G. Karypis and V. Kumar, "Multilevel k-way hypergraph partitioning," in Proc. ACM Design Automation Conf., 1999.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....separability based clustering [ESC] 35] modified hyperedge coarsening [MHEC] 31] the performance driven clustering (two level clustering [TLC] 36] or even use the original logical hierarchy for clustering. In our current implementation, we use the FirstChoice (FC) clustering algorithm [37] because it experimentally gives us a better hierarchy for global placement. See results in Section V A2. Initial Placement on the Coarsest Level: After the coarsening phase is complete, at the coarsest level a netlist which is much smaller and can be efficiently placed is obtained. Any ....

....grid can be set to a limit of no more than 20 cells in each bin. 2) Coarsening Schemes Impact on Final Wire Length: We compared different coarsening schemes to study their impact on the final wire length using circuits in BENCHP. Three clustering algorithms are compared: FC clustering algorithm [37], ESC algorithm [35] and MHEC algorithm [31] In the FC algorithm, cells clusters that have the strongest connection are clustered together. ESC exploits more global connectivity information, edge separability, to guide the clustering process. Edge separability is defined as the minimum cutsize ....

G. Karypis and V. Kumar, "Multilevel k-way hypergraph partitioning," in Proc. Design Automation Conf., 1998, pp. 343--348.

....objects legalization big objects legalization Fig. 2. Multi level mixed size placement flow in [12] which will be reviewed in the next subsection. A. Review MPG In MPG, the coarsening is performed by recursively clustering the placeable objects using the FirstChoice (FC) clustering algorithm [13] to build a hierarchy of netlist and placement instances from level L 0 to L 1 , L n .LevelL 0 represents the input netlist and placement instance. Level L n represents the coarsest level where the number of clusters is no less than a user specified number, say 500. The refinement is ....

G. Karypis and V. Kumar, "Multilevel k-way hypergraph partitioning, " in Proc. Design Automation Conf, pp. 343--348, 1998.

.... third class [9, 10, 11] couples the graph domain (nodes and their connections) and logic domain (function perform by each node) The tradeoff of improving the partitioning results is the expensive computational cost [10, 11] Recently, many research works on multi level partitioning are proposed [12, 13, 14, 15]. The general idea behind multi level partitioning is to first cluster the whole problem by some useful algorithms to reduce the size, then apply a well known graph domain partitioner on the coarsened graph to get a good initial solution. The graph is then unclustered and a suitable partitioning ....

....graph to get a good initial solution. The graph is then unclustered and a suitable partitioning refinement algorithm is applied in order to adjust the cut edge between partitions. The quality and the runtime by multi level partitioning are very encouraging. In particular, Karypis and Kumar [15] proposes a particular called hMETIS Kway. It first coarsens the hypergraph, then recursively bisects the graph into kparts, followed by uncoarsening the hypergraph with refinement algorithms. More recent research works [16, 17] in comparison with hMetis Kway, showed that the solution by ....

[Article contains additional citation context not shown here]

G. Karypis and V. Kumar, "Multilevel k-way hypergraph partitioning. ," Proc. 36th ACM/IEEE Design Automation Conference, 1999.

....framework. It includes a coarsening phase which recursively builds coarsening levels and a refinement phase which refines each coarser level representation to obtain a finer level representation. Our coarsening is done by iterative clustering. We select the FirstChoice (FC) clustering algorithm [19] because it experimentally gives us better clustering for coarse placement. Our refinement is done by a simulated annealing (SA) based placement engine which places each cluster in the current level in a placement bin. We choose to use an SA based placement as in [20, 21] for the flexibility of ....

G. Karypis and V. Kumar, "Multilevel k-way hypergraph partitioning," in Proceedings 1998.

....1 2 3 Split to this level Annealing at this level Annealing at this level using 1 level clusters Figure 5: Wirelength change in hierarchical placement 5. RESULTS AND DISCUSSION The proposed snap on placement tool has been implemented in C language on Sun Ultra10 workstation. We use hMetis [11] partitioning package to minimize net cut and use simulated annealing to minimize the wirelength in global placement stage. As the final placer, we use NRG[8] a local improvement tool based on low temperature annealing, flipping, switching neighbors and permutation exchange. Total wirelength is ....

G. Karypis and V. Kumar. "Multilevel k-way Hypergraph Partitioning". In Design Automation Conference, pages 343--348, 1999.

....correct wrong decisions made at higher levels. Our GP does not confine locations of subcircuits. This gives cells more freedom to move to achieve better placement results at each level. In order to reduce runtime, we limit our wirelength optimization searches in a local range. We pick hMetis [5] as the partitioner for Dragon2000 because of its superior quality and friendly user interface. A low temperature simulated annealing is used as the base algorithm to minimize wirelength because it is very easy to implement. The DP phase of Dragon2000 uses a greedy algorithm to perform local ....

G. Karypis and V. Kumar. "Multilevel k-way Hypergraph Partitioning". In Design Automation Conference, pages 343--348, 1999.

....Algorithms for Hypergraph Bipartitioning Andrew E. Caldwell, Andrew B. Kahng and Igor L. Markov UCLA Computer Science Dept. Los Angeles, CA 90095 1596 fcaldwell,abk,imarkovg cs.ucla.edu Abstract Multilevel Fiduccia Mattheyses (MLFM) hypergraph partitioning [3, 22, 24] is a fundamental optimization in VLSI CAD physical design. The leading implementation, hMetis [23] has since 1997 proved itself substantially superior in both runtime and solution quality to even very recent works (e.g. 13, 17, 25] In this work, we present two sets of results: i) new ....

....overhead when there are no terminals (cf. 10] Our second set of contributions is in multilevel partitioning. This algorithm framework entails a clustering of the original hypergraph so that clusters can be partitioned, after which the clustered partitioning solution is refined in many steps [22, 24]. The technique is used, e.g. by the leading hypergraph partitioning tool for large hypergraphs, hMetis [23] hMetis has been successfully applied to VLSI circuits, in data mining and in numerical analysis. However, some of the algorithms critical to the performance of hMetis require non trivial ....

[Article contains additional citation context not shown here]

G. Karypis and V. Kumar, "Multilevel k-way Hypergraph Partitioning", Proc. ACM/IEEE Design Automation Conf., 1999, pp. 343-348.

.... from scientific computations [Hendrickson and Leland, 1994, Karypis and Kumar, 1998b, Walshaw et al. 1997] but their advantages were quickly recognized by the VLSI CAD community, and a number of different multilevel algorithms have been developed [Karypis et al. 1999a, Alpert et al. 1997, Karypis and Kumar, 2000] In this chapter we try to provide an overview of the multilevel paradigm and describe the various algorithms that it uses and why it works. Even though our presentation will be generic, from time to time we will use our experience in developing the hMETIS [Karypis and Kumar, 1998a] hypergraph ....

Karypis, G. and Kumar, V. (2000). Multilevel kway hypergraph partitioning. VLSI Design.

No context found.

G. Karypis and V. Kumar, "Multilevel k-way hypergraph partitioning," in Proc. ACM Design Automation Conf., 1999.

No context found.

G. Karypis and V. Kumar, "Multilevel k-way hypergraph partitioning," in Proceedings 1998.

No context found.

G. Karypis and V. Kumar, "Multilevel k-way hypergraph partitioning," in Proc. ACM Design Automation Conf., 1999.

No context found.

G. Karypis and V. Kumar. "Multilevel k-way Hyper-graph Partitioning". Design Automation Conference (DAC), pp. 343-348, 1999. Capo + Parquet + Capo Our Floorplanning Flow Comparison circuit #nodes #nets HPWL runtime(min) #Hmacros HPWL runtime (min) Overlap HPWL speedup

No context found.

G. Karypis and V. Kumar. "Multilevel k-way Hyper-graph Partitioning". Design Automation Conference (DAC), pp. 343-348, 1999. Capo + Parquet + Capo Our Floorplanning Flow Comparison circuit #nodes #nets HPWL runtime(min) #Hmacros HPWL runtime (min) Overlap HPWL speedup

No context found.

G. Karypis and V. Kumar. "Multilevel k-way Hypergraph Partitioning". In Design Automation Conference, pages3-es 1999.

No context found.

G. Karypis and V. Kumar, "Multilevel k-way Hypergraph Partitioning", Proc. ACM/IEEE Design Automation Conf., 1999, pp. 343-348.

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC