Hewlett-Packard

About: Hewlett-Packard is a company organization based out in Palo Alto, California, United States. It is known for research contribution in the topics: Signal & Layer (electronics). The organization has 34663 authors who have published 59808 publications receiving 1467218 citations. The organization is also known as: Hewlett Packard & Hewlett-Packard Company.

On-demand multicast routing protocol in multihop wireless mobile networks

Abstract: An ad hoc network is a dynamically reconfigurable wireless network with no fixed infrastructure or central administration. Each host is mobile and must act as a router. Routing and multicasting protocols in ad hoc networks are faced with the challenge of delivering data to destinations through multihop routes in the presence of node movements and topology changes. This paper presents the On-Demand Multicast Routing Protocol (ODMRP) for wireless mobile and hoc networks. ODMRP is a mesh-based, rather than a conventional tree-based, multicast scheme and uses a forwarding group concept; only a subset of nodes forwards the multicast packets via scoped flooding. It applies on-demand procedures to dynamically build routes and maintain multicast group membership. ODMRP is well suited for ad hoc wireless networks with mobile hosts where bandwidth is limited, topology changes frequently, and power is constrained. We evaluate ODMRP performance with other multicast protocols proposed for ad hoc networks via extensive and detailed simulation.

Optimizing NUCA Organizations and Wiring Alternatives for Large Caches with CACTI 6.0

Abstract: A significant part of future microprocessor real estate will be dedicated to L2 or L3 caches. These on-chip caches will heavily impact processor perfor- mance, power dissipation, and thermal management strategies. There are a number of interconnect design considerations that influence power/performance/area characteristics of large caches, such as wire mod- els (width/spacing/repeaters), signaling strategy (RC/differential/transmission), router design, etc. Yet, to date, there exists no analytical tool that takes all of these parameters into account to carry out a design space exploration for large caches and estimate an optimal organization. In this work, we implement two major extensions to the CACTI cache modeling tool that focus on interconnect design for a large cache. First, we add the ability to model different types of wires, such as RC-based wires with different power/delay characteristics and differential low-swing buses. Second, we add the ability to model Non-uniform Cache Access (NUCA). We not only adopt state-of-the-art design space exploration strategies for NUCA, we also enhance this exploration by considering on-chip network contention and a wider spectrum of wiring and routing choices. We present a validation analysis of the new tool (to be released as CACTI 6.0) and present a case study to showcase how the tool can improve architecture research methodologies. Keywords: cache models, non-uniform cache archi- tectures (NUCA), memory hierarchies, on-chip intercon- nects.

Large-Scale Parallel Collaborative Filtering for the Netflix Prize

Abstract: Many recommendation systems suggest items to users by utilizing the techniques of collaborative filtering(CF) based on historical records of items that the users have viewed, purchased, or rated Two major problems that most CF approaches have to contend with are scalability and sparseness of the user profiles To tackle these issues, in this paper, we describe a CF algorithm alternating-least-squares with weighted-?-regularization(ALS-WR), which is implemented on a parallel Matlab platform We show empirically that the performance of ALS-WR (in terms of root mean squared error(RMSE)) monotonically improves with both the number of features and the number of ALS iterations We applied the ALS-WR algorithm on a large-scale CF problem, the Netflix Challenge, with 1000 hidden features and obtained a RMSE score of 08985, which is one of the best results based on a pure method In addition, combining with the parallel version of other known methods, we achieved a performance improvement of 591% over Netflix's own CineMatch recommendation system Our method is simple and scales well to very large datasets

A unified framework for coupling measurement in object-oriented systems

Abstract: The increasing importance being placed on software measurement has led to an increased amount of research developing new software measures. Given the importance of object-oriented development techniques, one specific area where this has occurred is coupling measurement in object-oriented systems. However, despite a very interesting and rich body of work, there is little understanding of the motivation and empirical hypotheses behind many of these new measures. It is often difficult to determine how such measures relate to one another and for which application they can be used. As a consequence, it is very difficult for practitioners and researchers to obtain a clear picture of the state of the art in order to select or define measures for object-oriented systems. This situation is addressed and clarified through several different activities. First, a standardized terminology and formalism for expressing measures is provided which ensures that all measures using it are expressed in a fully consistent and operational manner. Second, to provide a structured synthesis, a review of the existing frameworks and measures for coupling measurement in object-oriented systems takes place. Third, a unified framework, based on the issues discovered in the review, is provided and all existing measures are then classified according to this framework. This paper contributes to an increased understanding of the state-of-the-art.

Object-oriented development: the fusion method

Abstract: 1. Introduction. 2. Analysis Models and Notations. 3. Process of Analysis. 4. Design. 5. Implementation. 6. Case Study. 7. Exercises. 8. Fusion and Other Methods. 9. Reuse. 10. Managing a Fusion Project. Appendix A: Fusion Process Summary. Appendix B: Fusion Notation Summary. Appendix C: Fusion Reference.