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» Run-Time Techniques for Parallelizing Sparse Matrix Problems
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IM
2007
13 years 6 months ago
Estimating End-to-End Performance by Collaborative Prediction with Active Sampling
— Accurately estimating end-to-end performance in distributed systems is essential both for monitoring compliance with service-level agreements (SLAs) and for performance optimiz...
Irina Rish, Gerald Tesauro
GISCIENCE
2004
Springer
130views GIS» more  GISCIENCE 2004»
13 years 11 months ago
Comparing Exact and Approximate Spatial Auto-regression Model Solutions for Spatial Data Analysis
The spatial auto-regression (SAR) model is a popular spatial data analysis technique, which has been used in many applications with geo-spatial datasets. However, exact solutions f...
Baris M. Kazar, Shashi Shekhar, David J. Lilja, Ra...
SASP
2009
IEEE
291views Hardware» more  SASP 2009»
14 years 6 days ago
A parameterisable and scalable Smith-Waterman algorithm implementation on CUDA-compatible GPUs
—This paper describes a multi-threaded parallel design and implementation of the Smith-Waterman (SM) algorithm on compute unified device architecture (CUDA)-compatible graphic pr...
Cheng Ling, Khaled Benkrid, Tsuyoshi Hamada
ICDCS
2010
IEEE
13 years 7 months ago
Distributed Coverage in Wireless Ad Hoc and Sensor Networks by Topological Graph Approaches
Abstract—Coverage problem is a fundamental issue in wireless ad hoc and sensor networks. Previous techniques for coverage scheduling often require accurate location information o...
Dezun Dong, Yunhao Liu, Kebin Liu, Xiangke Liao
ICDM
2010
IEEE
264views Data Mining» more  ICDM 2010»
13 years 3 months ago
Block-GP: Scalable Gaussian Process Regression for Multimodal Data
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algori...
Kamalika Das, Ashok N. Srivastava