Making data structures persistent
STOC '86 Proceedings of the eighteenth annual ACM symposium on Theory of computing
Resource allocation problems: algorithmic approaches
Resource allocation problems: algorithmic approaches
Optimal allocation of multiple class resources in computer systems
SIGMETRICS '88 Proceedings of the 1988 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Complexity of scheduling parallel task systems
SIAM Journal on Discrete Mathematics
Percentile finding algorithm for multiple sorted runs
VLDB '89 Proceedings of the 15th international conference on Very large data bases
Knapsack problems: algorithms and computer implementations
Knapsack problems: algorithms and computer implementations
An effective algorithm for parallelizing sort merge joins in the presence of data skew
DPDS '90 Proceedings of the second international symposium on Databases in parallel and distributed systems
Exact and Approximate Algorithms for Scheduling Nonidentical Processors
Journal of the ACM (JACM)
A Fast Selection Algorithm and the Problem of Optimum Distribution of Effort
Journal of the ACM (JACM)
Optimal Buffer Partitioning for the Nested Block Join Algorithm
Proceedings of the Seventh International Conference on Data Engineering
Scheduling and Processor Allocation for Parallel Execution of Multi-Join Queries
Proceedings of the Eighth International Conference on Data Engineering
Approximate algorithms scheduling parallelizable tasks
SPAA '92 Proceedings of the fourth annual ACM symposium on Parallel algorithms and architectures
A Parallel Hash Join Algorithm for Managing Data Skew
IEEE Transactions on Parallel and Distributed Systems
Scheduling parallelizable tasks to minimize average response time
SPAA '94 Proceedings of the sixth annual ACM symposium on Parallel algorithms and architectures
Scheduling multiple queries on a parallel machine
SIGMETRICS '94 Proceedings of the 1994 ACM SIGMETRICS conference on Measurement and modeling of computer systems
A Hierarchical Approach to Parallel Multiquery Scheduling
IEEE Transactions on Parallel and Distributed Systems
Efficient and accurate cost models for parallel query optimization (extended abstract)
PODS '96 Proceedings of the fifteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Scheduling parallel tasks to minimize average response time
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
Scheduling malleable and nonmalleable parallel tasks
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
SAC '97 Proceedings of the 1997 ACM symposium on Applied computing
Parallel Query Scheduling and Optimization with Time- and Space-Shared Resources
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Performance Analysis of Database Systems
Performance Evaluation: Origins and Directions
Parallel Job Scheduling: A Performance Perspective
Performance Evaluation: Origins and Directions
Adaptive time/space sharing with SCOJO
International Journal of High Performance Computing and Networking
Adaptive job scheduling via predictive job resource allocation
JSSPP'06 Proceedings of the 12th international conference on Job scheduling strategies for parallel processing
The solution algorithms for the multiprocessor scheduling with workspan criterion
Expert Systems with Applications: An International Journal
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In this paper we formulate the following natural multiprocessor scheduling problem: Consider a parallel system with P processors. Suppose that there are Ntasks to be scheduled on this system, and that the execution time of each task j &egr; {1,…,N} is a nonincreasing function tj(&bgr;j) of the number of processors &&bgr;j &egr; {1,…,P} allotted to it. The goal is to find, for each task j, an allotment of processors &bgr;j, and, overall, a schedule assigning the tasks to the processors which minimizes the makespan, or latest task completion time. The so-called shelf strategy is commonly used for orthogonal rectangle packing, a related and classic optimization problem. The prime difference between the orthogonal rectangle problem and our own is that in our case the rectangles are, in some sense, malleable: The height of each rectangle is a nonincreasing function of its width. In this paper, we solve our multiprocessor scheduling problem exactly in the context of a shelf-based paradigm. The algorithm we give uses techniques from resource allocation theory and employs a variety of other combinatorial optimization techniques.