Affiliations: Dpto. Estadística, I.O. y Computación,
Universidad de La Laguna, La Laguna, 38271, Spain. Tel.: +34 922 318187; Fax:
+34 922 318170; E-mail: [email protected] | Universidad Nacional de San Luis, Ejército de los
Andes 950, San Luis, Argentina. E-mail: [email protected]
Note: [] Corresponding author
Abstract: Current performance prediction analytical models try to characterize
the performance behavior of actual machines through a small set of parameters.
In practice, substantial deviations are observed. These differences are due to
factors as memory hierarchies or network latency. A natural approach is to
associate a different proportionality constant with each basic block, and
analogously, to associate different latencies and bandwidths with each
"communication block". Unfortunately, to use this approach implies that the
evaluation of parameters must be done for each algorithm. This is a heavy task,
implying experiment design, timing, statistics, pattern recognition and
multi-parameter fitting algorithms. Software support is required. We present a
compiler that takes as source a C program annotated with complexity formulas
and produces as output an instrumented code. The trace files obtained from the
execution of the resulting code are analyzed with an interactive interpreter,
giving us, among other information, the values of those parameters.
