Xref: utzoo sci.math.num-analysis:585 sci.math:10141 comp.graphics:10206 comp.theory:411 Path: utzoo!utgpu!jarvis.csri.toronto.edu!rutgers!cs.utexas.edu!swrinde!zaphod.mps.ohio-state.edu!uakari.primate.wisc.edu!aplcen!haven!adm!smoke!gwyn From: gwyn@smoke.BRL.MIL (Doug Gwyn) Newsgroups: sci.math.num-analysis,sci.math,comp.graphics,comp.terminals.tty5620,comp.theory Subject: Re: How much precision does Mandelbrot need Message-ID: <12282@smoke.BRL.MIL> Date: 4 Mar 90 00:40:13 GMT References: <8602@cbnewsh.ATT.COM> Reply-To: gwyn@brl.arpa (Doug Gwyn) Followup-To: sci.math.num-analysis Organization: Ballistic Research Lab (BRL), APG, MD. Lines: 19 In article <8602@cbnewsh.ATT.COM> wcs@cbnewsh.ATT.COM (Bill Stewart 201-949-0705 erebus.att.com!wcs) writes: >How much precision does it take to calculate Mandelbrot sets correctly? That depends on the algorithm and on the resolution. With the most straightforward method, over thousands of iterations, I get the right results even at fairly high enlargements using normal double-precision floating-point hardware. If you think about the way that rounding errors would accumulate, that's not too surprising. >Since Mandelbrot sets depend very strongly on initial conditions, >it would seem that loss of precision would quasi-randomly cause >different results near any boundaries. It doesn't have a noticeable effect on the images, though. I would think that the software floating-point emulation of the 630 CCS would suffice. While I'm a fan of scaled fixed-point for such systems, I haven't tried applying that to Mandelbrot image generation. It would probably work, though.