In this era of intense liking to automation in almost all time-critical fields, real-time systems have got widespread utilization in industrial, commercial, medical, space and mil...
Mohammad Ullah Khan, Kurt Geihs, Felix Gutbrodt, P...
Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
One of the most fundamental problems automatic parallelization tools are confronted with is to find an optimal domain decomposition for a given application. For regular domain prob...
A new platform for reconfigurable computing has an object-based programming model, with architecture, silicon and tools designed to faithfully realize this model. The platform is ...
This paper proposes the study of a new computation model that attempts to address the underlying sources of performance degradation (e.g. latency, overhead, and starvation) and th...
Guang R. Gao, Thomas L. Sterling, Rick Stevens, Ma...