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VLSISP
2011
358views Database» more  VLSISP 2011»
13 years 2 months ago
Accelerating Machine-Learning Algorithms on FPGAs using Pattern-Based Decomposition
Machine-learning algorithms are employed in a wide variety of applications to extract useful information from data sets, and many are known to suffer from superlinear increases in ...
Karthik Nagarajan, Brian Holland, Alan D. George, ...
FPGA
2009
ACM
273views FPGA» more  FPGA 2009»
14 years 2 months ago
A parallel/vectorized double-precision exponential core to accelerate computational science applications
Many natural processes exhibit exponential decay and, consequently, computational scientists make extensive use of e−x in computer simulation experiments. While it is common to ...
Robin Pottathuparambil, Ron Sass
ITS
2010
Springer
157views Multimedia» more  ITS 2010»
14 years 11 days ago
A Computational Model of Accelerated Future Learning through Feature Recognition
Accelerated future learning, in which learning proceeds more effectively and more rapidly because of prior learning, is considered to be one of the most interesting measures of ro...
Nan Li, William W. Cohen, Kenneth R. Koedinger
CISS
2011
IEEE
12 years 11 months ago
Hardware accelerated visual attention algorithm
— We present a hardware-accelerated implementation of a bottom-up visual attention algorithm. This algorithm generates a multi-scale saliency map from differences in image intens...
Polina Akselrod, Faye Zhao, Ifigeneia Derekli, Cl&...
IEEEPACT
2005
IEEE
14 years 1 months ago
Exploiting Coarse-Grained Parallelism to Accelerate Protein Motif Finding with a Network Processor
While general-purpose processors have only recently employed chip multiprocessor (CMP) architectures, network processors (NPs) have used heterogeneous multi-core architectures sin...
Ben Wun, Jeremy Buhler, Patrick Crowley