Design space exploration during high level synthesis is often conducted through ad-hoc probing of the solution space using some scheduling algorithm. This is not only time consumi...
Gang Wang, Wenrui Gong, Brian DeRenzi, Ryan Kastne...
Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
Abstract--The multimode resource-constrained projectscheduling problem with discounted cash flows (MRCPSPDCF) is important and challenging for project management. As the problem is...
Wei-neng Chen, Jun Zhang, Henry Shu-Hung Chung, Ru...
While meta-heuristics are effective for solving large-scale combinatorial optimization problems, they result from time-consuming trial-and-error algorithm design tailored to speci...
Hoong Chuin Lau, Wee Chong Wan, Min Kwang Lim, Ste...
We present a novel methodology for design space exploration using a two-steps scheme to optimize the number of virtual channel buffers (buffers take the premier share of the route...