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The following TR is available via anonymous ftp from cs.rochester.edu 
in pub/systems_papers/92.TR420_interaction_architecture_parallel.ps.Z
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        Shared-Memory Multiprocessor Trends
        and the Implications for Parallel Program Performance

        by Evangelos P. Markatos and Thomas J. LeBlanc 

                        Abstract 
The last decade has produced enormous improvements in 
processor speeds without a corresponding improvement in
bus or interconnection network speeds.
As a result, the relative costs of communication and computation
in shared-memory multiprocessors have changed dramatically.
An important consequence of this trend is that many parallel applications,
which depend on a delicate balance between the cost of communication
and computation, do not execute efficiently on today's shared-memory
multiprocessors.

In this paper we quantify the effect of this trend
in multiprocessor architecture on parallel program performance.
Our experiments on bus-based,
cache-coherent machines like the Sequent Symmetry,
and large-scale distributed-memory machines like the BBN Butterfly,
demonstrate that applications scale much better on previous-generation 
machines than on current machines.
In addition, we show that some scalable machines support
fine-grain, shared-memory programs better than some bus-based,
cache-coherent machines, without significantly greater programming effort.
>From our experiments
we conclude that communication has become a
dominant source of inefficiency in shared-memory multiprocessors,
with serious consequences for system software involved in
scheduling and decomposition decisions.
In particular, we argue that
shared-memory programming models that could be implemented efficiently
on the machines of yesterday
do not readily port to state-of-the-art machines,
and that current software trends in support of fine-grain
parallel programming are at odds with hardware trends.
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thank you, 
Evangelos Markatos 
markatos@cs.rochester.edu