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IPPS
2007
IEEE
14 years 1 months ago
Challenges in Executing Data Intensive Biometric Workloads on a Desktop Grid
Desktop grids have traditionally focused on executing computation intensive workloads. Can they also be used to execute data-intensive workloads? To answer this question, we prese...
Christopher Moretti, Timothy C. Faltemier, Douglas...
SOSP
2009
ACM
14 years 3 months ago
Quincy: fair scheduling for distributed computing clusters
This paper addresses the problem of scheduling concurrent jobs on clusters where application data is stored on the computing nodes. This setting, in which scheduling computations ...
Michael Isard, Vijayan Prabhakaran, Jon Currey, Ud...
HIPC
2009
Springer
13 years 4 months ago
Comparing the performance of clusters, Hadoop, and Active Disks on microarray correlation computations
Abstract--Microarray-based comparative genomic hybridization (aCGH) offers an increasingly fine-grained method for detecting copy number variations in DNA. These copy number variat...
Jeffrey A. Delmerico, Nathanial A. Byrnes, Andrew ...
SASP
2008
IEEE
162views Hardware» more  SASP 2008»
14 years 1 months ago
Accelerating Compute-Intensive Applications with GPUs and FPGAs
—Accelerators are special purpose processors designed to speed up compute-intensive sections of applications. Two extreme endpoints in the spectrum of possible accelerators are F...
Shuai Che, Jie Li, Jeremy W. Sheaffer, Kevin Skadr...
DAC
2001
ACM
14 years 7 months ago
Detection of Partially Simultaneously Alive Signals in Storage Requirement Estimation for Data Intensive Applications
In this paper, we propose a novel storage requirement estimation methodology for use in the early system design phases when the data transfer ordering is only partially fixed. At ...
Per Gunnar Kjeldsberg, Francky Catthoor, Einar J. ...