An end-to-end Web services-based infrastructure for biomedical applications

Krishnan, Sriram; Baldridge, Kim K.; Greenberg, Joshua I.; Stearn, Brent; Bhatia, Karan

doi:10.1109/grid.2005.1542727

Cited by 20 publications

(14 citation statements)

References 14 publications

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“…In many XML datasets, the same type of element is repeated multiple times, corresponding to a large array of structs used by application programmers. For example, in a Biomedical application [25] that we used in our experiments, an atom element structure is repeated thousands of times. As expected, values within the atom varied each time.…”

Section: Research Challenges Addressed In This Papermentioning

confidence: 99%

“…The XML files in the protein sequence database are hundreds of megabytes in size and the overall application turn-around time is significantly affected if these datasets are not processed efficiently. Other examples of XML usage include Workflow documents [2,8], Event Streams [20], WS-Security Documents [19], and BioMedical Applications [25].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Cache Performance Optimization for Processing XML-Based Application Data on Multi-core Processors

Bhowmik

Govindaraju

2010

2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing

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There is a critical need to develop new programming paradigms for grid middleware tools and applications to harness the opportunities presented by emerging multi-core processors. Implementations of grid middleware and applications that do not adapt to the programming paradigm when executing on emerging processors can severely impact the overall performance. In this paper we focus on the utilization of the L2 cache, which is a critical shared resource on Chip Multiprocessors. The access pattern of the shared L2 cache, which is dependent on how the application schedules and assigns processing work to each thread, can either enhance or undermine the ability to hide memory latency on a multi-core processor. None of the current grid simulators and emulators provides feedback and fine-grained performance data that is essential for a detailed analysis. In this paper, using the feedback from an emulation framework, we present performance analysis and provide recommendations on how processing threads can be scheduled on multi-core nodes to enhance the performance of a class of grid applications that requires processing of large-scale XML data. In particular, we discuss the gains associated with the use of the adaptations we have made to the Cache-Affinity and Balanced-Set scheduling algorithms to improve L2 cache performance, and hence the overall application execution time.

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Section: Research Challenges Addressed In This Papermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cache Performance Optimization for Processing XML-Based Application Data on Multi-core Processors

Bhowmik

Govindaraju

2010

2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing

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“…One general challenge to build an integrated environment is the integration of data management capabilities across the desktop to the server: the data that an end-user employs is typically on his or her own local machine and used in day-to-day work such as email, writing reports, basic analysis using spreadsheets, or other desktop software. Within the grid, this data can be accessed using high-performance and secure grid protocols such as GridFTP [15]. However, from the desktop (which is outside of the formal grid) the end-user must employ different protocols to upload the data to a repository.…”

Section: Related Workmentioning

confidence: 99%

“…Some services are accessed by web portals, others by commandline tools, still others with custom tools with little commonality. The grid user community has been driving the development of user-friendly tools that resemble familiar environments such as browsers, hence the interest in web portal frameworks [15]. While these web portals do provide a browser-based access mechanism for a variety of grid services, they do not sufficiently integrate the capability of the end-users' desktop or laptop machine.…”

Section: Introductionmentioning

confidence: 99%

Topaz: Extending Firefox to Accommodate the GridFTP Protocol

Zamudio

Catarino

Taufer

et al. 2007

2007 IEEE International Parallel and Distributed Processing Symposium

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“…Service-oriented computing represent a significant step forward in providing a real architecture for writing Gridbased programs ( [6], [7]). In the commercial (and academic) space, Web services are now standard practice in making very complex systems (like Google Maps or Search) callable through a standard application programming interface (API).…”

Section: Introductionmentioning

confidence: 99%

Design and Evaluation of Opal2: A Toolkit for Scientific Software as a Service

Krishnan

Clementi

Ren

et al. 2009

2009 Congress on Services - I

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Abstract-Grid computing provides mechanisms for making large-scale computing environments available to the masses. In recent times, with the advent of Cloud computing, the concepts of Software as a Service (SaaS), where vendors provide key software products as services over the internet that can be accessed by users to perform complex tasks, and Service as Software (SaS), where customizable and repeatable services are packaged as software products that dynamically meet the demands of individual users, have become increasingly popular. Both SaaS and SaS models are highly applicable to scientific software and users alike. Opal2 is a toolkit for wrapping scientific applications as Web services on Grid and cloud computing resources. It provides a mechanism for scientific application developers to expose the functionality of their codes via simple Web service APIs, abstracting out the details of the back-end infrastructure. Services may be combined via customized workflows for specific research areas and distributed as virtual machine images. In this paper, we describe the overall philosophy and architecture of the Opal2 framework, including its new plug-in architecture and data handling capabilities. We analyze its performance in typical cluster and Grid settings, and in a cloud computing environment within virtual machines, using Amazon's Elastic Computing Cloud (EC2).

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An end-to-end Web services-based infrastructure for biomedical applications

Cited by 20 publications

References 14 publications

Cache Performance Optimization for Processing XML-Based Application Data on Multi-core Processors

Cache Performance Optimization for Processing XML-Based Application Data on Multi-core Processors

Topaz: Extending Firefox to Accommodate the GridFTP Protocol

Design and Evaluation of Opal2: A Toolkit for Scientific Software as a Service

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