‘Split personalities’ for scientific databases: targeting database middleware and interfaces to specific audiences

Pancake, Cherri M.; Newsome, Mark; Hanus, F. J.

doi:10.1016/s0167-739x(99)00042-4

“…Our choice for user interface platform was the ubiquitous web browser, which offers near-universal portability. The interface was developed using an existing web-to-database middleware package, QML (Query Markup Language [5]. QML allowed us to quickly develop prototype implementations of interfaces exploring various search strategies and to support a "drilling-down" style of search.…”

Section: User Interfacementioning

confidence: 99%

A Community Databank for Performance Tracefiles

Ferschweiler

¹

,

Calzarossa

²

,

Pancake

³

et al. 2001

Recent Advances in Parallel Virtual Machine and Message Passing Interface

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Tracefiles provide a convenient record of the behavior of HPC programs, but are not generally archived because of their storage requirements. This has hindered the developers of performance analysis tools, who must create their own tracefile collections in order to test tool functionality and usability. This paper describes a shared databank where members of the HPC community can deposit tracefiles for use in studying the performance characteristics of HPC platforms as well as in tool development activities. We describe how the Tracefile Testbed was designed and implemented to facilitate flexible searching and retrieval of tracefiles. A Web-based interface provides a convenient mechanism for browsing and downloading collections of tracefiles and tracefile segments based on a variety of characteristics. The paper discusses the key implementation challenges. The Tracefile TestbedTracefiles are a valuable source of information about the properties and behavior both of applications and of the systems on which they are executed. They are typically generated by the application programmer as part of the performance tuning process. Our field studies of HPC programmers indicate that many experienced programmers also create suites of simple pseudo-benchmark codes and generate tracefiles to help establish basic performance characteristics when they move to new HPC platforms. The intent in both cases is to help the user better understand and tune his/her applications.The developers of trace-based performance analysis and performance prediction tools (cf. [7,8,10,9,3] ) also generate suites of tracefiles. In this case, the objective is to assist in the process of testing and fine-tuning tool functionality. According to the subjects interviewed in our field studies, tool developers do not often have access to "real" applications for these activities; rather, they construct artificial codes designed to generate tracefiles that will stress the tool's boundary conditions or generate demonstration visualizations.Tool users and developers alike have indicated in several public forums (e.g., Parallel Tools Consortium meetings, BOF sessions at the SC conference, community workshops on parallel debugging and performance tuning tools) that it would be useful to construct a generally accessible testbed for tracefile data. This would make it possible for users to see if tracefiles from related applications can be of use in the design and tuning of their own application. It would also provide a more realistic foundation for testing new performance tools. Further, since tracefiles are typically large and unwieldy to store (the recording of key program events during one application run can generate

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The tracefile testbed - a community repository for identifying and retrieving HPC performance data

Ferschweiler

¹

,

Harrah

²

,

Keon

³

et al.

Proceedings International Conference on Parallel Processing

1

0

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Background and motivationA high-performance computing (HPC) application is characterized by many variables that control its execution and determine its performance. Variables such as algorithm type, problem size, input parameters, programming languages and paradigms, libraries, hardware architecture, etc., can have very significant effects on program behavior. It is important to understand the role played by each variable and the ways they combine to influence the performance achieved, or achievable, by the application.Two approaches are commonly used for the purpose of understanding these effects: performance profiling and performance prediction. Profiling [7,8] captures the behavior of an application by monitoring its execution. Monitoring can be based on hardware counter sampling or it can require the instrumentation of the application's source code or its binary executable. The data produced by monitoring may be analyzed on-the-fly or stored as tracefiles for post-mortem analysis. Many of the tools currently available for HPC performance analysis are based on tracefiles. Examples include:• These techniques attempt to provide estimates of the performance achievable by an application by analyzing its structure and the influences of compiler transformations and the system architecture, using symbolic analysis, simulation, or other model-based methods. Prediction tools often rely directly or indirectly on tracefiles. The data from tracefiles can serve as the basis for constructing or validating the performance model, or can be used directly by the tool to adjust the model to the characteristics of a particular application (e.g., [9]).Tracefiles are typically generated by the application programmer as part of the performance tuning process. Our field studies of HPC programmers indicate that many experienced programmers also create suites of simple pseudo-benchmark codes and generate tracefiles to help establish basic performance characteristics when they

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The Tracefile Testbed: a community repository for identifying and retrieving HPC performance data

Ferschweiler¹,

Harrah²,

Keon³

et al. 2005

IJHPCN

1

0

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Background and motivationA high-performance computing (HPC) application is characterized by many variables that control its execution and determine its performance. Variables such as algorithm type, problem size, input parameters, programming languages and paradigms, libraries, hardware architecture, etc., can have very significant effects on program behavior. It is important to understand the role played by each variable and the ways they combine to influence the performance achieved, or achievable, by the application.Two approaches are commonly used for the purpose of understanding these effects: performance profiling and performance prediction. Profiling [7,8] captures the behavior of an application by monitoring its execution. Monitoring can be based on hardware counter sampling or it can require the instrumentation of the application's source code or its binary executable. The data produced by monitoring may be analyzed on-the-fly or stored as tracefiles for post-mortem analysis. Many of the tools currently available for HPC performance analysis are based on tracefiles. Examples include:• These techniques attempt to provide estimates of the performance achievable by an application by analyzing its structure and the influences of compiler transformations and the system architecture, using symbolic analysis, simulation, or other model-based methods. Prediction tools often rely directly or indirectly on tracefiles. The data from tracefiles can serve as the basis for constructing or validating the performance model, or can be used directly by the tool to adjust the model to the characteristics of a particular application (e.g., [9]).Tracefiles are typically generated by the application programmer as part of the performance tuning process. Our field studies of HPC programmers indicate that many experienced programmers also create suites of simple pseudo-benchmark codes and generate tracefiles to help establish basic performance characteristics when they

show abstract

‘Split personalities’ for scientific databases: targeting database middleware and interfaces to specific audiences

Cited by 3 publications

References 15 publications

A Community Databank for Performance Tracefiles

A Community Databank for Performance Tracefiles

The tracefile testbed - a community repository for identifying and retrieving HPC performance data

The Tracefile Testbed: a community repository for identifying and retrieving HPC performance data

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