We propose dynamic scheduler designs to improve the scheduler scalability and reduce its complexity in the SMT processors. Our first design is an adaptation of the recently propos...
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Previous approaches for computing duplicate-sensitive aggregates in sensor networks (e.g., in TAG) have used a tree topology, in order to conserve energy and to avoid double-count...
Suman Nath, Phillip B. Gibbons, Srinivasan Seshan,...
This paper describes a novel algorithm to extract surface meshes directly from implicitly represented heterogeneous models made of different constituent materials. Our approach ca...
In a Grid computing environment, resources are shared among a large number of applications. Brokers and schedulers find matching resources and schedule the execution of the applic...
Seyed Masoud Sadjadi, Shu Shimizu, Javier Figueroa...