At 10:39 AM 3/14/2007, Joe Landman wrote:
Robert G. Brown wrote:
So I'm not holding my breath on ML running out this week or next. I'm
more interested in speculating on when the next massive superML jump on
TOP of ML will occur, when the next phase/paradigm shift is due that
Ah....
Ok, my concern is that silicon may be running out of room. Now if
we all just put on our happy faces, and use GaAs, we can go much
faster. Yeah, it has some issues ...
Like
1) yield
2) wafer size
3) power consumption
4) maximum density
Note that what's available in GaAs tends to be things like RF
amplifiers, 4 bit counters, etc. I don't know that there's any LSI
GaAs (what they call LSI in the GaAs world is things like
operational amplifiers with (gasp) dozens of transistors.. which is a
very high level of integration compared to one or two transistors in
the usual RF amplifier.
There have been some experimental GaAs switches (like crossbars) For
instance, a google turns up the work of Yamada, et al., in 1999 with
a 8x8 ATM switch using 0.5 micron gate GaAs clocking at 1.3 GHz.
dissipating only a few tens of watts.
But... you CAN run it at a junction temperature of 200C. GaN can run
even hotter.
You're much better off pushing the CMOS processes (where they have
fT's up in the 10s of GHz)
SiGe might be more attractive.. decent density, lower power
consumption, ability to integrate CMOS structures, etc.
But think of how much faster we can be. (that and my thesis work
might suddenly have applicability, but that is another matter).
More seriously, our computing industry can build silicon really
well. As it keeps shrinking problems arise. Some of these problems
can be ameliorated by doing a material paradigm shift. But our
computing industry does silicon really well ...
Really, really well...
Folks have been struggling with GaAs, GaN, InP, etc for a long time.
Joe
--
Joseph Landman, Ph.D
Founder and CEO
Scalable Informatics LLC,
email: [EMAIL PROTECTED]
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cell : +1 734 612 4615
James Lux, P.E.
Spacecraft Radio Frequency Subsystems Group
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