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language-specific keyboard layouts have been adopted that allow for the relative
frequency of letter use in the different alphabets.
Input problems are compounded in languages that print from right to left, such
as Arabic and Hebrew. When the default input mode is Arabic, some computers re-
quire that English characters be input in reverse order. Becker describes a different
method in which the keyboard is temporarily reconfigured for each alphabet, so the
characters are accepted in the conventional mode for each language. A prompt
window on the display indicates the current keyboard configuration. The concept of a
language-independent keyboard is an important contribution to multilingual
processing.
Input of Oriental languages poses even more difficult problems. The use of
logo-graphic, rather than alphabetic, characters to represent words stems from ancient
Chinese writing, which was also adopted by the Japanese and Koreans around 1,000
years ago. These symbols are effective in permitting communication between cultures
that speak different dialects, but the large number of characters and their different
pronunciations in each language create serious input difficulties.
The problem of providing a simple, efficient input method in a multilingual
environment remains complex. Multiple input devices, including voice as well as
key-boards, could be one solution. More research in this area is sorely needed.
TEXT 3
THE DO-I T-YOURSELF S UPERCOMPUTER
In the well-known stone soup fable, a wandering soldier stops at a poor village
and says he will make soup by boiling a cauldron of water containing only a shiny
stone. The townspeople are skeptical at first but soon bring small offerings: a head of
cabbage, a bunch of carrots, a bit of beef. In the end, the cauldron is filled with
enough hearty soup to feed everyone. The moral: cooperation can produce significant
achievements, even from meager, seemingly insignificant contributions.
Researchers are now using a similar cooperative strategy to build
supercomputers, the powerful machines that can perform billions of calculations in a
second. Most conventional supercomputers employ parallel processing: they contain
arrays of ultrafast microprocessors that work in tandem to solve complex problems
such as forecasting the weather or simulating a nuclear explosion. Made by IBM,
Cray and other computer vendors, the machines typically cost tens of millions of
dollars–far too much for a research team with a modest budget. So over the past few
years, scientists at national laboratories and universities have learned how to
construct their own supercomputers by linking inexpensive PCs and writing software
that allows these ordinary computers to tackle extraordinary problems.
In 1996 two of us (Hargrove and Hoffman) encountered such a problem in our
work at Oak Ridge National Laboratory (ORNL) in Tennessee. We were trying to
draw a national map of ecoregions, which are defined by environmental conditions:
all areas with the same climate, landforms and soil characteristics fall into the same
ecoregion. To create a high-resolution map of the continental U.S., we divided the
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