The zero/one multiple knapsack problem and genetic algorithms
SAC '94 Proceedings of the 1994 ACM symposium on Applied computing
Solving the multidimensional multiple-choice knapsack problem by constructing convex hulls
Computers and Operations Research
Fundamenta Informaticae - The Fourth Special Issue on Applications of Concurrency to System Design (ACSD05)
Application Scenarios in Streaming-Oriented Embedded-System Design
IEEE Design & Test
A New Heuristic for Solving the Multichoice Multidimensional Knapsack Problem
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A pareto-algebraic framework for signal power optimization in global routing
Proceedings of the 16th ACM/IEEE international symposium on Low power electronics and design
Proceedings of the Conference on Design, Automation and Test in Europe
A low-overhead heuristic for mixed workload resource partitioning in cluster-based architectures
ARCS'12 Proceedings of the 25th international conference on Architecture of Computing Systems
Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Self-adaptive hybrid dynamic power management for many-core systems
Proceedings of the Conference on Design, Automation and Test in Europe
Mapping on multi/many-core systems: survey of current and emerging trends
Proceedings of the 50th Annual Design Automation Conference
Design-space exploration and runtime resource management for multicores
ACM Transactions on Embedded Computing Systems (TECS) - Special issue on application-specific processors
A fast and scalable multidimensional multiple-choice knapsack heuristic
ACM Transactions on Design Automation of Electronic Systems (TODAES) - Special Section on Networks on Chip: Architecture, Tools, and Methodologies
Agent-based distributed power management for kilo-core processors
Proceedings of the International Conference on Computer-Aided Design
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Modern embedded systems typically contain chip-multiprocessors (CMPs) and support a variety of applications. Applications may run concurrently and can be started and stopped over time. Each application may typically have multiple feasible configurations, trading off quality aspects (energy consumption, audio-visual quality) with resource usage for various types of resources. Overall system quality needs to be guaranteed and optimized at all times. This leads to the need for a run-time management solution that selects an appropriate system configuration from all the application configurations of active applications. This run-time management problem can be phrased as a multi-dimensional multiple-choice knapsack (MMKP) problem. We present a compositional heuristic to solve MMKP, that due to the compositionality is better suited to CMP run-time management than existing heuristics that are all not compositional. Our heuristic outperforms the best-known heuristic to date. The heuristic is parameterized, leading to the additional advantage that it allows to trade off execution time vs. solution quality, and to bound the time needed to compute a solution. The latter makes it particularly well-suited for resource-constrained embedded platforms.