Performance improvements for computational sciences such as biology, physics, and chemistry are critically dependent on advances in multicore and manycore hardware. However, these emerging systems require substantial investment in software development time to migrate, optimize, and validate existing science models. The focus of our study is to examine the step-by-step process of adapting new and existing computational biology models to multicore and distributed memory architectures. We analyze different strategies that may be more efficient in multicore vs. manycore environments. Our target application, Kingen, was developed to simulate AMPAR ion channel activity and to optimize kinetic model rate constants to biological data. Kingen uses a genetic algorithm to stochastically search parameter space to find global optima. As each individual in the population describes a rate constant parameter set in the kinetic model and the model is evaluated for each individual, there is significant computational complexity and parallelism in even a simple model run.

Energy efficiency is the essential consideration in advances of wireless sensor networks (WSNs) usefully designed for low data rate, low power consumption, and low-cost networking. Mindful of the above constraints, selecting an appropriate routing protocol can significantly improve overall performance with limited sensor network resources, especially energy awareness in WSNs. We propose an energy-aware routing protocol improved by our adaptive-gossip algorithm that will reduce the redundant routing messages so that it can minimize the overall energy consumption of a WSN. To analyze the energy efficiency, we introduce two energy performance metrics: Delay*Energy and Normalized-RoutingLoad*Energy. These metrics suggest that energy consumption heavily depends on both packet losses and packet delivery successes that affect delay and routing overhead respectively. We present both analytical and experimental results thoroughly to evaluate our adaptive-gossip proposal, and demonstrate its advantages over flooding and static-gossiping based protocols for densely deployed networks and different types of network such as peer-to-peer and multi-to-one.

This paper presents an efficient file enciphering service for a UNIX-like operating system. It allows OSs to encipher or/and decipher automatically only a portion of being accessed file by applications. Its approach shows that users can access encrypted files using the proposed method much faster than using the existing techniques without losing the user transparency.

In this paper, we present an architecture of an AdaptiveCommunication System (ACS) that provides applicationswith programmable communication, control, andmanagement services that can be adopted dynamicallyto maximize application performance at runtime. ACSsupports adaptive and scalable communication servicesthat select the appropriate multicast/broadcast algorithmsfor a given class of applications. These algorithms takeinto consideration both the application requirements andthe load of computing and communication systems.We overview the ACS architecture and then describe ourapproach to implement the ACS group communication services.We introduce two procedures (Resource Aware procedureand Application Aware procedure) to build the appropriatemulticast tree that takes into consideration both thecharacteristics and load conditions of machines as well asthe group communication patterns of a given application.We develop analytical techniques and new metric measuresto characterize and quantify the performance of a multicasttree. We also present our preliminary performance resultsthat show significant performance gain can be achievedfrom using ACS multicast algorithms.

The requirements of grand challenge problems and the deployment of gigabit networks makes the network computing framework an attractive and cost effective computing environment with which to interconnect geographically distributed processing and storage resources. Our project, Virtual Distributed Computing Environment (VDCE), provides a problem-solving environment for high-performance distributed computing over wide area networks. VDCE delivers well-defined library functions that relieve end-users of tedious task implementations and also support reusability. In this paper we present the conceptual design of VDCE software architecture, which is defined in three modules: (a) the Application Editor, a user-friendly application development environment that generates the Application Flow Graph (AFG) of an application; (b) the Application Scheduler, which provides an efficient task-to-resource mapping of AFG; and (c) the VDCE Runtime System, which is responsible for running and managing application execution and monitoring the VDCE resources.