HPCwire: An Open Source Run-Time for Distributed HPC

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March 31, 2006

An Open Source Run-Time for Distributed HPC

by Michael Feldman, Editor, HPCwire

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OpenRTE (www.open-rte.org) is an open source project that is designed to provide a portable distributed computing run-time environment for HPC workloads. Ralph Castain, of Los Alamos National Laboratory, leads the development of this project and has been conducting research in large-scale distributed computing as a research scientist at Colorado State University for some time. HPCwire got a chance to speak with Ralph about OpenRTE. In this Q&A, he describes what it is, how it works, and what it could mean to the HPC community.

HPCwire: What are the origins and goals of OpenRTE?

Castain: OpenRTE began as a sub-project within the Open MPI initiative that is aimed at creating a free, open source, peer-reviewed, production-quality complete MPI-2 implementation. Open MPI strives to provide an extremely high, competitive performance system by directly involving the HPC community with external development and feedback -- vendors, 3rd party researchers, users, etc.

Building an MPI layer capable of meeting those objectives required the development of an equally ambitious run-time environment that would be capable of providing the necessary infrastructure. OpenRTE evolved from that effort. We recognized early on that we had an opportunity to provide an infrastructure that could transparently support extended features for MPI -- something that would transcend the traditional MPI environment of running an application on a single cluster. For example, we could use the infrastructure we were developing to transparently "stitch" together multiple applications, or to extend applications to span multiple clusters.

The goals of OpenRTE therefore became:

(a) Provide a seamless, transparent distributed computing environment that allows users to execute their applications in a single cluster or on multiple clusters, and/or to integrate individual applications together, all without changing their application code. Our current computing environments require that the user recompile their code, and perhaps even make changes in the source code itself, when moving from a cluster to a Grid or some other venue. In addition, connecting multiple applications generally requires that the integration be done at the source code level. Our objective is to make this as transparent as possible. Users should be able to execute the same code on a cluster or a Grid without changes, and be able to connect applications at run-time -- again, without changing the source code.

(b) Create a robust, production-quality platform upon which high-performance computing applications can execute. The run-time must do its job and then get out of the way -- it cannot impact critical timing loops. At the same time, it has to provide a rock-solid foundation (the run-time must never fail; instead, it must provide error messages and, if necessary, gracefully exit) that includes support for response to system faults to enable the computing application to continue executing; and

(c) Create an extensible system based on a component architecture that allows developers to "overload" any OpenRTE function, thus enabling the necessary research to support new enhanced features in a production environment. We recognized up-front that OpenRTE's goals are ambitious, and that, as the research literature demonstrates, there are multiple ways of implementing just about every major functional block in the system. We wanted to create an architecture for OpenRTE that would make it easy for a researcher to replace one of those functional blocks with their own idea on how to implement it -- without that researcher having to write all the rest of the blocks required to make a system operational. Thus, a researcher interested in distributed data storage -- such as is found in the OpenRTE's registry -- can "overload" that functional block with their own implementation, and then test the results in a production environment without having to write code to launch and monitor processes.

HPCwire: Can you describe the architecture of OpenRTE and how it works?

Castain: OpenRTE consists of four major subsystem blocks, all built upon a component architecture. Sitting at the core of the system is a publish/subscribe general purpose registry (GPR) that is used to synchronize events across the system. The GPR is designed to asynchronously notify subscribers of events such as data being entered or changed in the registry, and to transmit along with that notification whatever data the subscriber requests. This is the underlying mechanism supporting, among other things, the exchange of communication connection data among processes.

Subsystems in the Resource Management block make heavy use of the GPR to discover computing resources that may be available to the user, allocate those resources for use by a particular application, map the application's processes to specific allocated resources, and launch the processes to begin execution. In this block, the GPR is primarily used as an intermediate storage medium -- the resource discovery service, for example, places entries on the registry with information identifying the resources it has found, their state of operation, how much of their capability, if any, has been reserved for this user, etc. This information is then used by the allocation service to determine if additional resources need to be requested for the user and from where they might come. The mapper service then takes the allocated resources and maps processes to them so that the launch service can start the application.

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