IEEE Transactions on Computers
Heuristic Algorithms for Task Assignment in Distributed Systems
IEEE Transactions on Computers
Scheduling precedence graphs in systems with interprocessor communication times
SIAM Journal on Computing
Automatic determination of grain size for efficient parallel processing
Communications of the ACM - Special issue: multiprocessing
Scheduling parallel program tasks onto arbitrary target machines
Journal of Parallel and Distributed Computing - Special issue: software tools for parallel programming and visualization
Multiprocessor system for realtime robotics applications
Microprocessors & Microsystems
Analysis and evaluation of heuristic methods for static task scheduling
Journal of Parallel and Distributed Computing
Architectures for statically scheduled dataflow
Journal of Parallel and Distributed Computing - Special issue: data-flow processing
IEEE Transactions on Software Engineering
Deterministic Processor Scheduling
ACM Computing Surveys (CSUR)
A comparison of list schedules for parallel processing systems
Communications of the ACM
Operating Systems Theory
A comparative analysis of static parallel schedulers where communication costs are significant
A comparative analysis of static parallel schedulers where communication costs are significant
Performance Evaluation of Scheduling Precedence-Constrained Computations on Message-Passing Systems
IEEE Transactions on Parallel and Distributed Systems
Scheduling optimization through iterative refinement
PACT '95 Proceedings of the IFIP WG10.3 working conference on Parallel architectures and compilation techniques
Dynamic Task Scheduling Using Online Optimization
IEEE Transactions on Parallel and Distributed Systems
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The author studies dynamic scheduling of computational tasks with communication costsusing nonuniform memory access architecture. The computing model assumes that datatransfer can be partitioned into parallel and sequential parts with respect to the taskexecution. A scheduling heuristic, called least-communication (LC), together with atwo-level scheduler is proposed in an attempt to minimize the finish time. The LC selectsthe task that removes the largest amount of remaining data transfer, if no such tasks areavailable the task that has been ready to run at the earliest is selected first. The timecomplexity of LC is O(n/sub 2/). Testing the finish time of LC and first-come first-servedscheduling (FCFS) shows that LC is useful for tasks having moderate granularity andwhose computation and communication requirements vary widely for different data sets.