905924
Resource Monitoring with Globus Toolkit 4
The past few years have seen the Grid rapidly evolving towards a service-oriented computing infrastructure. With the OGSA facilitating this evolution, it is expected that WSRF will be acting as the main an enabling technology to drive the Grid further. Resource monitoring plays a critical role in managing a large-scale Grid system. This paper presents GREMO, a lightweight resource monitor developed with Globus Toolkit 4 (GT4) for monitoring CPU and memory of computing nodes in a Windows and Linux environments.
45224109
Service Matchmaking and Discovery with Rough Sets
The past few years have seen the Grid is evolving as a service-oriented computing infrastructure. It is foreseen that various resources in a Grid environment will be exposed as services for use by a wider user community. Service discovery becomes an issue of vital importance for utilising Grid facilities. This paper presents Rosse, a Rough Sets based Search Engine for service discovery that can deal with uncertainty of service properties when matching service advertisements with service requests. The evaluation results show that Rosse is more effective in service discovery compared with other mechanisms such as UDDI keyword matching and OWL-S matchmaking.
14345064
A Wrapper Generator for Wrapping High Performance Legacy Codes as Java/CORBA Components
This paper describes a Wrapper Generator for wrapping high performance legacy codes as Java/CORBA components for use in a distributed component-based problem- solving environment. Using the Wrapper Generator we ave automatically wrapped an MPI-based legacycode as a single CORBA object, and implemented a problem- solving environment for molecular dynamic simulations. Performance comparisons between runs of the CORBA object and the original legacy code on a cluster of workstations and on a parallel computer are also presented.
1974621
Engineering high-performance legacy codes as CORBA components for problem-solving environments
This paper describes techniques used to leverage high-performance legacy codes as CORBA components to a distributed problem-solving environment. It first briefly introduces the software architecture adopted by the environment. Then it presents a CORBA oriented wrapper generator (COWG) which can be used to automatically wrap high-performance legacy codes as CORBA components. Two legacy codes have been wrapped with COWG. One is an MPI-based molecular dynamic simulation (MDS) code, the other is a finite element-based computational fluid dynamics (CFD) code for simulating incompressible Navier-Stokes flows. Performance comparisons between runs of the MDS CORBA component and the original MDS legacy code on a cluster of workstations and on a parallel computer are also presented. Wrapped as CORBA components, these legacy codes can be reused in a distributed computing environment. The first case shows that high-performance can be maintained with the wrapped MDS component. The second case shows that a Web user can submit a task to the wrapped CFD component through a Web page without knowing the exact implementation of the component. In this way, a user's desktop computing environment can be extended to a high-performance computing environment using a cluster of workstations or a parallel computer.
5393650
PaDDMAS: parallel and distributed data mining application suite
Discovering complex associations, anomalies and patterns in distributed data sets is gaining popularity in a range of scientific, medical and business applications. Various algorithms are employed to perform data analysis within a domain, and range from statistical to machine learning and AI based techniques. Several issues need to be addressed however to scale such approaches to large data sets, particularly when these are applied to data distributed at various sites. As new analysis techniques are identified, the core tool set must enable easy integration of such analytical components. Similarly, results from an analysis engines must be sharable, to enable storage, visualisation or further analysis of results. We describe the architecture of PaDDMAS, a component based system for developing distributed data mining applications. PaDDMAS provides a tool set for combining pre-developed or custom components using a dataflow approach, with components performing analysis, data extraction or data management and translation. Each component is wrapped as a Java/CORBA object, and has an interface defined in XML. Components can be serial or parallel objects, and may be binary or contain a more complex internal structure. We demonstrate a prototype using a neural network analysis algorithm.
7274224
Wrapping MPI-based legacy codes as Java/CORBA components
Abstract Techniques for wrapping an MPI-based molecular dynamics (MD) simulation code as Java/CORBA components, for use within a distributed component based problem solving environment (CB-PSE), is presented. A legacy code for simulating a Lennard–Jones fluid is first wrapped as a single CORBA object, followed by division of the code into computational sub-units, where each sub-unit is wrapped as a CORBA object containing MPI calls, and run on a cluster of workstations — enabling different MPI implementations to inter-operate. Using a Java implementation, users can submit simulation tasks through a Web based interface, without needing to know implementation details of the legacy code, or the exact interaction between sub-units within the code. We provide performance comparisons of wrapping the entire MD code as a single object versus wrapping sub-units within it, and offer a simple performance model to explain our findings.
16584711
PeerWindow: an efficient, heterogeneous, and autonomic node collection protocol
Nodes in peer-to-peer systems need to know the information about others to optimize neighbor selection, resource exchanging, replica placement, load balancing, query optimization, and other collaborative operations. However, how to collect this information effectively is still an open issue. In this paper, we propose a novel information collection protocol, PeerWindow, with which each node can collect a large amount of pointers to other nodes at a very low cost. Compared to existing protocols, PeerWindow is 1) efficient, the cost of collecting 1,000 pointers being less than 1 kbps in a common system environment, 2) heterogeneous, nodes with different capacities collecting different amounts of information, and 3) autonomic, nodes determining their bandwidth cost for node collection by themselves and adjusting it dynamically. PeerWindow can be used in many existing peer-to-peer systems and has tremendous potential for future expansions.
15035117
How to share concurrent wait-free variables
Sharing data between multiple asynchronous users—each of which can atomically read and write the data—is a feature that may help to increase the amount of parallelism in distributed systems. An algorithm implementing this feature is presented. The main construction of an <italic>n</italic>-user atomic variable directly from single-writer, single-reader atomic variables uses <italic>O(n)</italic> control bits and <italic>O(n)</italic> accesses per Read/Write running in <italic>O(1)</italic> parallel time.
9175149
Generation of Comprehensible Hypotheses from Gene Expression Data
Machine learning techniques have been recognized as powerful tools for the analysis of gene expression data. However, most learning techniques used in class prediction in gene expression analysis during the past years generate black-box models. Although the prediction accuracy of these models could be very well, they provide little insight into the biological facts. This paper holds the recognition that a more reasonable role for machine learning techniques is to generate hypotheses that can be verified or refined by human experts instead of making decisions for human experts. Based on this recognition, a general approach to generate comprehensible hypotheses from gene expression data is described and applied to human acute leukemias as a test case. The results demonstrate the feasibility of using machine learning techniques to help form hypotheses on the relationship between genes and certain diseases.
6156793
Optimum Robot Control for 3D Virtual Fixture in Constrained ENT Surgery
In ENT surgery, the operating volume is very limited. This is especially true in sinus surgery, when the instrument passes through the sinus cavity to reach the pathological area. The sinus bones impose geometric constraints on the work volume. During the surgery, the surgeon needs to take care of the motion of the instrument tip to accomplish some delicate procedure; meanwhile he/she needs to avoid hitting anatomic constraints. In this paper, we present a method to assist the path following task in a constrained area. We project instrument tip motion, boundary information on the joint displacement via robot kinematics, and then use a constrained quadratic optimization algorithm to compute the optimal set of corresponding joint displacements. In the preliminary study, we show that the optimization constrained control can avoid collision with geometric constraints on the work volume, while keeping the precision of the tool motion.
1558162
Monitoring Abnormal Patterns with Complex Semantics over ICU Data Streams
Monitoring abnormal patterns in data streams is an important research area for many applications. In this paper we present a new approach MAPS(Monitoring Abnormal Patterns over data Streams) to model and identify the abnormal patterns over the massive data streams. Compared with other data streams, ICU streaming data have their own features: pseudo-periodicity and polymorphism. MAPS first extracts patterns from the online arriving data streams and then normalizes them according to their pseudo-periodic semantics. Abnormal patterns will be detected if they are satisfied the predicates defined in the clinician-specifying normal patterns. At last, a real application demonstrates that MAPS is efficient and effective in several important aspects.