

Extreme Scale Computing - dlnovell
http://blog.irvingwb.com/blog/2010/02/extreme-scale-computing.html#

======
vyrotek
A lot of random thoughts came to mind when the author referenced mainframes.

My father and I argue/discuss this sort of thing often. Mainly because we're
from two different worlds. He comes from a Mainframe (z/TPF) background and
usually laughs at what we think is high-performance or a heavy load on our web
servers. (He also likes to ask when I'm going to learn a real programming
language like assembler.)

Just last night I was asking him why web companies don't run companies of just
one of these juggernauts mainframes. The price of the hardware seems to be the
biggest hurdle. But there's also the fact that if you want 'feature x' with
how you store data... well you write it yourself so that it runs as fast as
possible. You won't find VISA running distributed MySQL instances anytime
soon. The mainframe mindset seems to be that you build the system EXACTLY how
you need it. No More, No Less! The way I think of it is like Lego blocks.

Today we take a companies like Twitter who think "We have a lot of different
kinds of blocks, how can we make them fit together and do what we need."

Mainframe developers think "We need to handle tens of thousands of
transactions per second doing X. So lets make our own blocks that fit together
perfectly and do exactly that."

This means you end up having to re-invent a lot of things. But you re-invent
exactly what you need and leave out the rest. I wonder if the future is in a
hybrid of these two types of systems. Perhaps we need to put Mainframes in the
Cloud and let people purchase time on them like Windows Azure & AWS. I would
certainly like to play with that kind of horsepower. Or perhaps the future is
in something that doesn't exist yet which the author seems to suggest.

~~~
jared314
What you are suggesting was called Time-sharing (1960s).
<http://en.wikipedia.org/wiki/Time-sharing>

------
drallison
Supercomputing is a moving target. Irving Wladawsky-Berger has given a nice
summary of how supercomputers are scaling (we are beginning to see petaflop
machines) and what the challenges for the scale up to exascale computing will
be and the significant changes to predictive modeling that they will enable.

In case you have not noticed, supercomputing (at least at the teraflop level)
has become mainstream. We are beginning to see monolithic supercomputers, that
is, machines primarily dedicated to a particular application or sub-
application, in a variety of production situations. Often these monolithic
supercomputers are constructed of standard commodity servers; some use
hardware accelerators to substantially improve throughput or real time
performance by exploiting unrealized parallelism. Specialization by an
accelerator can improve throughput by significant factors, often an order of
magnitude or two.

