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128
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KDD
2004
ACM
118views Data Mining» more  KDD 2004»
16 years 5 months ago
Parallel computation of high dimensional robust correlation and covariance matrices
The computation of covariance and correlation matrices are critical to many data mining applications and processes. Unfortunately the classical covariance and correlation matrices...
James Chilson, Raymond T. Ng, Alan Wagner, Ruben H...
ASPLOS
2008
ACM
15 years 6 months ago
Optimistic parallelism benefits from data partitioning
Recent studies of irregular applications such as finite-element mesh generators and data-clustering codes have shown that these applications have a generalized data parallelism ar...
Milind Kulkarni, Keshav Pingali, Ganesh Ramanaraya...
162
Voted
BMCBI
2011
14 years 11 months ago
DecGPU: distributed error correction on massively parallel graphics processing units using CUDA and MPI
Background: Next-generation sequencing technologies have led to the high-throughput production of sequence data (reads) at low cost. However, these reads are significantly shorter...
Yongchao Liu, Bertil Schmidt, Douglas L. Maskell
SIGSOFT
2009
ACM
16 years 5 months ago
SCA: a semantic conflict analyzer for parallel changes
Parallel changes are becoming increasingly prevalent in the development of large scale software system. To further study the relationship between parallel changes and faults, we h...
Danhua Shao, Sarfraz Khurshid, Dewayne E. Perry
SIGMOD
2004
ACM
151views Database» more  SIGMOD 2004»
16 years 4 months ago
Highly-Available, Fault-Tolerant, Parallel Dataflows
We present a technique that masks failures in a cluster to provide high availability and fault-tolerance for long-running, parallelized dataflows. We can use these dataflows to im...
Mehul A. Shah, Joseph M. Hellerstein, Eric A. Brew...