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Enregistrement W2061217021 · doi:10.1145/605440.605449

A search-based bump-and-refit approach to incremental routing for ECO applications in FPGAs

2002· article· en· W2061217021 sur OpenAlex

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Notice bibliographique

RevueACM Transactions on Design Automation of Electronic Systems · 2002
Typearticle
Langueen
DomaineEngineering
ThématiqueRadiation Effects in Electronics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésNetlistComputer scienceRouting (electronic design automation)Place and routeProcess (computing)Field-programmable gate arrayPhysical designContext (archaeology)PlacementMultipath routingParallel computingDistributed computingStatic routingEmbedded systemCircuit designRouting protocol

Résumé

récupéré en direct d'OpenAlex

Incremental physical CAD is encountered frequently in the so-called engineering change order (ECO) process in which design changes are made typically late in the design process in order to correct logical and/or technological problems in the circuit. Incremental routing is a significant part of an incremental physical design methodology. Typically after an ECO process, a small portion of the circuit netlist is changed, and in order to capitalize on the enormous resources and time already spent on routing the circuit it is desirable to reroute only the ECO-affected portion of the circuit, while minimizing any routing changes in the much larger unaffected part. Incremental rerouting also needs to be fast and to effectively use available routing resources. In this article, we develop a complete incremental routing methodology for FPGAs using a novel approach called bump and refit (B&R). The basic B&R idea (which was originally proposed in Dutt et al. [1999] in the much simpler context of extending some nets by a segment for the purpose of fault tolerance) in our algorithms is to rearrange some portions of some existing nets on other tracks within their current channels in order to find valid routings for the new/modified nets without requiring any extra routing resources and with little effect on the electrical properties of existing nets. Here we significantly extend the B&R concept to global and detailed incremental routing for FPGAs with complex switchboxes (SBox's) such as those in Lucent's ORCA and Xilinx's Virtex series. We introduce new concepts such as a B&R cost in global routing and the optimal subnet set to relocate for each bumped net (determined using an efficient dynamic programming formulation). We developed optimal and near-optimal algorithms (called Subsec_B&R and Subnet_B&R, respectively) to find incremental routing solutions using the B&R paradigm in complex FPGAs (e.g., Lucent's ORCA FPGA) with <i>i</i>-to-<i>j</i> SBox's, as well as an optimal version Fullnet_B&R for the VPR architecture from the University of Toronto using the simpler <i>i</i>-to-<i>i</i> SBox's. We compared our algorithms (simply called B&R when no distinction needs to be made between our versions) to two recent incremental routing techniques, Standard (Std) and Rip-up&Reroute (R&R), and to Lucent's A_PAR routing tool and the University of Toronto's VPR router used in complete rerouting modes. Experimental results for the ORCA show that B&R is 10 to 20 times faster than complete rerouting using A_PAR, and that B&R is also nearly 27% faster and yields new nets with nearly 10% smaller lengths compared to previous incremental routers. Furthermore, B&R routers do not change either the lengths or topologies of existing nets, a significant advantage in ECO applications, in contrast to R&R which increases the length of ripped-up nets by an average of 8.75 to 13.6%. Experimental results for the VPR architecture are dominated by the significantly larger (in many cases, orders of magnitude more) number of nets left unrouted by Std and R&R compared to B&R, which highlights the much greater efficacy of B&R-based incremental routing. However, B&R is significantly slower than the other two incremental routers, although on an absolute scale it is quite fast for two of four cases we simulated; in one case, it is about 25 times faster than VPR used in the full rerouting mode. The relative slowness of B&R for the VPR architecture arises from the fact that we used <i>i</i>-to-<i>i</i> SBox's which forces each net to be routed on the same track, thus causing significantly more bumpings and searches for rearranged solutions compared to <i>i</i>-to-<i>j</i> SBox's where a net can be routed on different interconnected tracks to minimize the amount of bumpings (as we did for the ORCA). Since modern FPGAs generally have the latter type of SBox's, B&R would be fast as well as very effective on them.

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Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,961
Score d'incertitude au seuil0,962

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,024
Tête enseignante GPT0,238
Écart entre enseignants0,215 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle