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» On the Execution of Deep Models
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PVLDB
2008
182views more  PVLDB 2008»
15 years 6 months ago
SCOPE: easy and efficient parallel processing of massive data sets
Companies providing cloud-scale services have an increasing need to store and analyze massive data sets such as search logs and click streams. For cost and performance reasons, pr...
Ronnie Chaiken, Bob Jenkins, Per-Åke Larson,...
AAAI
2007
15 years 9 months ago
Learning by Reading: A Prototype System, Performance Baseline and Lessons Learned
A traditional goal of Artificial Intelligence research has been a system that can read unrestricted natural language texts on a given topic, build a model of that topic and reason...
Ken Barker, Bhalchandra Agashe, Shaw Yi Chaw, Jame...
PADS
2003
ACM
16 years 3 days ago
Maya: a Multi-Paradigm Network Modeling Framework
This paper presents Maya, a multi-paradigm, scalable and extensible network modeling framework for emulating distributed applications. A novel three-tier architecture is proposed ...
Junlan Zhou, Zhengrong Ji, Mineo Takai, Rajive Bag...
ECMDAFA
2006
Springer
136views Hardware» more  ECMDAFA 2006»
15 years 10 months ago
Finding a Path to Model Consistency
A core problem in Model Driven Engineering is model consistency achievement: all models must satisfy relationships constraining them. Active consistency techniques monitor and cont...
Gregory de Fombelle, Xavier Blanc, Laurent Rioux, ...
ICPP
1991
IEEE
15 years 10 months ago
Two Techniques to Enhance the Performance of Memory Consistency Models
The memory consistency model supported by a multiprocessor directly affects its performance. Thus, several attempts have been made to relax the consistency models to allow for mor...
Kourosh Gharachorloo, Anoop Gupta, John L. Henness...