Where’s the Real Bottleneck in Scientific Computing?

WHEN I FIRST started doing computational science in 1986, a new generation of fast, cheap chips had just ushered in the airrent era of low-cost supercomputers, in which multiple processors work in parallel on a single problem. Suddenly, it seemed as thougli e\'eryone who ttx)k number cmnching seriously was rewriting his or her software to take advantage of these new machines. Sure, it hurt—the compilers that translated programs to iTin on parallel computers were flaky, debugging tools were nonexistent, and thinking