Real-time transactions, in addition to preserving consistency of the database as in traditional transactions, have to meet the deadlines. Scheduling real-time transactions in parallel database systems has not received...
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Real-time transactions, in addition to preserving consistency of the database as in traditional transactions, have to meet the deadlines. Scheduling real-time transactions in parallel database systems has not received much attention. This paper focuses on real-time transaction scheduling in shared-nothing parallel database systems. We evaluate the performance of a new priority-based scheduling policy, in which all scheduling decisions are made locally by each node. In contrast, several other algorithms, proposed for the distributed systems, require communication among the nodes to globally synchronize their local block and abort decisions. Such synchronization can deteriorate performance as real-time transactions will have to meet deadlines. We use miss ratio as the performance metric and show that, in general, the new policy provides a superior performance for the workload and system parameters considered in this study.
Networks of workstations (NOWs) are cost-effective alternatives to multiprocessor systems. Recently, NOWs have been proposed for parallel query processing. Idle CPU cycles of workstations in a NOW-based system can be ...
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Networks of workstations (NOWs) are cost-effective alternatives to multiprocessor systems. Recently, NOWs have been proposed for parallel query processing. Idle CPU cycles of workstations in a NOW-based system can be used to process database query operations. We report on the performance of the hierarchical architecture for parallel query processing on a NOW. We have implemented the hierarchical architecture using PVM on a Pentium-based NOW. The experimental results reported suggest that the hierarchical architecture is successful in achieving good scale-ups and speedups indicating that the idle processor cycles are effectively used for query processing. The hierarchical system can also handle both light and heavy workloads in a load sharing fashion. Our results also suggest that the performance is sensitive to the minimum fragmentation size (chunk size) for partial operations and the structure of queries.
Processor scheduling policies for distributed memory systems can be divided into space sharing or time sharing policies. In space sharing, the set of processors in the system is partitioned and each partition is assig...
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Processor scheduling policies for distributed memory systems can be divided into space sharing or time sharing policies. In space sharing, the set of processors in the system is partitioned and each partition is assigned for the exclusive use of a job. In time sharing policies, on the other hand, none of the processors is given exclusively to jobs; instead, several jobs share the processors (for example, in a round robin fashion). There are advantages and disadvantages associated with each type of policy. Typically, space sharing policies are good at low to moderate system loads and when job parallelism does not vary much. However, at high system loads and widely varying job parallelism, time sharing policies provide a better performance. We propose a new policy that is based on a hierarchical organization that incorporates the merits of these two types of policies. The new policy is a hybrid policy that uses both space sharing as well as time sharing to achieve better performance. We demonstrate that, at most system loads of interest, the proposed policy outperforms both space sharing and time sharing policies by a wide margin.
This paper describes the implementation of transmission-line matrix (TLM) method algorithms on a massively parallel computer (DECmpp 12000), the technique of distributedcomputing in the UNIX environment, and the comb...
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This paper describes the implementation of transmission-line matrix (TLM) method algorithms on a massively parallel computer (DECmpp 12000), the technique of distributedcomputing in the UNIX environment, and the combination of TLM analysis with Prony's method as well as with autoregressive moving average (ARMA) digital signal processing for electromagnetic field modelling. By combining these advanced computation techniques, typical electromagnetic field modelling of microwave structures by TLM analysis can be accelerated by a few orders of magnitude.
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