Compilers for VLIW and superscalar machines increasingly use dynamic
application behavior or profiling information in optimizations such as
instruction scheduling, speculative code motion, and code
layout. Hence it is extremely useful to develop inexpensive techniques
that gather accurate profiling information. This paper presents novel
edge profiling techniques that greatly reduce run-time overhead by
efficiently exploiting instruction level parallelism between
application and instrumentation. Best results are achieved when
speculatively executing a software pipelined version of the
instrumentation code. For an 8-wide issue machine, measurements for
the SPECint95 benchmarks indicate a 10-fold reduction in overhead
(from 32.8% to 3.3%), when compared with previous techniques.

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The author's web site:
<a href="http://www.ece.ncsu.edu/tinker">www.ece.ncsu.edu/tinker</a>