Characterizing vulnerability of parallelism to resource constraints

The theoretical available instruction level parallelism in most benchmark is very high. Vulnerability is related to the difficulty with which we can extract this parallelism with finite resources. This study characterizes the vulnerability of parallelism to resource constraints by scheduling dynamic dependence graphs (DDGs) from traces of several benchmarks using different scheduling algorithms and different number of functional units. It is observed that the execution time of the DDGs does not vary significantly with low-level scheduling algorithms like lazy, slack, etc. Measures of vulnerability based on slack and load were also considered. Although Accslk-Load, which uses a combination of accurate slack and load to make a prediction, has a prediction accuracy of about 85%, the prediction rate is only 42%. On the other hand, even though the prediction accuracy of σ(L^x), the standard deviation in the load, is not as high, there is a prediction in all the cases. The DDG execution time is also found to be most vulnerable to the functional unit with the greatest σ(L_x)