5,407 research outputs found

    Designing a scalable dynamic load -balancing algorithm for pipelined single program multiple data applications on a non-dedicated heterogeneous network of workstations

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    Dynamic load balancing strategies have been shown to be the most critical part of an efficient implementation of various applications on large distributed computing systems. The need for dynamic load balancing strategies increases when the underlying hardware is a non-dedicated heterogeneous network of workstations (HNOW). This research focuses on the single program multiple data (SPMD) programming model as it has been extensively used in parallel programming for its simplicity and scalability in terms of computational power and memory size.;This dissertation formally defines and addresses the problem of designing a scalable dynamic load-balancing algorithm for pipelined SPMD applications on non-dedicated HNOW. During this process, the HNOW parameters, SPMD application characteristics, and load-balancing performance parameters are identified.;The dissertation presents a taxonomy that categorizes general load balancing algorithms and a methodology that facilitates creating new algorithms that can harness the HNOW computing power and still preserve the scalability of the SPMD application.;The dissertation devises a new algorithm, DLAH (Dynamic Load-balancing Algorithm for HNOW). DLAH is based on a modified diffusion technique, which incorporates the HNOW parameters. Analytical performance bound for the worst-case scenario of the diffusion technique has been derived.;The dissertation develops and utilizes an HNOW simulation model to conduct extensive simulations. These simulations were used to validate DLAH and compare its performance to related dynamic algorithms. The simulations results show that DLAH algorithm is scalable and performs well for both homogeneous and heterogeneous networks. Detailed sensitivity analysis was conducted to study the effects of key parameters on performance

    Computing in the RAIN: a reliable array of independent nodes

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    The RAIN project is a research collaboration between Caltech and NASA-JPL on distributed computing and data-storage systems for future spaceborne missions. The goal of the project is to identify and develop key building blocks for reliable distributed systems built with inexpensive off-the-shelf components. The RAIN platform consists of a heterogeneous cluster of computing and/or storage nodes connected via multiple interfaces to networks configured in fault-tolerant topologies. The RAIN software components run in conjunction with operating system services and standard network protocols. Through software-implemented fault tolerance, the system tolerates multiple node, link, and switch failures, with no single point of failure. The RAIN-technology has been transferred to Rainfinity, a start-up company focusing on creating clustered solutions for improving the performance and availability of Internet data centers. In this paper, we describe the following contributions: 1) fault-tolerant interconnect topologies and communication protocols providing consistent error reporting of link failures, 2) fault management techniques based on group membership, and 3) data storage schemes based on computationally efficient error-control codes. We present several proof-of-concept applications: a highly-available video server, a highly-available Web server, and a distributed checkpointing system. Also, we describe a commercial product, Rainwall, built with the RAIN technology

    The Raincore Distributed Session Service for Networking Elements

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    Motivated by the explosive growth of the Internet, we study efficient and fault-tolerant distributed session layer protocols for networking elements. These protocols are designed to enable a network cluster to share the state information necessary for balancing network traffic and computation load among a group of networking elements. In addition, in the presence of failures, they allow network traffic to fail-over from failed networking elements to healthy ones. To maximize the overall network throughput of the networking cluster, we assume a unicast communication medium for these protocols. The Raincore Distributed Session Service is based on a fault-tolerant token protocol, and provides group membership, reliable multicast and mutual exclusion services in a networking environment. We show that this service provides atomic reliable multicast with consistent ordering. We also show that Raincore token protocol consumes less overhead than a broadcast-based protocol in this environment in terms of CPU task-switching. The Raincore technology was transferred to Rainfinity, a startup company that is focusing on software for Internet reliability and performance. Rainwall, Rainfinity’s first product, was developed using the Raincore Distributed Session Service. We present initial performance results of the Rainwall product that validates our design assumptions and goals

    CRAUL: Compiler and Run-Time Integration for Adaptation under Load

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