Cost minimization of partitions into multiple devices

Kuznar, R.; Brglez, Franc; Kozminski, K.

doi:10.1145/157485.164910

Cited by 59 publications

(36 citation statements)

References 4 publications

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“…But these two objectives are not directly related. This was stated also in [9]. In some cases, it may happen that net with zerogain changes the number of I/Os of block to/from which it is moved.…”

Section: Methods Descriptionmentioning

confidence: 77%

“…We start by mentioning the recursive paradigm used in [9]. The algorithm is composed of k , 1 iterations.…”

Section: Methods Descriptionmentioning

confidence: 99%

“…The mostly referenced works for multi-FPGA partitioning are [9], [10], [11], and [12]. Proposed in [9] method (kway.x) is based on recursive bipartitioning alternating with improvements by calling the FM algorithm ( [4]).…”

Section: Introductionmentioning

confidence: 99%

“…Proposed in [9] method (kway.x) is based on recursive bipartitioning alternating with improvements by calling the FM algorithm ( [4]). In [11], the previous method was extended with functional replication possibilities (implementation program called r + p.0).…”

Section: Introductionmentioning

confidence: 99%

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Iterative improvement based multi-way netlist partitioning for FPGAs

Krupnova¹,

Saucier

1999

Proceedings of the Conference on Design, Automation and Test in Europe

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Section: Methods Descriptionmentioning

confidence: 77%

“…We start by mentioning the recursive paradigm used in [9]. The algorithm is composed of k , 1 iterations.…”

Section: Methods Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Iterative improvement based multi-way netlist partitioning for FPGAs

Krupnova¹,

Saucier

1999

Proceedings of the Conference on Design, Automation and Test in Europe

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“…Multilevel partitioning is a paradigm that can be combined with PROP and SHRINK-PROP to obtain even better results. However, flat partitioners such as PROP and SHRINK-PROP are probably more suitable for complex placement problems, such as those for submicrometer VLSI with multiple objectives and constraint [12], [13], [25], [27].…”

Section: Discussionmentioning

confidence: 99%

A probability-based approach to VLSI circuit partitioning

Dutt¹,

Deng²

33rd Design Automation Conference Proceedings, 1996

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Abstract-Iterative-improvement two-way min-cut partitioning is an important phase in most circuit placement tools, and finds use in many other computer-aided design (CAD) applications. Most iterative improvement techniques for circuit netlists like the Fiduccia-Mattheyses (FM) method compute the gains of nodes using local netlist information that is only concerned with the immediate improvement in the cutset. This can lead to misleading gain information. Krishnamurthy suggested a lookahead (LA) gain calculation method to ameliorate this situation; however, as we show, it leaves room for improvement. We present here a probabilistic gain computation approach called probabilistic partitioner (PROP) that is capable of capturing the future implications of moving a node at the current time. We also propose an extended algorithm SHRINK-PROP that increases the probability of removing recently "perturbed" nets (nets whose nodes have been moved for the first time) from the cutset. Experimental results on medium-to large-size ACM/SIGDA benchmark circuits show that PROP and SHRINK-PROP outperform previous iterative-improvement methods like FM (by about 30% and 37%, respectively) and LA (by about 27% and 34%, respectively). Both PROP and SHRINK-PROP also obtain much better cutsizes than many recent state-of-the-art partitioners like EIG1, WINDOW, MELO, PARABOLI, GFM and GMetis (by 4.5% to 67%). Our empirical timing results reveal that PROP is appreciably faster than most recent techniques. We also obtain results on the more recent ISPD-98 benchmark suite that show similar substantial mincut improvements by PROP and SHRINK-PROP over FM (24% and 31%, respectively). It is also noteworthy that SHRINK-PROP's results are within 2.5% of those obtained by hMetis, one of the best multilevel partitioners. However, the multilevel paradigm is orthogonal to SHRINK-PROP. Further, since it is a "flat" partitioner, it has advantages over hMetis in partition-driven placement applications.Index Terms-Clustering effect, iterative-improvement, min-cut partitioning, probabilistic gain, VLSI circuit.

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