Distributed learning is a problem of fundamental interest in machine learning and cognitive science. In this paper, we present asynchronous distributed learning algorithms for two...
—This paper derives simple, yet fundamental formulas to describe the interplay between parallelism of an application, program performance, and energy consumption. Given the ratio...
Power management is critical to power-constrained real-time systems. In this paper, we present a dynamic power management algorithm. Unlike other approaches that focus on the trad...
A multiprocessor virtual machine benefits its guest operating system in supporting scalable job throughput and request latency--useful properties in server consolidation where ser...
In distributed real-time systems, an application is often modeled as a set of real-time transactions, where each transaction is a chain of precedence-constrained tasks. Each task ...