🚀 go-pugleaf

In article <490@ctycal.UUCP> ingoldsb@ctycal.UUCP (Terry Ingoldsby) writes:
>
>Note that I'm not saying to give up on parallel processing; on the contrary
>I believe that it is the only way to do certain activities.  I am saying
>that the notion of a general purpose massively parallel architecture that
>efficiently executes all kinds of algorithms is probably a naive and
>simplistic view of the world.

Depends on how you classify "all" algorithms. Nary a machine ever made
is good at every algorithm ever invented.

I suspect fine-grain SIMD machines are the way to go for a broader
class of algorithms than we currently suspect. Cellular automata,
fluid flow, computer vision, certain types of image processing and
computer graphics have all shown themselves to be amenable to running
on a Connection Machine. I'm sure the list will continue to grow. In
fact Dow Jones himself now owns two; anybody know what he's doing with
them?

Peak performance for a CM-2, fully decked out, is on the order of 10
Gflops. This is with 64K 1-bit processors and 2K Weitek FP chips. The
individual processors are actually pretty slow, 10-100Kips, I think.
Imagine what this baby'd be like if they were actually fast! Their
Datavault only has something like 30MB/sec transfer rate, which seems
pretty poor for that many disks with that much potential bandwidth.

Rumors of a CM-3 abound. More memory (1 Mbit/processor?), more
processors (I think the addressing for processors is already in the
neighborhood of 32 bits), more independent actions perhaps going as
far as local loops, etc.

I was told by a guy from Thinking Machines that they get two basic
questions when describing the machine:

1) Why so many processors?

2) Why so few processors?

Answering the second one is easy: It was the most they could manage.
Answering the first one is harder, because the people who ask tend not
to grasp the concept at all.

What do I think? I think the next ten years are going to be very
interesting!

		--Rod