Path: utzoo!utgpu!news-server.csri.toronto.edu!cs.utexas.edu!wuarchive!zaphod.mps.ohio-state.edu!rpi!leah!bingvaxu!kym From: kym@bingvaxu.cc.binghamton.edu (R. Kym Horsell) Newsgroups: comp.arch Subject: Re: benchmark for evaluating extended precision (data, long) Keywords: extended precision,multiply,benchmark,arithmetic Message-ID: <4004@bingvaxu.cc.binghamton.edu> Date: 13 Sep 90 18:38:10 GMT References: <2114@charon.cwi.nl> <119983@linus.mitre.org> <3999@bingvaxu.cc.binghamton.edu> <120002@linus.mitre.org> Reply-To: kym@bingvaxu.cc.binghamton.edu.cc.binghamton.edu (R. Kym Horsell) Organization: SUNY Binghamton, NY Lines: 19 In article <120002@linus.mitre.org> bs@linus.mitre.org (Robert D. Silverman) writes: [distinction of theoretical complexity of division algorithm as opposed to complexity of particular algorithm]. >I'm talking about PRACTICAL algorithms here, not theoretical ones. >There doesn't seem to be a recursive bisection algorithm similar to >Karatsuba's that works for division. Methods based on FFT's are >ineffective until one reaches thousands of bits. For numbers in the >(say) 200 decimal digit range, ordinary long division is best, and >that algorithm is O(n^2). So long as you make the distinction between problem complexity, algorithm complexity & the complexity of algorithms that you use. Such niceties are sometimes lost on some of us who read this group. I will check out your claim re _practicality_ of FFT algorithms and will report results to the net; they may be of use to people to those concened about implementation issues. -Kym Horsell