Supporting dynamic parallel object arrays

Abstract

We present efficient support for generalized arrays of parallel data driven objects. Array elements are regular C++ objects, and are scattered across the parallel machine. An individual element is addressed by its 'index', which can be an arbitrary object rather than a simple integer. For example, an array index can be a series of numbers, supporting multidimensional sparse arrays; a bit vector, supporting collections of quadtree nodes; or a string. Methods can be invoked on any individual array element from any processor, and the elements can participate in reductions and broadcasts. Individual elements can be created or deleted dynamically at any time. Most importantly, the elements can migrate from processor to processor at any time. We discuss support for message delivery and collective operations in the face of such dynamic behavior. The migration capabilities of array elements have proven extremely useful, for example, in implementing flexible load balancing strategies and for exploiting workstation clusters adaptively. We present the design, an implementation, and performance results. 372O. S. LAWLOR AND L. V. KALÉ is slow and duplicates delivery effort), misdelivered (delivered to the current occupant of that address), or lost (returned to the sender or dropped completely).MPI also uses physical addressing-messages in MPI are sent to a particular process number and tag. Like the postal service, if the computational entity the message is destined for moves, the message will either have to be manually forwarded or (more likely) will be misdelivered or lost. This means computational entities in MPI programs either never move, or can only be moved with a great deal of intricate, error-prone programming effort.While it is easy to deliver messages to a physical address, it is evident that moving objects are difficult to support. We present a simple, well-known solution to this problem-a layer of indirection between objects and physical addresses.Our framework allows an object to be referenced by a globally unique, problem-domain, userassigned logical address called an 'array index'. All communication is via the array index, which allows the object to be migrated in a completely general and user-transparent way.In this paper, we show how to support message delivery, creation, deletion, and migration scalably and efficiently using this logical addressing scheme. We present a solution to the problem of broadcasts and reductions in the presence of ongoing migrations. Finally, we present performance data from several actual applications built using this system. Partition decompositionMany of today's emerging high-end parallel applications are characterized by irregular and dynamic computational structure. These problems demand techniques such as latency hiding and dynamic load balancing to achieve good parallel performance. However, it requires significant programming effort to incorporate these techniques into a parallel program written using the prevalent processor-centric programming model exemplified by MPI.We a...

A Software Framework to Support Adaptive Applications in Distributed/Parallel Computing

“…This allows a resource to be added to the application during the execution: the application simply spawns another herder process on the added resource and then moves some automata objects on the empty process for load balancing. Paper [14], [15] introduce the similar ideas to support the dynamic application reconfiguration based on objects migration. We generalize the above applications as -Adaptive Distributed/Parallel Applications (ADA).…”

“…Charm++ [24], [14] is one of few existing middleware that supports the concept of ADA (based on the notion of Distributed Automata Graphs). It is designed with the goal of enhancing programmer productivity by providing a highlevel abstraction of a parallel program while at the same time delivering good performance.…”

On-line feedback-based automatic resource configuration for distributed applications

“…A traditional parallel application can be rewritten to be adaptive by various methods, such as master-worker processing architecture [10], object graphs [1,15] with dynamic load balancing.…”

On-line automatic resource selection in distributed computing

“…A traditional parallel application can be rewritten to be adaptive by various methods, such as masterworker processing architecture [13], object arrays [14] and dynamic load balancing. Second, this approach requires a middleware to manage resource on-line during execution.…”