SUMMARYThe 1990s have seen the explosive growth of the Internet and Web-based information sharing and dissemination systems. The Internet is also showing the potential to form a supercomputing resource out of networked computers. Parallel computing on the Internet often works in a machine-centric 'pull' execution model. That is, a coordinator machine maintains a pool of tasks and distributes the tasks to other participants on demand. This paper proposes a novel mobile agent based 'push' methodology from the perspective of applications. In this method, users declare their computation-bound jobs as autonomous agents. The computational agents roam on the Internet to find servers to run. Since the agents can be programmed to satisfy their goals, even if they move and lose contact with their creators, they can survive intermittent or unreliable network connections. During their lifetime, the agents can also move themselves autonomously from one machine to another for load balancing, enhancing data locality, and tolerating faults.We present an agent-oriented programming and resource brokerage infrastructure, TRAVELER, in support of global parallel computing. The TRAVELER provides a mechanism for clients to wrap their parallel applications as mobile agents. The agents are dispatched to a resource broker. The broker forms a parallel virtual machine atop available servers to execute the agents. TRAVELER relies on an integrated distributed shared array runtime system to support inter-agent communication and synchronization on clusters of servers. We demonstrate the feasibility of the TRAVELER in parallel sorting and LU factorization problems.
This paper proposes a Java-based mobile agent infrastructure, TRAVELER, to support wide area parallel applications. Unlike other meta-computing systems, TRAVELER allows users to dispatch their compute-intensive jobs as mobile agents via a resource broker. The broker forms a parallel virtual machine atop servers to execute the agents. Since the agents can be programmed to satisfy their goals, even if they move and lose contact with their creators, they can survive intermittent or unreliable network connection. During their lifetime, the agents can also move themselves autonomously from one machine to another for load balancing, enhancing data locality, and tolerating faults. TRAVELER relies on an integrated distributed shared array runtime system in support of agent communications on clusters of servers. We demonstrated the feasibility of the TRAVELER in LU factorization problems.
Distributed Shared Arrays (DSA) is a distributed virtual machine that supports Java-compliant multithreaded programming with mobility support for system reconfiguration in distributed environments. The DSA programming model allows programmers to explicitly control data distribution so as to take advantage of the deep memory hierarchy, while relieving them from error-prone orchestration of communication and synchronization at run-time. The DSA system is developed as an integral component of mobility support middleware for Grid computing so that DSA-based virtual machines can be reconfigured to adapt to the varying resource supplies or demand over the course of a computation. The DSA runtime system also features a directorybased cache coherence protocol in support of replication of user-defined sharing granularity and a communication proxy mechanism for reducing network contention. System reconfiguration is achieved by a DSA service migration mechanism, which moves the DSA service and residing computational agents between physical servers for load balancing and fault resilience. We demonstrate the programmability of the model in a number of parallel applications and evaluate its performance by application benchmark programs, in particular, the impact of the coherence granularity and service migration overhead.
This paper presents a Distributed Shared Array runtime system to support Java-compliant multithreaded programming on clusters of symmetric multiprocessors (SMPs). As a hybrid of message passing and shared address space programming models, the DSA programming model allows programmers to explicitly control data distribution so as to take advantage of the deep memory hierarchy, while relieving them from error-prone orchestration of communication and synchronization at run-time. The DSA system is developed as an integral component of mobility support middleware for grid computing so that DSA-based virtual machines can be reconfigured to adapt to the varying resource supplies or demand over the course of a computation. The DSA runtime system also features a directory-based cache coherence protocol in support of replication of user-defined sharing granularity and a communication proxy mechanism for reducing network contention. We demonstrate the programmability of the model in a number of parallel applications and evaluate its performance on a cluster of SMP servers, in particular, the impact of the coherence granularity.
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