We present a new data partitioning strategy for parallel computing on three interconnected clusters. This partitioning has two advantages over existing partitionings. First it can...
This paper presents an eco-friendly daemon that reduces power and energy consumption while better maintaining high performance via an accurate workload characterization that infer...
Clustering is an important technique for understanding and analysis of large multi-dimensional datasets in many scientific applications. Most of clustering research to date has be...
Both technology mapping and circuit clustering have a large impact on FPGA designs in terms of circuit performance, area, and power dissipation. Existing FPGA design flows carry o...
Spectral clustering is one of the most widely used techniques for extracting the underlying global structure of a data set. Compressed sensing and matrix completion have emerged a...