Discovery of Application Workloads from Network File Traces

An understanding of application I/O access patterns is useful in several situations. First, gaining insight into what applications are doing with their data at a semantic level helps in designing efficient storage systems. Second, it helps create benchmarks that mimic realistic application behavior closely. Third, it enables autonomic systems as the information obtained can be used to adapt the system in a closed loop.All these use cases require the ability to extract the application-level semantics of I/O operations. Methods such as modifying application code to associate I/O operations with semantic tags are intrusive. It is well known that network file system traces are an important source of information that can be obtained non-intrusively and analyzed either online or offline. These traces are a sequence of primitive file system operations and their parameters. Simple counting, statistical analysis or deterministic search techniques are inadequate for discovering application-level semantics in the general case, because of the inherent variation and noise in realistic traces.In this paper, we describe a trace analysis methodology based on Profile Hidden Markov Models. We show that the methodology has powerful discriminatory capabilities that enable it to recognize applications based on the patterns in the traces, and to mark out regions in a long trace that encapsulate sets of primitive operations that represent higher-level application actions. It is robust enough that it can work around discrepancies between training and target traces such as in length and interleaving with other operations. We demonstrate the feasibility of recognizing patterns based on a small sampling of the trace, enabling faster trace analysis. Preliminary experiments show that the method is capable of learning accurate profile models on live traces in an online setting. We present a detailed evaluation of this methodology in a UNIX environment using NFS traces of selected commonly used applications such as compilations as well as on industrial strength benchmarks such as TPC-C and Postmark, and discuss its capabilities and limitations in the context of the use cases mentioned above.

Register File Energy Optimization for Snooping Based Clustered VLIW Architectures

Frequent accesses to the register file make it one of the major sources of energy consumption in ILP architectures. The large number of functional units connected to a large unified register file in VLIW architectures make power dissipation in the register file even worse because of the need for a large number of ports. High power dissipation in a relatively smaller area occupied by a register file leads to a high power density in the register file and makes it one of the prime hot-spots. This makes it highly susceptible to the possibility of a catastrophic heatstroke. This in turn impacts the performance and cost because of the need for periodic cool down and sophisticated packaging and cooling techniques respectively. Clustered VLIW architectures partition the register file among clusters of functional units and reduce the number of ports required thereby reducing the power dissipation. However, we observe that the aggregate accesses to register files in clustered VLIW architectures (and associated energy consumption) become very high compared to the centralized VLIW architectures and this can be attributed to a large number of explicit inter-cluster communications. Snooping based clustered VLIW architectures provide very limited but very fast way of inter-cluster communication by allowing some of the functional units to directly read some of the operands from the register file of some of the other clusters. In this paper, we propose instruction scheduling algorithms that exploit the limited snooping capability to reduce the register file energy consumption on an average by 12% and 18% and improve the overall performance by 5% and 11% for a 2-clustered and a 4-clustered machine respectively, over an earlier state-of-the-art clustered scheduling algorithm when evaluated in the context of snooping based clustered VLIW architectures.

Aggregate download throughput for TCP-controlled long file transfers in a WLAN with multiple STA-AP association rates

We consider several WLAN stations associated at rates r(1), r(2), ... r(k) with an Access Point. Each station (STA) is downloading a long file from a local server, located on the LAN to which the Access Point (AP) is attached, using TCP. We assume that a TCP ACK will be produced after the reception of d packets at an STA. We model these simultaneous TCP-controlled transfers using a semi-Markov process. Our analytical approach leads to a procedure to compute aggregate download, as well as per-STA throughputs, numerically, and the results match simulations very well. (C) 2012 Elsevier B.V. All rights reserved.

Static analysis for checking data format compatibility of programs

Large software systems are developed by composing multiple programs. If the programs manip-ulate and exchange complex data, such as network packets or files, it is essential to establish that they follow compatible data formats. Most of the complexity of data formats is associated with the headers. In this paper, we address compatibility of programs operating over headers of network packets, files, images, etc. As format specifications are rarely available, we infer the format associated with headers by a program as a set of guarded layouts. In terms of these formats, we define and check compatibility of (a) producer-consumer programs and (b) different versions of producer (or consumer) programs. A compatible producer-consumer pair is free of type mismatches and logical incompatibilities such as the consumer rejecting valid outputs gen-erated by the producer. A backward compatible producer (resp. consumer) is guaranteed to be compatible with consumers (resp. producers) that were compatible with its older version. With our prototype tool, we identified 5 known bugs and 1 potential bug in (a) sender-receiver modules of Linux network drivers of 3 vendors and (b) different versions of a TIFF image library.

Structure, dynamics and thermodynamics of single-file water under confinement: effects of polarizability of water molecules

Various structural, dynamic and thermodynamic properties of water molecules confined in single-wall carbon nanotubes (CNTs) are investigated using both polarizable and non-polarizable water models. The inclusion of polarizability quantitatively affects the nature of hydrogen bonding, which governs many properties of confined water molecules. Polarizable water leads to tighter hydrogen bonding and makes the distance between neighboring water molecules shorter than that for non-polarizable water. Stronger hydrogen bonding also decreases the rotational entropy and makes the diffusion constant smaller than in TIP3P and TIP3PM water models. The reorientational dynamics of the water molecules is governed by a jump mechanism, the barrier for the jump being highest for the polarizable water model. Our results highlight the role of polarizability in governing the dynamics of confined water and demonstrate that the inclusion of polarizability is necessary to obtain agreement with the results of ab initio simulations for the distributions of waiting and jump times. The SPC/E water model is found to predict various water properties in close agreement with the results of polarizable water models with much lower computational costs.

First demonstration on the non-transparency of FWM and its application of 40 Gbit/s all-optical CSRZ-to-RZ format conversion

We report first experimental demonstration on the non-transparent characteristic of FWM using NRZ-DPSK, RZ-DPSK, CSRZ-DPSK, and CSRZ signals. One potential non-transparency application of 40Gbit/s CSRZ-to-RZ format conversion is experimentally demonstrated. © 2008 IEEE.

Metadata Federation of PICES Member Countries

(Document pdf contains 193 pages) Executive Summary (pdf, < 0.1 Mb) 1. Introduction (pdf, 0.2 Mb) 1.1 Data sharing, international boundaries and large marine ecosystems 2. Objectives (pdf, 0.3 Mb) 3. Background (pdf, < 0.1 Mb) 3.1 North Pacific Ecosystem Metadatabase 3.2 First federation effort: NPEM and the Korea Oceanographic Data Center 3.2 Continuing effort: Adding Japan’s Marine Information Research Center 4. Metadata Standards (pdf, < 0.1 Mb) 4.1 Directory Interchange Format 4.2 Ecological Metadata Language 4.3 Dublin Core 4.3.1. Elements of DC 4.4 Federal Geographic Data Committee 4.5 The ISO 19115 Metadata Standard 4.6 Metadata stylesheets 4.7 Crosswalks 4.8 Tools for creating metadata 5. Communication Protocols (pdf, < 0.1 Mb) 5.1 Z39.50 5.1.1. What does Z39.50 do? 5.1.2. Isite 6. Clearinghouses (pdf, < 0.1 Mb) 7. Methodology (pdf, 0.2 Mb) 7.1 FGDC metadata 7.1.1. Main sections 7.1.2. Supporting sections 7.1.3. Metadata validation 7.2 Getting a copy of Isite 7.3 NSDI Clearinghouse 8. Server Configuration and Technical Issues (pdf, 0.4 Mb) 8.1 Hardware recommendations 8.2 Operating system – Red Hat Linux Fedora 8.3 Web services – Apache HTTP Server version 2.2.3 8.4 Create and validate FGDC-compliant Metadata in XML format 8.5 Obtaining, installing and configuring Isite for UNIX/Linux 8.5.1. Download the appropriate Isite software 8.5.2. Untar the file 8.5.3. Name your database 8.5.4. The zserver.ini file 8.5.5. The sapi.ini file 8.5.6. Indexing metadata 8.5.7. Start the Clearinghouse Server process 8.5.8. Testing the zserver installation 8.6 Registering with NSDI Clearinghouse 8.7 Security issues 9. Search Tutorial and Examples (pdf, 1 Mb) 9.1 Legacy NSDI Clearinghouse search interface 9.2 New GeoNetwork search interface 10. Challenges (pdf, < 0.1 Mb) 11. Emerging Standards (pdf, < 0.1 Mb) 12. Future Activity (pdf, < 0.1 Mb) 13. Acknowledgments (pdf, < 0.1 Mb) 14. References (pdf, < 0.1 Mb) 15. Acronyms (pdf, < 0.1 Mb) 16. Appendices 16.1. KODC-NPEM meeting agendas and minutes (pdf, < 0.1 Mb) 16.1.1. Seattle meeting agenda, August 22–23, 2005 16.1.2. Seattle meeting minutes, August 22–23, 2005 16.1.3. Busan meeting agenda, October 10–11, 2005 16.1.4. Busan meeting minutes, October 10–11, 2005 16.2. MIRC-NPEM meeting agendas and minutes (pdf, < 0.1 Mb) 16.2.1. Seattle Meeting agenda, August 14-15, 2006 16.2.2. Seattle meeting minutes, August 14–15, 2006 16.2.3. Tokyo meeting agenda, October 19–20, 2006 16.2.4. Tokyo, meeting minutes, October 19–20, 2006 16.3. XML stylesheet conversion crosswalks (pdf, < 0.1 Mb) 16.3.1. FGDCI to DIF stylesheet converter 16.3.2. DIF to FGDCI stylesheet converter 16.3.3. String-modified stylesheet 16.4. FGDC Metadata Standard (pdf, 0.1 Mb) 16.4.1. Overall structure 16.4.2. Section 1: Identification information 16.4.3. Section 2: Data quality information 16.4.4. Section 3: Spatial data organization information 16.4.5. Section 4: Spatial reference information 16.4.6. Section 5: Entity and attribute information 16.4.7. Section 6: Distribution information 16.4.8. Section 7: Metadata reference information 16.4.9. Sections 8, 9 and 10: Citation information, time period information, and contact information 16.5. Images of the Isite server directory structure and the files contained in each subdirectory after Isite installation (pdf, 0.2 Mb) 16.6 Listing of NPEM’s Isite configuration files (pdf, < 0.1 Mb) 16.6.1. zserver.ini 16.6.2. sapi.ini 16.7 Java program to extract records from the NPEM metadatabase and write one XML file for each record (pdf, < 0.1 Mb) 16.8 Java program to execute the metadata extraction program (pdf, < 0.1 Mb) A1 Addendum 1: Instructions for Isite for Windows (pdf, 0.6 Mb) A2 Addendum 2: Instructions for Isite for Windows ADHOST (pdf, 0.3 Mb)

PAnalyzer: A software tool for protein inference in shotgun proteomics

Background Protein inference from peptide identifications in shotgun proteomics must deal with ambiguities that arise due to the presence of peptides shared between different proteins, which is common in higher eukaryotes. Recently data independent acquisition (DIA) approaches have emerged as an alternative to the traditional data dependent acquisition (DDA) in shotgun proteomics experiments. MSE is the term used to name one of the DIA approaches used in QTOF instruments. MSE data require specialized software to process acquired spectra and to perform peptide and protein identifications. However the software available at the moment does not group the identified proteins in a transparent way by taking into account peptide evidence categories. Furthermore the inspection, comparison and report of the obtained results require tedious manual intervention. Here we report a software tool to address these limitations for MSE data. Results In this paper we present PAnalyzer, a software tool focused on the protein inference process of shotgun proteomics. Our approach considers all the identified proteins and groups them when necessary indicating their confidence using different evidence categories. PAnalyzer can read protein identification files in the XML output format of the ProteinLynx Global Server (PLGS) software provided by Waters Corporation for their MSE data, and also in the mzIdentML format recently standardized by HUPO-PSI. Multiple files can also be read simultaneously and are considered as technical replicates. Results are saved to CSV, HTML and mzIdentML (in the case of a single mzIdentML input file) files. An MSE analysis of a real sample is presented to compare the results of PAnalyzer and ProteinLynx Global Server. Conclusions We present a software tool to deal with the ambiguities that arise in the protein inference process. Key contributions are support for MSE data analysis by ProteinLynx Global Server and technical replicates integration. PAnalyzer is an easy to use multiplatform and free software tool.

Query-by-Example Spoken Term Detection ALBAYZIN 2012 evaluation: overview, systems, results, and discussion

Query-by-Example Spoken Term Detection (QbE STD) aims at retrieving data from a speech data repository given an acoustic query containing the term of interest as input. Nowadays, it has been receiving much interest due to the high volume of information stored in audio or audiovisual format. QbE STD differs from automatic speech recognition (ASR) and keyword spotting (KWS)/spoken term detection (STD) since ASR is interested in all the terms/words that appear in the speech signal and KWS/STD relies on a textual transcription of the search term to retrieve the speech data. This paper presents the systems submitted to the ALBAYZIN 2012 QbE STD evaluation held as a part of ALBAYZIN 2012 evaluation campaign within the context of the IberSPEECH 2012 Conference(a). The evaluation consists of retrieving the speech files that contain the input queries, indicating their start and end timestamps within the appropriate speech file. Evaluation is conducted on a Spanish spontaneous speech database containing a set of talks from MAVIR workshops(b), which amount at about 7 h of speech in total. We present the database metric systems submitted along with all results and some discussion. Four different research groups took part in the evaluation. Evaluation results show the difficulty of this task and the limited performance indicates there is still a lot of room for improvement. The best result is achieved by a dynamic time warping-based search over Gaussian posteriorgrams/posterior phoneme probabilities. This paper also compares the systems aiming at establishing the best technique dealing with that difficult task and looking for defining promising directions for this relatively novel task.