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From: ehj@mordor.ARPA (Eric H Jensen)
Newsgroups: net.arch
Subject: Re: Floating point performance
Message-ID: <16112@mordor.ARPA>
Date: Fri, 17-Oct-86 15:13:32 EDT
Article-I.D.: mordor.16112
Posted: Fri Oct 17 15:13:32 1986
Date-Received: Sat, 18-Oct-86 00:02:43 EDT
References: <340@euroies.UUCP> <1989@videovax.UUCP> <722@mips.UUCP> <725@mips.UUCP> <6028@ut-sally.UUCP>
Reply-To: ehj@mordor.UUCP (Eric H Jensen)
Organization: S-1 Project, LLNL
Lines: 29

In article <6028@ut-sally.UUCP> nather@ut-sally.UUCP (Ed Nather) writes:
>more complex (and slower) using standard hardware.  Also, the aphorism
>about using a lot of floating operations was brought home to me:
>"Using floating point is like moving piles of sand around.  Every time
>you move one you lose a little sand, and pick up a little dirt."

I thought numerical analysis was the plastic sheet you place your sand
on - with some thought (algorithm changes) you can control your
errors most of the time or at least understand them.  Then of course
there is always an Extended format ...

>Has hardware technology progressed to the point where we might want to
>consider making a VERY LARGE integer machine -- with integers long
>...
>scaling, Planck's constant.  It would allow rapid integer operations
>in place of floating point operations.  If you could add two 512-bit
>integers in a couple of clock cycles, it should be pretty fast.

I would not want to be the one to place and route the carry-lookahead
logic for a VERY fast 512 bit adder (you could avoid this by using the
tidbits approach but that has many other implications).  The real
killers would be multiply and divide.  If you really want large
integers use an efficient bignum package; hardware can help by
providing traps or micro-code support for overflow conditions.

-- 
eric h. jensen        (S1 Project @ Lawrence Livermore National Laboratory)
Phone: (415) 423-0229 USMail: LLNL, P.O. Box 5503, L-276, Livermore, Ca., 94550
ARPA:  ehj@angband    UUCP:   ...!decvax!decwrl!mordor!angband!ehj