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Message
From: markus at reaaliaika.net<markus@r...>
Date: Thu Jul 15 09:19:47 CEST 2004
Subject: [oc] Parallel Array Processor Project
> The Raw project is here:
> http://www.cag.lcs.mit.edu/raw/
OK, I read the available information of RAW, Transit, iRAM and those.
RAW is "regular" transputer -like architecture. The similarities between
these architectures and mine is the connection network (just ot
neighbors) and for the same reasons - this kind of network is highly
scalable compared to any central-controlled networks.
The difference between my project and these "transputer" -like
architectures are the cell design. Both transputer and MIT RAW use
quite regular CPUs as processing nodes. I'm trying to construct an
independent cell, which have:
- 1 instruction word memory (maybe 12 bits?)
- 1 x 8-bit write-only memory element
- N x 8-bit read-only memory (N = number of neighbors, possible values
might be 4, 6 or 8)
You might think, that my "macrocell" units bring the project closer to
transputers, but it's not entirely true. "Macrocells" are there just to
reduce transistor count by "simulating" the operation of multiple cells -
thus many logic circuits can be shared, altought the speed drops
because of sequential execution.
Because cells are basically (but not purely) DFMs (Data Flow Machines),
the "macrocells" are DFMs, too. I have already found DFM designs, but
they mostly concentrate for implementing a - could we say - large scale
DFM, with a pool of processors and common memory. Altought for these
differences between my "macrocells" and those DFMs, I was able to
refine my design using the information available on those.
For programmers point of view, there's no semantical difference, if the
processor hardware is constructed from single cells or macro-cells or
with a hybrid model (using both macrocells and single cells in various
combinations). It's possible to use even a heterogenous model, i.e. not
all cells are able to perform all instructions - or the instruction
completition time may vary. For example, single-cycle multiplication,
which takes a lots of space, could only be performed in one cell, while
others implement it with chained adding-and-shifting (taking several
cycles).
I also searched information about cellular automatas. I found something,
but most of these systems are not aimed to produce a computational
platform or to be used in physical world (only in computer simulations).
I'll keep my eyes open for these.
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