Searching for authors named "Apostolos Gerasoulis" – sorted by Relevance.
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List Scheduling with and without Communication Delays
- Empirical results have shown that the classical critical path (CP) list scheduling heuristic for task graphs is a fast and practical heuristic when communication cost is zero. In the first part of this paper we study the theoretical properties of the CP heuristic that lead to near optimum performanc
- Cited by 34 (7 self) – Add To MetaCart
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A Parallel Programming Tool for Scheduling on Distributed Memory Multiprocessors
- PYRROS is a tool for scheduling and parallel code generation for distributed memory message passing architectures [35]. In this paper, we discuss several compile-time optimization techniques used in PYRROS. The scheduling part of PYRROS optimizes both data and program mapping so that the parallel ti
- Cited by 8 (1 self) – Add To MetaCart
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Scheduling Program Task Graphs on MIMD Architectures
- Scheduling is a mapping of parallel tasks onto a set of physical processors and a determination of the starting time of each task. In this paper, we discuss several static scheduling techniques used for distributed memory architectures. We also give an overview of a software system PYRROS [38] that
- Cited by 5 (1 self) – Add To MetaCart
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PYRROS: Static Task Scheduling and Code Generation for Message Passing Multiprocessors
- We describe a parallel programming tool for scheduling static task graphs and generating the appropriate target code for message passing MIMD architectures. The computational complexity of the system is almost linear to the size of the task graph and preliminary experiments show performance comparab
- Cited by 85 (23 self) – Add To MetaCart
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A Fast Static Scheduling Algorithm for DAGs on an Unbounded Number of Processors
- Scheduling parallel tasks on an unbounded number of completely connected processors when communication overhead is taken into account is NP-complete. Assuming that task duplication is not allowed, we propose a fast heuristic algorithm, called the dominant sequence clustering algorithm (DSC), for thi
- Cited by 26 (3 self) – Add To MetaCart
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DSC: Scheduling Parallel Tasks on an Unbounded Number of Processors
- We present a low complexity heuristic named the Dominant Sequence Clustering algorithm (DSC) for scheduling parallel tasks on an unbounded number of completely connected processors. The performance of DSC is comparable or even better on average than many other higher complexity algorithms. We assume
- Cited by 134 (10 self) – Add To MetaCart
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On The Granularity And Clustering Of Directed Acyclic Task Graphs
- Clustering has been used as a compile time pre-processing step in the scheduling of task graphs on parallel architectures. A special case of the clustering problem arises in scheduling an unbounded number of completely connected processors. Using a generalization of Stone's granularity definition, t
- Cited by 91 (21 self) – Add To MetaCart
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A Scheduling Approach to Parallel Harmonic Balance Simulation
- . Rather than approach the parallelization of the harmonic balance simulation method numerically, a novel scheduling-oriented approach is described. The technique leverages circuit substructure to expose potential parallelism in the form of a directed, acyclic graph (dag) of computations. This dag i
- Cited by 1 (0 self) – Add To MetaCart
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Mapping Iterative Task Graphs on Distributed Memory Machines
- This paper addresses the problem of scheduling iterative task graphs on distributed memory architectures with nonzero communication overhead. The proposed algorithm incorporates techniques of software pipelining, graph unfolding and directed acyclic graph scheduling. The goal of optimization is to m
- Cited by 4 (0 self) – Add To MetaCart
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Integrating Software Pipelining and Graph Scheduling for Iterative Scientific Computations
- . Graph scheduling has been shown effective for solving irregular problems represented as directed acyclic graphs(DAGs) on distributed memory systems. Many scientific applications can also be modeled as iterative task graphs(ITGs). In this paper, we model the SOR computation for solving sparse matri
- Cited by 1 (1 self) – Add To MetaCart

