Distributed-system observation tools require an efficient data structure to store and query the partial-order of execution. Such data structures typically use vector timestamps to...
A new method for the simplification of flow fields is presented. It is based on continuous clustering. A well-known physical clustering model, the Cahn Hillard model which desc...
Clustering and scheduling of tasks for parallel implementation is a well researched problem. Several techniques have been presented in the literature to improve performance and re...
Clustering is a common problem in the analysis of large data sets. Streaming algorithms, which make a single pass over the data set using small working memory and produce a cluster...
Clustered processors lose performance as a result of clusteringinduced stalls. Such stalls are the result of distributed resources and cluster communication delays. Our performanc...