Evaluating the Kernighan-Lin Heuristic for Hardware/Software Partitioning

Mann, Zoltán Ádám; Orbán, András; Farkas, Viktor

doi:10.2478/v10006-007-0022-3

Cited by 7 publications

(5 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…another path-based HW/SW partitioning was proposed in . In (Mann et al, 2007), the possibilities of applying the Kernighan-Lin algorithm to the HS P problem were evaluated. In (Zhang et al, 2018), the authors proposed an algorithm for multiprocessing embedded systems, the optimization objective is minimizing the critical path which demonstrates the longest path in a DAG graph, the critical path would determine the time required to execute the tasks on the embedded platform, the hardware area is set as a constraint, the proposed algorithm is based on Shuffled Frog Leaping Algorithm and Greedy Algorithm.…”

Section: Related Workmentioning

confidence: 99%

GO Game Inspired Algorithm for Hardware Software Partitioning in Multiprocessor Embedded Systems

Iguider¹,

Bousselam²,

Elissati³

et al. 2019

CIS

View full text Add to dashboard Cite

The codesign is a robust methodology, used in modern embedded systems with the objective of achieving the functional specifications and meeting the non-functional requirements. The most interesting step in the codesing is the process of Hardware/Software Partitioning. The aim is to decide which functionalities of the system should be implemented in hardware (HW) or in software (S W). In this article, a new heuristic algorithm is proposed to simultaneously optimize the hardware area (cost) and the execution time (performance) of a multiprocessor system. The proposed algorithm is inspired from game theory and especially from the GO game. The system is modeled using the DAG graph (Data Acyclic Graph), and two players (HW player and SW player) play in turn and choose a block (functionality) from the graph (system). The HW player has the goal of optimizing the global HW area while the SW player has the objective of minimizing the global execution time. After the game termination, and based on the 0-1 Knapsack algorithm, a step of refinement is used to meet the constraint on the total hardware area or on the overall execution time if a constraint is pre-defined. Experimental results show that the proposed algorithm gives better solutions compared to the Simulated Annealing algorithm and the Genetic Algorithm.

show abstract

Section: Related Workmentioning

confidence: 99%

GO Game Inspired Algorithm for Hardware Software Partitioning in Multiprocessor Embedded Systems

Iguider¹,

Bousselam²,

Elissati³

et al. 2019

CIS

View full text Add to dashboard Cite

show abstract

“…Finding a small balanced cut in a hypergraph is a well-known problem for its numerous applications in VLSI netlist partitioning and other areas [15] [32] [40]. Unfortunately, finding the minimal cut that satisfies a balance constraint is known to be NP-hard [38].…”

Section: Models Of Formula Partitioningmentioning

confidence: 99%

Guiding SAT Solving by Formula Partitioning

Mann

Papp

2017

Int. J. Artif. Intell. Tools

View full text Add to dashboard Cite

When deciding the satisfiability of a Boolean formula, one promising approach is to split the formula into two smaller independent sub-formulas. While many studies report encouraging early results with such methods, the approach is rarely used in state-of-the-art solvers. In this paper, we present a technique that uses formula partitioning to guide the solution of the SAT problem through providing initialization values for the VSIDS heuristic. Our results on a large number of benchmark instances show that the method can notably improve the performance of modern solvers, especially if the time available for solving is short. We also present some findings in the area of hypergraph partitioning, which is used as a tool for our technique.

show abstract

“…Many exact algorithms such as dynamic programming [2], [3], branch-and-bound [4], integer linear programming [5], [6]. Since most formulations of the hardware/software partitioning are NP-hard, the exact algorithms for them have exponential runtimes [7]. A number of heuristic algorithms have been considered for approximately solving the hardware/software partitioning problem in an acceptable time.…”

Section: Introductionmentioning

confidence: 99%

“…A number of heuristic algorithms have been considered for approximately solving the hardware/software partitioning problem in an acceptable time. One of the most effective heuristic algorithms [7], [8] is based on the KernighanLin heuristic [9] for circuit partitioning. The basic idea is to swap nodes between the hardware and software subsets in a way that decreases the objective value.…”

Section: Introductionmentioning

confidence: 99%

An iterative greedy algorithm for hardware/software partitioning

Lin

2013

2013 Ninth International Conference on Natural Computation (ICNC)

View full text Add to dashboard Cite

Hardware/software partitioning is one of the most important problems in hardware/software codesign. This paper proposes an iterative greedy algorithm for solving hardware/software partitioning. The proposed algorithm iteratively refines a solution by a local search method, a destruction method and a construction method. We show computational results on four benchmarks from the literature. Comparisons with a traditional evolutionary algorithm and an algorithm based on artificial immune principles demonstrate the efficacy of the proposed algorithm in terms of solution quality.

show abstract

Evaluating the Kernighan-Lin Heuristic for Hardware/Software Partitioning

Cited by 7 publications

References 45 publications

GO Game Inspired Algorithm for Hardware Software Partitioning in Multiprocessor Embedded Systems

GO Game Inspired Algorithm for Hardware Software Partitioning in Multiprocessor Embedded Systems

Guiding SAT Solving by Formula Partitioning

An iterative greedy algorithm for hardware/software partitioning

Contact Info

Product

Resources

About