Abstract. We present a strategy to develop, in a functional setting, correct, e cient and portable Divide-and-Conquer (DC) programs for massively parallel architectures. Starting f...
This paper explores the scalability of the Stream Processor architecture along the instruction-, data-, and thread-level parallelism dimensions. We develop detailed VLSI-cost and ...
Classification of items taken from data streams requires algorithms that operate in time sensitive and computationally constrained environments. Often, the available time for class...
— This work addresses the problem of building representative subsets of benchmarks from an original large set of benchmarks, using statistical analysis techniques. The subsets sh...
Vassilios N. Christopoulos, David J. Lilja, Paul R...
Existing density-based data stream clustering algorithms use a two-phase scheme approach consisting of an online phase, in which raw data is processed to gather summary statistics...
Agostino Forestiero, Clara Pizzuti, Giandomenico S...