Path: utzoo!attcan!uunet!snorkelwacker!usc!wuarchive!udel!nigel.ee.udel.edu!mccalpin From: mccalpin@perelandra.cms.udel.edu (John D. McCalpin) Newsgroups: comp.arch Subject: Re: LINPACK 1000x1000 MFLOPS per $$$ Message-ID: Date: 20 Jul 90 14:24:28 GMT References: <2349@crdos1.crd.ge.COM> Sender: usenet@ee.udel.EDU Organization: College of Marine Studies, U. Del. Lines: 105 In-reply-to: davidsen@crdos1.crd.ge.COM's message of 20 Jul 90 12:02:03 GMT In article <> mccalpin@pereland.cms.udel.edu I wrote about MFLOPS/$: >| (2) The $13,000 configuration includes no monitor or graphics adapter, >| etc. It is strictly a server, configured with 16 MB RAM and 120 MB >| disk. NFS is used to store results directly onto my graphics >| workstation. In article <> davidsen@crdos1.crd.ge.COM (Wm E Davidsen Jr) replies: > You have defined the solution by picking the dataset... You are > talking about a tiny problem here, not at all typical of what is run on > a Cray. Certainly there are problems requiring lots of CPU and tiny > memory, and it's nice that you have one. Workstations are good at that. > We run dedicated troff servers here, and they're workstations, too. The configuration that I quoted has a rather small memory by current supercomputer standards, but 2 MW (64-bit) is hardly "tiny". As soon as 3rd-party vendors start delivering memory boards at competitive prices, the machine will be upgradable to 4 MW (64-bit) for about $2000. Since the machine was designed to accept 4 Mbit technology, it is possible to configure it with up to 16 MW of memory. I expect that it will be a few months before IBM releases any boards based on 4 Mbit chips, and then a few more months before clones are available from 3rd parties. Estimated cost for a full 128 MB = 16 MW is about $20,000 in addition to the base price of $8700 for the machine. Since Cray is still selling lots of Y/MP's with 32 MW memories, it is hardly fair to criticize a single-user workstation on that account. As far as disk storage goes, I have 1.5 GB of disk space on my graphics workstation, and will soon have a 2.3 GB tape drive. So manipulating 500 MB datasets (see below) is entirely practical. The whole setup: Silicon Graphics 4D/25TG 1.5 GB disk (2x760MB) 2.3 GB tape 32 MB RAM 150 MB tape IBM 320 server 16 MB RAM 120 MB disk is under $50,000 at University prices. > If you define the dataset to be typical Cray size, say 500MB, the > workstation becomes impractical. And if you assume non-vectorable very > large problems the Cray2 has the edge in scalar speed. How did you decide that 500 MB was a "typical" Cray dataset? There is such a large variety of jobs that are run on Crays that defining a "typical" job seems counter-productive. There are *many* important problems which are cpu-intensive that can fit comfortably into machines with 2, 4, 8, or 16 MW of memory. After all, Cray has only been shipping X and Y machines with more than 8 MW of memory for about 2 years now. Concerning the Cray-2 --- if the job *absolutely requires* at least 256 MW of real memory, then there are not many options (though I believe that the Convex C-240 can be configured with 256 MW at considerably less cost). On the other hand, it might be more cost-effective in the longer term to spend the programmer salary required to port the application to run out-of-core on a much cheaper machine. > This is a lot like saying that you want to haul a bag of groceries at > 100mph, and therefore sports cars are killing trucks. You have a sports > car problem here, and your solution is cost effective. So? We still need > trucks. I said precisely the same thing at the end of my original posting. However, I disagree that memory size is the primary dividing line between jobs which require supercomputers and those which do not. The IBM 320 that I described only has 2 memory board slots. The server configurations have more slots and can be configured with up to 512 MB = 64 MW of RAM (depending on the model) using 4 Mbit technology. Since most 8-cpu Y/MP's are shipping with memories of this same size, it hardly seems like a clear distinction. As other people have pointed out, the choice of a computational platform is a multivariate constrained optimization problem. Some of the constraints are: (1) The cost must be within the available budget. This includes the cost of porting the code as well. (2) The wall-clock turnaround must be within the limits of the research project. (3) Point (2) usually requires sufficient memory to make the problem core-containable. (4) Sufficient mass storage space and access speed must be available to save intermediate and permanent results without slowing down the calculation past the constraints of point (2). An anecdote: I recently submitted a proposal to the NSF to do some cpu-intensive studies of the equations governing a theoretical two-dimensional ocean. The calculations are estimated to require 200 hours of Cray Y/MP time. I don't consider this a trivial expenditure.... With an IBM 320, I would probably be able to finish all of the calculations before the proposal even completes the review process! > bill davidsen (davidsen@crdos1.crd.GE.COM -or- uunet!crdgw1!crdos1!davidsen) > "Stupidity, like virtue, is its own reward" -me -- John D. McCalpin mccalpin@perelandra.cms.udel.edu Assistant Professor mccalpin@vax1.udel.edu College of Marine Studies, U. Del. J.MCCALPIN/OMNET