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IEEECIT
2010
IEEE
15 years 3 months ago
Scaling the iHMM: Parallelization versus Hadoop
—This paper compares parallel and distributed implementations of an iterative, Gibbs sampling, machine learning algorithm. Distributed implementations run under Hadoop on facilit...
Sebastien Bratieres, Jurgen Van Gael, Andreas Vlac...
ASPDAC
2011
ACM
227views Hardware» more  ASPDAC 2011»
14 years 8 months ago
Minimizing buffer requirements for throughput constrained parallel execution of synchronous dataflow graph
– This paper concerns throughput-constrained parallel execution of synchronous data flow graphs. This paper assumes static mapping and dynamic scheduling of nodes, which has seve...
Tae-ho Shin, Hyunok Oh, Soonhoi Ha
SIGIR
2011
ACM
14 years 7 months ago
Parallel learning to rank for information retrieval
Learning to rank represents a category of effective ranking methods for information retrieval. While the primary concern of existing research has been accuracy, learning efficien...
Shuaiqiang Wang, Byron J. Gao, Ke Wang, Hady Wiraw...
IFM
2009
Springer
119views Formal Methods» more  IFM 2009»
15 years 11 months ago
Parallel Processes with Real-Time and Data: The ATLANTIF Intermediate Format
Abstract. To model real-life critical systems, one needs“high-level”languages to express three important concepts: complex data structures, concurrency, and real-time. So far, ...
Jan Stöcker, Frédéric Lang, Hub...
SIPS
2007
IEEE
15 years 10 months ago
An Area-Efficient FPGA-Based Architecture for Fully-Parallel Stochastic LDPC Decoding
Stochastic decoding is a new alternative method for low complexity decoding of error-correcting codes. This paper presents the first hardware architecture for stochastic decoding...
Saeed Sharifi Tehrani, Shie Mannor, Warren J. Gros...