Scheduling with global information in distributed systems (original) (raw)
2000, Proceedings 20th IEEE International Conference on Distributed Computing Systems
One of the major problems faced by the developers of parallel programs is the lack of a clear separation between the programming model and the operating system. In this paper, we present a new methodology to multitask parallel jobs in a message-passing environment and to develop parallel programs that can pave the way to the efficient implementation of a distributed operating system. This methodology is based on three innovative techniques: communication buffering, strobing, and non-blocking, one-sided communication. By leveraging these techniques, we can perform effective optimizations based on the gloabl status of the parallel machine rather than on the limited knowledge available locally to each processor. The advantages of the proposed methodology include higher resource utilization, reduced communication overhead, efficient implementation of flowcontrol strategies and fault-tolerant protocols, accurate performance modeling, and a simplified yet still expressive parallel programming model. Some preliminary experimental results show that this methodology is very effective in increasing the overall performance in the presence of load imbalance and communication intensive workloads.
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