Parallelizing a new class of large applications over high-speed networks

Kung, H. T.; Steenkiste, Peter; Gubitoso, Marco Dimas; Khaira, Manpreet

doi:10.1145/109626.109643

Cited by 3 publications

(3 citation statements)

References 12 publications

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“…Use of a network based multicomputer for VLSI simulation is proposed in [7]. In this architecture, a number of existing machines are linked via a high-speed network which utilizes fiber-optic links and crossbar switches (HUBs).…”

Section: Previous Workmentioning

confidence: 99%

A Framework for Distributed VLSI Simulation on a Network of Workstations

Karthik

Abraham

1993

SIMULATION

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A distributed framework for logic simulation is presented. Switch-level simulation has been mapped to a distributed platform using a network of workstations on an Ethernet bus. Model parallelism is used with preprocessing to partition the circuit to be simulated among the processors. The simulation algorithm is decoupled from the communication layers to ensure easy portability. We have proposed a high level pipelining scheme with multiple buffers to overcome the effects of a low bandwidth network. Speedups of up to 4.1 with 5 processors have been obtained for medium sized ISCAS benchmark circuits. The speedups achieved using distributed simulation are very close to that obtained by the same switch-level simulator implemented on a shared memory parallel machine. Novel techniques to improve the performance of distributed simulation have also been implemented on a shared memory parallel machine.

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Section: Previous Workmentioning

confidence: 99%

A Framework for Distributed VLSI Simulation on a Network of Workstations

Karthik

Abraham

1993

SIMULATION

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“…The sequential LA simulation program consists of about 2500 lines of FORTRAN and 300 lines of C codes and a distributed version using send and receive primitives is described in [12]. Computing the particle traces is a two phase process.…”

Section: Simulation Of Air Pollution In Los Angelesmentioning

confidence: 99%

Aroma: language support for distributed objects

Nishikawa

Steenkiste

Proceedings Sixth International Parallel Processing Symposium

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Aroma simplifies the task of parallelizing large applications on multicomputers by providing applications with a shared object space. Aroma supports both traditional monolithic objects and aggregate object that can be partitioned across multiple nodes. Aggregate objects support data parallelism efficiently. An Aroma program consists of tasks that operate on shared objects. Tasks typically execute on the node on which their input data is located, thus minimizing communication. Shared data objects have synchronization properties associated with them, making it possible to parallelize a large class of applications without using explicit locks and condition variables. In this paper, we present and justify the Aroma language features, and give examples of Aroma programs. Aroma has been implemented on the Nectar multicompnter and we give performance results for several applications.

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“…Previous reports [2, 91 describe the problem in more detail. In [9] the effect of static load balancing is shown. In [a], we use dynamic load balancing, but only the particle tracking tasks can be moved.…”

Section: Heterogeneous Task Load Balancingmentioning

confidence: 99%

A general architecture for load balancing in a distributed-memory environment

Nishikawa¹,

Steenkiste²

[1993] Proceedings. The 13th International Conference on Distributed Computing Systems

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The goal of load balancing is to assign to each node a number of tasks proportional to its performance. On distributed-memory machines, it is important to take data dependencies into account when distributing tasks, since they have a big impact on the communication requirements of the distributed application. Many load balancers have been proposed that deal with applications with homogeneous tasks, but applications with heterogeneous tasks have proven to be far more complex to handle. In this paper we present a load balancing architecture that can deal with applications with heterogeneous tasks. The idea is to provide a set of load balancers that are effective for different types of homogeneous tasks, and to allow users to combine these load balancers for applications with heterogeneous tasks. We implemented this architecture on the Nectar multicomputer and we present performance results for several applications with homogeneous and heterogeneous tasks.

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Parallelizing a new class of large applications over high-speed networks

Cited by 3 publications

References 12 publications

A Framework for Distributed VLSI Simulation on a Network of Workstations

A Framework for Distributed VLSI Simulation on a Network of Workstations

Aroma: language support for distributed objects

A general architecture for load balancing in a distributed-memory environment

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