Path: utzoo!utgpu!news-server.csri.toronto.edu!rpi!zaphod.mps.ohio-state.edu!mips!spool.mu.edu!munnari.oz.au!bunyip.cc.uq.oz.au!marlin.jcu.edu.au!csrdh From: csrdh@marlin.jcu.edu.au (Rowan Hughes) Newsgroups: comp.arch Subject: Re: massive linpack Message-ID: <1991Jun8.055711.13457@marlin.jcu.edu.au> Date: 8 Jun 91 05:57:11 GMT References: <9106070135.AA02947@ucbvax.Berkeley.EDU> Organization: James Cook University Lines: 37 In <9106070135.AA02947@ucbvax.Berkeley.EDU> jbs@WATSON.IBM.COM writes: > Richard Lethin asks: >At what size N for massive linpack does the accumulated numerical fuzz >swamp the precision available in a double precision number? > Very large. Typical relative error (in the vector norm sense) >in the solution is n*c*e, where n is matrix size, c is condition number >and e is machine epsilon (2**-52 for IEEE double). Therefore if you >want a solution accurate to 1 part in 1000 (10 bits) and your matrix >has condition number less than 1000 (10 bits) your n can be 2**30 or I would have thought (N**2)*C*E was more appropriate. > Richard Lethin asks: >Aren't really large problems of interest sparse matrices anyway? Who >holds the record for massive sparse matrix solves? Yes, large problems (N > 10,000) are typically sparse, and with strong diagonal banding. These can only be solved with iterative methods, and only on vector, or large parallel machines. Iterative methods usually have no sensitivity to round-off errors since the original matrix is used continuously in the solution. Successive Over Relaxation was the most commonly used method until a few years ago (SOR). It had some very severe restrictions on the types of matrix problems it could solve; the diagonal dominance condition. Biconjugate gradient methods, using Chebychev orthogonalilization, are now the rage. They're iterative, but round-off errors can eventually destroy the solution. The largest problem I've seen solved is for N=100,000. Bico does'nt have such a severe restriction regarding diagonal dominance. Bico is well suited to vector architectures; thats what it was designed for. It can also work quite well on parallel machines. -- Rowan Hughes James Cook University Marine Modelling Unit Townsville, Australia. Dept. Civil and Systems Engineering csrdh@marlin.jcu.edu.au