[Beowulf] [landman@scalableinformatics.com: Re: [Bioclusters] FPGA in bioinformatics clusters (again?)]
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Jim Lux James.P.Lux at jpl.nasa.govSat Jan 14 15:56:51 PST 2006
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At 08:52 AM 1/14/2006, Eugen Leitl wrote: <snip> >'t see attached processing >replacing clusters or HPC systems, Is. > >-- >Joseph Landman, Ph.D using masses of FPGAs is fundamentally different than uses masses of computers in a number of ways: 1) The FPGA is programmed at a lower conceptual level if you really want to get the benefit of performance. Sure, you can implement multiple PowerPC cores on a Xilinx, and even run off the shelf PPC software on them, however, it would be cheaper and faster to just get Power PCs. There's a world of difference between modifying someone's program in FORTRAN or C and modifying something in Verilog or VHDL. Fundamentally, the FPGA is a bunch of logic gates, and not a sequential VonNeumann computer with a single ALU. The usage model is different. 2) Most large FPGAs have very high bandwidth links available (RocketPortIO for Xilinx for instance), although, they're hardly a commodity generic thing with well defined high level methods of use (e.g. not like using sockets). You're hardly likely to rack and stack FPGAs. 3) Hardware failure probabilities are probably comparable between FPGAs and conventional CPUs. However, you're hardly likely to get the economies of scale for FPGAs. Megagate FPGAs are in the multikilobuck range: just for the chip. There isn't a well developed commodity mobo market for FPGAs, that you can just pick your FPGA, and choose from among a half dozen boards that are all essentially identical functionally. What "generic" FPGA boards exist are probably in the multikilobuck area as well. 4) There are applications for which FPGAs excel, but it's likely that a FPGA solution to that problem is going to be very tailored to that solution, and not particularly useful for other problems. The FPGA may be a perfectly generalized resource, but the system into which it is soldered is not likely to be so. Joe's analogy to video coprocessors is apt. Very specialized to a particular need, where they achieve spectacular performances, especially in a operations per dollar or operations per watt sense. However, they are very difficult to apply in a generalized way to a variety of problems. Of course, the video coprocessor is actually an ASIC, and is essentially hardwired for a particular (set) of algorithms. You don't see many video cards out there with an FPGA on them, for the reason that the price/performance would not be very attractive. (mind you, if you've got the resources, and a suitable small set of problems you're interested in, developing ASICs is the way to go. D.E.Shaw Research is doing just this for their computational chemistry problems.) 5) FPGA development tools are wretchedly expensive, compared to the tools for "software". It's a more tedious, difficult and expensive development process. There's a lot more software developers than FPGA designers out there, so it's harder to find someone to do your FPGA. It's not really a dollar issue (top pros in both are both in the $100K/yr salary range) it's finding someone who's interested in working on YOUR project. Sure, there are some basic "free-ish" tools out there for some FPGAs, but if you want to do the equivalent of programming in a high level language, you're going to be forking out $100K/yr in tools. Resynthesizing your FPGA design is often a lot slower than recompiling your program. Also, because it's basically a set of logic gates, there typically isn't the concept of recompiling just part and relinking. It's resynthesize EVERYTHING, and then you have to revalidate all the timings, regenerate test vectors, etc. There's no equivalent of "patching". James Lux, P.E. Spacecraft Radio Frequency Subsystems Group Flight Communications Systems Section Jet Propulsion Laboratory, Mail Stop 161-213 4800 Oak Grove Drive Pasadena CA 91109 tel: (818)354-2075 fax: (818)393-6875
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