The crucial issue in many classification applications is how to achieve the best possible classifier with a limited number of labeled data for training. Training data selection is ...
The Sesame modeling and simulation framework aims at early and thus efficient system-level design space exploration of embedded multimedia system architectures. So far, Sesame onl...
The performance of data-parallel algorithms for spatial operations using data-parallel variants of the bucket PMR quadtree, R-tree, and R+-tree spatial data structures is compared...
Exploiting parallelism at both the multiprocessor level and the instruction level is an e ective means for supercomputers to achieve high-performance. The amount of instruction-le...
Scott A. Mahlke, William Y. Chen, John C. Gyllenha...
Information on the behavior of programs is essential for deciding the number and nature of functional units in high performance architectures. In this paper, we present studies on...
Lizy Kurian John, Vinod Reddy, Paul T. Hulina, Lee...