For modern superscalar processors which implement deeper and wider pipelines, accurate branch prediction is crucial for feeding sufficient number of correct instructions into the superscalar’s highly-parallelized execution core. In this paper, we show that what the branch predictor is learning has significant implications for its ability to make effective use of branch correlation and its abili...

Random decision tree is an ensemble of decision trees. The feature at any node of a tree in the ensemble is chosen randomly from remaining features. A chosen discrete feature on a decision path cannot be chosen again. Continuous feature can be chosen multiple times, however, with a different splitting value each time. During classification, each tree outputs raw posterior probability. The proba...

We present a novel Dynamic Bayesian Network for pedestrian path prediction in the intelligent vehicle domain. The model incorporates the pedestrian situational awareness, situation criticality and spatial layout of the environment as latent states on top of a Switching Linear Dynamical System (SLDS) to anticipate changes in the pedestrian dynamics. Using computer vision, situational awareness i...

Nowadays, path prediction is being extensively examined for use in the context of mobile and wireless computing towards more efficient network resource management schemes. Path prediction allows the network and services to further enhance the quality of service levels that the user enjoys. In this paper we present a path prediction algorithm that exploits the machine learning algorithm of learn...

The shadow of diffraction, which account for the growth of trees based on wireless sensors and automatic acquisition of environmental information, were presented to meet the requirements for a wireless sensor network in a forest. there’s a necessity to avoid the dead zone of signal diffraction when laying wireless sensor in the forest, the integration of SBR and UTD is applied to study the impa...

The importance of wireless path loss prediction and interference minimization studies in various environments cannot be over-emphasized. In fact, numerous researchers have done massive work on scrutinizing the effectiveness existing models for channel modeling. difficulties experienced by determining or having detailed information about propagating environment prompted use computational intelli...

How to resolve the control flow breaking caused by the branch instructions is a major issue in modern deep pipeline processor design. Our project is based on the paper of J. Stark et. al. [1], a variable length path branch predictor. It uses the branch path information for prediction, and change the length of the path dynamically based on the profiling of the application. It shows that a “cleve...