Using Participant Choice to Enhance Memory Performance

Two Techniques to Enhance the Performance of Memory Consistency Models

The memory consistency model supported by a multiprocessor directly affects its performance. Thus, several attempts have been made to relax the consistency models to allow for more buffering and pipelining of memory accesses. Unfortunately, the potential increase in performance afforded by relaxing the consistency model is accompanied by a more complex programming model. This paper introduces t...

Using Cohort-Scheduling to Enhance Server Performance

A server application is commonly organized as a collection of concurrent threads, each of which executes the code necessary to process a request. This software architecture, which causes frequent control transfers between unrelated pieces of code, decreases instruction and data locality, and consequently reduces the effectiveness of hardware mechanisms such as caches, TLBs, and branch predictor...

Using traffic asymmetry to enhance TCP performance

A wealth of recent work has gone into optimizing the performance of Transmission Control Protocol (TCP) on the downlink channel of wireless networks such as for example, honing its congestion awareness mechanism so that it is minimally affected by random wireless losses, and optimizing achieved fairness of the end-to-end TCP rates. Other work has gone into balancing the allocation of a shared r...

Observing Unobserved Heterogeneity: Using Process Data to Enhance Choice Models

USING DISTRIBUTION OF DATA TO ENHANCE PERFORMANCE OF FUZZY CLASSIFICATION SYSTEMS

This paper considers the automatic design of fuzzy rule-basedclassification systems based on labeled data. The classification performance andinterpretability are of major importance in these systems. In this paper, weutilize the distribution of training patterns in decision subspace of each fuzzyrule to improve its initially assigned certainty grade (i.e. rule weight). Ourapproach uses a punish...