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CONCURRENCY
2010
130views more  CONCURRENCY 2010»
15 years 3 months ago
Enabling high-speed asynchronous data extraction and transfer using DART
As the complexity and scale of current scientific and engineering applications grow, managing and transporting the large amounts of data they generate is quickly becoming a signif...
Ciprian Docan, Manish Parashar, Scott Klasky
VEE
2012
ACM
322views Virtualization» more  VEE 2012»
13 years 11 months ago
Modeling virtualized applications using machine learning techniques
With the growing adoption of virtualized datacenters and cloud hosting services, the allocation and sizing of resources such as CPU, memory, and I/O bandwidth for virtual machines...
Sajib Kundu, Raju Rangaswami, Ajay Gulati, Ming Zh...
CGF
2008
100views more  CGF 2008»
15 years 3 months ago
Density Displays for Data Stream Monitoring
In many business applications, large data workloads such as sales figures or process performance measures need to be monitored in real-time. The data analysts want to catch proble...
Ming C. Hao, Daniel A. Keim, Umeshwar Dayal, Danie...
ICDCS
2012
IEEE
13 years 6 months ago
eTransform: Transforming Enterprise Data Centers by Automated Consolidation
Abstract—Modern day enterprises have a large IT infrastructure comprising thousands of applications running on servers housed in tens of data centers geographically spread out. T...
Rahul Singh, Prashant J. Shenoy, K. K. Ramakrishna...
KDD
2008
ACM
140views Data Mining» more  KDD 2008»
16 years 4 months ago
Semi-supervised approach to rapid and reliable labeling of large data sets
Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...
György J. Simon, Vipin Kumar, Zhi-Li Zhang