Proximity Optimization for Adaptive Circuit Design

The performance growth of conventional VLSI circuits is seriously hampered by various variation effects and the fundamental limit of chip power density. Adaptive circuit design is recognized as a power-efficient approach to tackling the variation challenge. However, it tends to entail large area overhead if not carefully designed. This work studies how to reduce the overhead by forming adaptivity blocks considering both timing and physical proximity among logic cells. The proximity optimization consists of timing and location aware cell clustering and incremental placement enforcing the clusters. Experiments are performed on the ICCAD 2014 benchmark circuits, which include case of near one million cells. The experiment results prove that during clustering, location proximity among logic cells are equally important as the timing proximity among logic cells. Compared to alternative methods, our approach achieves 25% to 75% area overhead reduction with an average of 0:6% wirelength overhead, while retains about the same timing yield and power consumption

Sensitivity of night cooling performance to room/system design: surrogate models based on CFD

Night cooling, especially in offices, attracts growing interest. Unfortunately, building designers face considerable problems with the case-specific convective heat transfer by night. The BES programs they use actually need extra input, from either costly experiments or CFD simulations. Alternatively, up-front research on how to engineer best a generic night cooled office – as in this work – can thrust the application of night cooling. A fully automated configuration of data sampling, geometry/grid generation, CFD solving and surrogate modelling, generates several surrogate models. These models relate the convective heat flow in a night cooled landscape office to the ventilation concept, mass distribution, geometry and driving force for convective heat transfer. The results indicate that cases with a thermally massive floor have the highest night cooling performance

Energy-Efficient Resource Allocation for Device-to-Device Underlay Communication

Device-to-device (D2D) communication underlaying cellular networks is expected to bring significant benefits for utilizing resources, improving user throughput and extending battery life of user equipments. However, the allocation of radio and power resources to D2D communication needs elaborate coordination, as D2D communication can cause interference to cellular communication. In this paper, we study joint channel and power allocation to improve the energy efficiency of user equipments. To solve the problem efficiently, we introduce an iterative combinatorial auction algorithm, where the D2D users are considered as bidders that compete for channel resources, and the cellular network is treated as the auctioneer. We also analyze important properties of D2D underlay communication, and present numerical simulations to verify the proposed algorithm.Comment: IEEE Transactions on Wireless Communication

Every Moment Counts: Synchrophasors for Distribution Networks with Variable Resources

Chapter 34 in the textbook, "Renewable Energy Integration: Practical Management of Variability, Uncertainty and Flexibility

NASA Center for Intelligent Robotic Systems for Space Exploration

NASA's program for the civilian exploration of space is a challenge to scientists and engineers to help maintain and further develop the United States' position of leadership in a focused sphere of space activity. Such an ambitious plan requires the contribution and further development of many scientific and technological fields. One research area essential for the success of these space exploration programs is Intelligent Robotic Systems. These systems represent a class of autonomous and semi-autonomous machines that can perform human-like functions with or without human interaction. They are fundamental for activities too hazardous for humans or too distant or complex for remote telemanipulation. To meet this challenge, Rensselaer Polytechnic Institute (RPI) has established an Engineering Research Center for Intelligent Robotic Systems for Space Exploration (CIRSSE). The Center was created with a five year $5.5 million grant from NASA submitted by a team of the Robotics and Automation Laboratories. The Robotics and Automation Laboratories of RPI are the result of the merger of the Robotics and Automation Laboratory of the Department of Electrical, Computer, and Systems Engineering (ECSE) and the Research Laboratory for Kinematics and Robotic Mechanisms of the Department of Mechanical Engineering, Aeronautical Engineering, and Mechanics (ME,AE,&M), in 1987. This report is an examination of the activities that are centered at CIRSSE