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From: dik@cwi.nl (Dik T. Winter)
Newsgroups: comp.arch
Subject: Re: Anything wrong with the i860
Message-ID: <3486@charon.cwi.nl>
Date: 7 May 91 23:56:13 GMT
References: <1991May7.145407.18417@midway.uchicago.edu>
Sender: news@cwi.nl
Organization: CWI, Amsterdam
Lines: 31

In article <1991May7.145407.18417@midway.uchicago.edu> rtp1@quads.uchicago.edu (raymond thomas pierrehumbert) writes:
 > I have seen relatively little about the i860 chip on this newsgroup.
 > Also, compared to MIPS, it doesn't seem to be very popular as the
 > base processor for computers;  Alliant uses it in their shared-memory
 > machines (800 & 2800), Intel has the Touchstone experimental mpp machine,
 > and the i860 seems popular as a graphics coprocessor (e.g. in the NeXt),
 > but generally, I see surprisingly little interest in the chip.
FPS and Stardent (will) use it as computational coprocessor (I think).
 > 
 > Is there something wrong with the architecture?  As a platform,
 > what are its advantages and disadvantages over the competition?
 > I am particularly interested in this, as I am thinking of buying
 > an Alliant F/800; I did a lot of benchmarks, and the performance
 > seems extremely good compared to other RISC architectures (even
 > on a per-processor basis running on throughput rather than
 > parallelization), so I'm wondering if there isn't some "catch"
 > I haven't encountered yet.
The problem I see with the i860 is that it is very good with especially tuned
code, but that it is extremely bothersome for compilers to get that performance.
(This holds for f-p only, if you are thinking non-f-p it can compete with the
others.)  My opinion is that you would want the i860 only if your f-p work-load
consist mainly of the use of standard libraries.  Do not expect such a good
performance if you code everything yourself.  So for chemical/physical research
it is quite good (if you use the standard libraries), but when you are doing
research in numerical mathematics it is less well suited.  On the other hand
Alliants model for parallellism is very good to do basic research in
parallel algorithms (in that case performance is not the main problem; we are
still on an FX/4; talking about performance :-)).
--
dik t. winter, cwi, amsterdam, nederland
dik@cwi.nl