Implementing Multithreaded Protocols for Release Consistency on Top of the Generic DSM-PM2 Platform

10.1007/3-540-47840-X_18DSM-PM2 is an implementation platform designed to facilitate the experimental studies with consistency protocoles for distributed shared memory. This platform provides basic building blocks, allowing for an easy design, implementation and evaluation of a large variety of multithreaded consistency protocols within a unified framework. DSM-PM2 is portable over a large variety of cluster architectures, using various communication interfaces (TCP, MPI, BIP, SCI, VIA, etc.). This paper presents the design of two multithreaded protocols implementing the release consistency model. We evaluate the impact of these consistency protocols on the overall performance of a typical distributed application, for two clusters with different interconnection networks and communication interfaces

Implementation of GenePattern within the Stanford Microarray Database

Hundreds of researchers across the world use the Stanford Microarray Database (SMD; http://smd.stanford.edu/) to store, annotate, view, analyze and share microarray data. In addition to providing registered users at Stanford access to their own data, SMD also provides access to public data, and tools with which to analyze those data, to any public user anywhere in the world. Previously, the addition of new microarray data analysis tools to SMD has been limited by available engineering resources, and in addition, the existing suite of tools did not provide a simple way to design, execute and share analysis pipelines, or to document such pipelines for the purposes of publication. To address this, we have incorporated the GenePattern software package directly into SMD, providing access to many new analysis tools, as well as a plug-in architecture that allows users to directly integrate and share additional tools through SMD. In this article, we describe our implementation of the GenePattern microarray analysis software package into the SMD code base. This extension is available with the SMD source code that is fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD with an enriched data analysis capability

The Stanford Microarray Database accommodates additional microarray platforms and data formats

The Stanford Microarray Database (SMD) (http://smd.stanford.edu) is a research tool for hundreds of Stanford researchers and their collaborators. In addition, SMD functions as a resource for the entire biological research community by providing unrestricted access to microarray data published by SMD users and by disseminating its source code. In addition to storing GenePix (Axon Instruments) and ScanAlyze output from spotted microarrays, SMD has recently added the ability to store, retrieve, display and analyze the complete raw data produced by several additional microarray platforms and image analysis software packages, so that we can also now accept data from Affymetrix GeneChips (MAS5/GCOS or dChip), Agilent Catalog or Custom arrays (using Agilent's Feature Extraction software) or data created by SpotReader (Niles Scientific). We have implemented software that allows us to accept MAGE-ML documents from array manufacturers and to submit MIAME-compliant data in MAGE-ML format directly to ArrayExpress and GEO, greatly increasing the ease with which data from SMD can be published adhering to accepted standards and also increasing the accessibility of published microarray data to the general public. We have introduced a new tool to facilitate data sharing among our users, so that datasets can be shared during, before or after the completion of data analysis. The latest version of the source code for the complete database package was released in November 2004 (http://smd.stanford.edu/download/), allowing researchers around the world to deploy their own installations of SMD

TB database: an integrated platform for tuberculosis research

The effective control of tuberculosis (TB) has been thwarted by the need for prolonged, complex and potentially toxic drug regimens, by reliance on an inefficient vaccine and by the absence of biomarkers of clinical status. The promise of the genomics era for TB control is substantial, but has been hindered by the lack of a central repository that collects and integrates genomic and experimental data about this organism in a way that can be readily accessed and analyzed. The Tuberculosis Database (TBDB) is an integrated database providing access to TB genomic data and resources, relevant to the discovery and development of TB drugs, vaccines and biomarkers. The current release of TBDB houses genome sequence data and annotations for 28 different Mycobacterium tuberculosis strains and related bacteria. TBDB stores pre- and post-publication gene-expression data from M. tuberculosis and its close relatives. TBDB currently hosts data for nearly 1500 public tuberculosis microarrays and 260 arrays for Streptomyces. In addition, TBDB provides access to a suite of comparative genomics and microarray analysis software. By bringing together M. tuberculosis genome annotation and gene-expression data with a suite of analysis tools, TBDB (http://www.tbdb.org/) provides a unique discovery platform for TB research

TB database: an integrated platform for tuberculosis research

The effective control of tuberculosis (TB) has been thwarted by the need for prolonged, complex and potentially toxic drug regimens, by reliance on an inefficient vaccine and by the absence of biomarkers of clinical status. The promise of the genomics era for TB control is substantial, but has been hindered by the lack of a central repository that collects and integrates genomic and experimental data about this organism in a way that can be readily accessed and analyzed. The Tuberculosis Database (TBDB) is an integrated database providing access to TB genomic data and resources, relevant to the discovery and development of TB drugs, vaccines and biomarkers. The current release of TBDB houses genome sequence data and annotations for 28 different Mycobacterium tuberculosis strains and related bacteria. TBDB stores pre- and post-publication gene-expression data from M. tuberculosis and its close relatives. TBDB currently hosts data for nearly 1500 public tuberculosis microarrays and 260 arrays for Streptomyces. In addition, TBDB provides access to a suite of comparative genomics and microarray analysis software. By bringing together M. tuberculosis genome annotation and gene-expression data with a suite of analysis tools, TBDB (http://www.tbdb.org/) provides a unique discovery platform for TB research

On a coupled PDE model for image restoration

In this paper, we consider a new coupled PDE model for image restoration. Both the image and the edge variables are incorporated by coupling them into two different PDEs. It is shown that the initial-boundary value problem has global in time dissipative solutions (in a sense going back to P.-L. Lions), and several properties of these solutions are established. This is a rough draft, and the final version of the paper will contain a modelling part and numerical experiments

SPEEDING UP COMMUTER RAIL SERVICE: COMPARATIVE ACTUAL PERFORMANCE OF TRAIN AND STATION PLATFORM DESIGNS

Speeding up commuter rail service can be achieved by various design changes in trains or stations or both. An analysis was conducted of the effect of a car design intended to achieve low station dwell times, which are termed short dwell time entranceways (SDE). Actual timetable data from commuter rail systems of different design to estimate the time saving from using SDEs compared with traditional end vestibule entranceways (EVE) were used. A new procedure was developed to characterize speed (or run time) performance of trains that accounts for differences among run characteristics (e.g., station spacing, speed limits). The validity of the procedure is assessed, and its usefulness as a complement to train performance simulators is discussed. The lines analyzed had speed limits averaging 60 mph (96.6 km/h) and average station stop spacings of 1.25 mi (2.01 km) to 5.0 mi (8.04 km). The time saving resulting from SDEs versus EVEs at low-level platforms is slightly more than 5% at the shortest station spacing, about 2% at the longest. These gains approximate those from electrification retaining the EVE car design. Thus, car design to achieve low dwell time is a very important option. Because EVE car designs are most prevalent on lines with a mixture of high- and low- level platforms, the implications for such lines, including Americans with Disabilities Act accessibility considerations, are discussed