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FPGA
2010
ACM
232views FPGA» more  FPGA 2010»
15 years 28 days ago
High-throughput bayesian computing machine with reconfigurable hardware
We use reconfigurable hardware to construct a high throughput Bayesian computing machine (BCM) capable of evaluating probabilistic networks with arbitrary DAG (directed acyclic gr...
Mingjie Lin, Ilia Lebedev, John Wawrzynek
119
Voted
JAIR
2008
135views more  JAIR 2008»
15 years 22 days ago
On Similarities between Inference in Game Theory and Machine Learning
In this paper, we elucidate the equivalence between inference in game theory and machine learning. Our aim in so doing is to establish an equivalent vocabulary between the two dom...
Iead Rezek, David S. Leslie, Steven Reece, Stephen...
108
Voted
ICPP
2008
IEEE
15 years 7 months ago
Machine Learning Models to Predict Performance of Computer System Design Alternatives
Computer manufacturers spend a huge amount of time, resources, and money in designing new systems and newer configurations, and their ability to reduce costs, charge competitive p...
Berkin Özisikyilmaz, Gokhan Memik, Alok N. Ch...
105
Voted
HPCA
1998
IEEE
15 years 5 months ago
FPGA Based Custom Computing Machines for Irregular Problems
Over the past few years there has been increased interest in building custom computing machines (CCMs) as a way of achieving very high performance on specific problems. The advent...
David Abramson, Paul Logothetis, Adam Postula, Mar...
110
Voted
CLUSTER
2007
IEEE
15 years 4 months ago
Identifying energy-efficient concurrency levels using machine learning
Abstract-- Multicore microprocessors have been largely motivated by the diminishing returns in performance and the increased power consumption of single-threaded ILP microprocessor...
Matthew Curtis-Maury, Karan Singh, Sally A. McKee,...