Cumulvs: Providing Fault Toler. Ance, Visualization, and Steer Ing of Parallel Applications

Geist, G.A.; Kohl, James Arthur; Papadopoulos, Philip M.

doi:10.1177/109434209701100305

Cited by 107 publications

(75 citation statements)

References 3 publications

(1 reference statement)

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“…CUMULVS [32] is an infrastructure library that allows a programmer to easily extract data from a running parallel simulation and send the data to a visualization package. CUMULVS includes the capability to steer user-defined parameters in a distributed simulation.…”

Section: Runtime Auto-tunersmentioning

confidence: 99%

Tuning parallel applications in parallel

2009

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Auto-tuning has recently received significant attention from the High Performance Computing community. Most auto-tuning approaches are specialized to work either on specific domains such as dense linear algebra and stencil computations, or only at certain stages of program execution such as compile time and runtime.Real scientific applications, however, demand a cohesive environment that can efficiently provide auto-tuning solutions at all stages of application development and deployment. Towards that end, we describe a unified end-to-end approach to autotuning scientific applications. Our system, Active Harmony, takes a search-based collaborative approach to auto-tuning. Application programmers, library writers and compilers collaborate to describe and export a set of performance related tunable parameters to the Active Harmony system. These parameters define a tun- Active Harmony supports runtime adaptive code-generation and tuning for parameters that require new code (e.g. unroll factors). Effectively, we merge traditional feedback directed optimization and just-in-time compilation. This feature also enables application developers to write applications once and have the autotuner adjust the application behavior automatically when run on new systems. We evaluated our system on multiple large-scale parallel applications and showed that our system can improve the execution time by up to 46% compared to the original version of the program.Finally, we believe that the success of any auto-tuning research depends on how effectively application developers, domain-experts and auto-tuners communicate and work together. To that end, we have developed and released a simple and extensible language that standardizes the parameter space representation. Using this language, developers and researchers can collaborate to export tunable parameters to the tuning frameworks. Relationships (e.g. ordering, dependencies, constraints, ranking) between tunable parameters and search-hints can also be expressed.

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Section: Runtime Auto-tunersmentioning

confidence: 99%

Tuning parallel applications in parallel

2009

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“…Their ''MxN Redistribution'' working group has been dealing with the issues of data redistribution when multiple parallel components are coupled together. The CU-MULVS MxN interface [26] from Oak Ridge National Laboratory, the PAWS environment [8] from Los Alamos National Laboratory and the PARDIS SPMD objects [28] from Indiana University work within the CCA to develop a parallel RPC standard. The main goals of these systems include providing interoperability between different components, building user interfaces for conveying information about the parallel data, developing communication schedules to communicate the data between different components and synchronizing data transfers.…”

Section: Related Workmentioning

confidence: 99%

“…Some of the parallel RPC systems [8,18,21,22,26,[28][29][30]35] are mainly concerned with providing robust and efficient interfaces for the service providers to integrate their parallel applications into the systems, and for the end users to remotely use these parallel services. In these systems the users or the service providers have to provide their own scheduling mechanisms if the resources for end application execution have to be dynamically chosen.…”

Section: Introductionmentioning

confidence: 99%

GrADSolve—a grid-based RPC system for parallel computing with application-level scheduling

Vadhiyar

Dongarra

2004

Journal of Parallel and Distributed Computing

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Although some existing Remote Procedure Call (RPC) systems provide support for remote invocation of parallel applications, these RPC systems lack powerful scheduling methodologies for the dynamic selection of resources for the execution of parallel applications. Some RPC systems support parallel execution of software routines with simple modes of parallelism. Some RPC systems statically choose the configuration of resources for parallel execution even before the parallel routines are invoked remotely by the end user. These policies of the existing systems prevent them from being used for remotely solving computationally intensive parallel applications over dynamic computational Grid environments. In this paper, we discuss a RPC system called GrADSolve that supports execution of parallel applications over Grid resources. In GrADSolve, the resources used for the execution of parallel application are chosen dynamically based on the load characteristics of the resources and the characteristics of the application. Application-level scheduling is employed for taking into account both the application and resource properties. GrADSolve also stages the user's data to the end resources based on the data distribution used by the end application. Finally, GrADSolve allows the users to store execution traces for problem solving and use the traces for subsequent solutions. Experiments are presented to prove that GrADSolve's data staging mechanisms can significantly reduce the overhead associated with data movement in current RPC systems. Results are also presented to demonstrate the usefulness of utilizing the execution traces maintained by GrADSolve for problem solving. r

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“…CUMULVS (Collaborative, User Migration, User Library for Visualization and Steering) [2,3] provides an essential platform for interacting with running simulation programs. With CUMULVS, a scientist can observe the internal state of a simulation while it is running via online visualization, and then can "close the loop" and redirect the course of the simulation using computational steering.…”

Section: Cumulvsmentioning

confidence: 99%

“…This paper describes work to integrate CUMULVS [2,3] into the AVS/Express [4] viewer environment, which provides a framework for data visualization, including both 2D and 3D capabilities. AVS/Express is unique in the way that it allows changes to the application structure and functionality during runtime.…”

Section: Introductionmentioning

confidence: 99%

Integrating CUMULVS into AVS/Express

Wilde

Kohl

Flanery

2002

Lecture Notes in Computer Science

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Abstract. This paper discusses the development of a CUMULVS interface for runtime data visualization using the AVS/Express commercial visualization environment. The CUMULVS (Collaborative, User Migration, User Library for Visualization and Steering) system, developed at Oak Ridge National Laboratory, is an essential platform for interacting with high-performance scientific simulation programs on-the-fly. It provides run-time visualization of data while they are being computed, as well as coordinated computational steering, application-directed checkpointing and fault recovery mechanisms, and rudimentary model coupling functions. CUMULVS primarily consists of two distinct but cooperative libraries -an application library and a viewer library. The application library allows instrumentation of scientific simulations to describe distributed data fields, and the viewer library interacts with this application side to dynamically attach and then extract and assemble sequences of data snapshots for use in front-end visualization tools. A development strategy will be presented for integrating and using CUMULVS in AVS/Express, including discussion of the various objects, modules, macros and user interfaces.

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Cumulvs: Providing Fault Toler. Ance, Visualization, and Steer Ing of Parallel Applications

Cited by 107 publications

References 3 publications

Tuning parallel applications in parallel

Tuning parallel applications in parallel

GrADSolve—a grid-based RPC system for parallel computing with application-level scheduling

Integrating CUMULVS into AVS/Express

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