A common technique to deploy linear prediction to nonstationary signals is time segmentation and local analysis. In [1], the temporal changes of linear prediction coefficients (L...
Communication misses--those serviced by dirty data in remote caches--are a pressing performance limiter in shared-memory multiprocessors. Recent research has indicated that tempor...
Machine learning approaches offer some of the most cost-effective approaches to building predictive models (e.g., classifiers) in a broad range of applications in computational bio...
—In this paper, we analyze restrictions of traditional models affecting the accuracy of analytical prediction of the execution time of collective communication operations. In par...
Alexey L. Lastovetsky, Vladimir Rychkov, Maureen O...
This paper presents a prediction algorithm for estimating the upper bound of future Web traffic volume. Unlike traditional traffic predictions that are performed at a single time ...