COM (Robert Bernecky) (03/01/91)
The question was: "who wants massive parallelism anyway..."? Answer: Anybody with a large problem to solve or a problem to solve quickly which can be mapped onto such an architecture. For example: Dow Jones wants to supply a service to their tens of thousands of customers, to let them search, for example, the New York Times articles for the past 10 years, for all occurences of "not a crook" and "national security" within the same paragraph. The Connection Machine(with a piddly 64k processors) does a fairly bangup job of this. I suspect the human genome problem is another candidate for massively parallel processing. The key to making MPP work lies in NOT having to program for it explicitly. That is where languages such as J should be helpful -- reflect the way we think, rather than the way computers are built. When I was Director of Research at I.P. Sharp (bought out by Reuters, arch-enemy \\\\\competitor\\\\\\\\\\honorable opponent of Dow Jones), I proposed we get an CM2 to look at such applications. This was refused by the forward-thinking management of Reuters, who were happily exploring ideas such as mediocrely parallel systems, and farms of sun workstations. I think both ideas, and the people who were pushing them, are no longer at Reuters either. Food for thought... Bob Bernecky Snake Island Research Inc. ps: I'm not there any more either.
frost@watop.nosc.mil (Richard Frost) (03/04/91)
Jeff Carroll (carroll@ssc-vax.boeing.com) writes: > I think there are two kinds of people who use transputers. > One is the computer scientist who is doing research on parallel > systems, and the other is the scientist or engineer whose > number-crunching application takes too long to run on his PC. Some of use want them because our number-crunching applications take too long on a Cray YMP or its simply more cost effective to use a large transputer network for an inherently parallel application. (Never mind that a 25-33MHz PC or Mac outperforms a VAX ;-) moses@NADC.NADC.NAVY.MIL (Bill Moses) writes: >Who wants massively parallel machines anyhow? >What are the foreseen uses of large parallel machines? Digital signal processing: Specifically at my site--a proposed application is the identification of dim incoming hostile targets (e.g. Exocet missles). Another application was proposed at CERN to detect weak particle signatures. Some image-processing applications are better suited for transputers or MIMD in general. Real-time non-linear controls for many dynamic systems including municipal traffic control are possible with parallel machines. Numerical Analysis: The folks at Los Alamos and elsewhere have been busy re-writing the book for parallel architectures. Check recent SIAM proceedings. Symbolic Analysis: The nth order hyper-foobar expansion of f(x,y,z). Soliton or wavelet solutions to the general case of Maxwell's equations => goodby to ray-tracing. Combinitorics/Graph Theory: Transportation and Network optimization, and of course the TSP. Others will undoubtably contribute more ... -- (Note: please e-mail directly as the mail header "From:" line is broken) Richard Frost Naval Ocean Systems Center frost@watop.nosc.mil voice: 619-553-6960
hht@filbert.sarnoff.com (Herbert H. Taylor x2733) (03/06/91)
** This brings up a simple question: Who wants massively parallel ** machines anyhow? Computer Scientists and Engineers experiment ** with and develop systems - what are they used for? I'm all ** for research for its own sake, but there are actually people ** out there who want to apply it. I suppose the questions are more ** along these lines: What are the foreseen uses of large parallel ** machines? Is this in line with current research? What should ** they be used for (besides weather prediction, Mandelbrot sets, etc.)? We have developed a massively parallel, Video Supercomputer a.k.a. the Princeton Engine. This is a SIMD machine with 2048 16bit custom DSP chips. It was originally intended for HDTV research but has since found a diverse number of applications including image pyramid processing, multispectral analysis, SAR, histogram equalization, Data compression algorithms, neural nets, terrain rendering, medical imaging, volume visualization, ultrasound processing, teleoperation and, oh, even mandlebrot sets.... All these applications run in continuous real-time. For example, we simulate in continuous real-time HDTV system proposals. HDTV simulations on conventional computing platforms, for example, high-end mainframes take 10 to 20 hours to compute ONE second of video - while on the Princeton Engine this is continuous real-time - we watch "television" on the computer. For a conventional mainframe to assemble even a "few seconds" of a single simulation of important design ideas (perhaps to show your boss) it might take weeks to compose, simulate and evaluate. On a system such as the Princeton Engine - the process is real-time. In fact, the kind of interaction one can have with the creative design process when the response of the computer is instant is extraordinary - and is difficult to describe without sounding unbelievable. It is even different then the interaction one can have with other very fast computers - even a supercomputer. The Princeton Engine was originally developed when DSRC was RCA Labs. One system has been here at DSRC in Princeton and one in Indianapolis Ind. for almost three years. This spring we are placing another system at NIST in Maryland under DARPA sponsorship. The NIST system will be used primarily by DARPA HDTV program participants. Many of the important conceptual ideas embodied in the recent DARPA BAA for High Definition systems will require massive parallel systems to fully explore the underlying ideas. DARPA's interest lies in, "high resolution systems for applications in command and control, battle management, training and simulation, intelligence analysis, weapons systems..." If one examines the processing requirements to accomplish several of the ares embodied in the BAA it is evident that a significant measure of parallism will be required. The technical areas of the BAA include displays, processors, etc. These are fundamentally the areas where the Princeton Engine has found great applicability. H Taylor.