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» High-Level Optimization via Automated Statistical Modeling
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TVLSI
2008
140views more  TVLSI 2008»
13 years 7 months ago
A Novel Mutation-Based Validation Paradigm for High-Level Hardware Descriptions
We present a Mutation-based Validation Paradigm (MVP) technology that can handle complete high-level microprocessor implementations and is based on explicit design error modeling, ...
Jorge Campos, Hussain Al-Asaad
DAC
2007
ACM
14 years 8 months ago
Shared Resource Access Attributes for High-Level Contention Models
Emerging single-chip heterogeneous multiprocessors feature hundreds of design elements contending for shared resources, making it difficult to isolate performance impacts of indiv...
Alex Bobrek, JoAnn M. Paul, Donald E. Thomas
ICLP
2009
Springer
14 years 8 months ago
Generative Modeling by PRISM
PRISM is a probabilistic extension of Prolog. It is a high level language for probabilistic modeling capable of learning statistical parameters from observed data. After reviewing ...
Taisuke Sato
AVSS
2007
IEEE
14 years 2 months ago
Vehicular traffic density estimation via statistical methods with automated state learning
This paper proposes a novel approach of combining an unsupervised clustering scheme called AutoClass with Hidden Markov Models (HMMs) to determine the traffic density state in a R...
Evan Tan, Jing Chen