498 research outputs found

    Lexicographic path searches for FPGA routing

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    This dissertation reports on studies of the application of lexicographic graph searches to solve problems in FPGA detailed routing. Our contributions include the derivation of iteration limits for scalar implementations of negotiation congestion for standard floating point types and the identification of pathological cases for path choice. In the study of the routability-driven detailed FPGA routing problem, we show universal detailed routability is NP-complete based on a related proof by Lee and Wong. We describe the design of a lexicographic composition operator of totally-ordered monoids as path cost metrics and show its optimality under an adapted A* search. Our new router, CornNC, based on lexicographic composition of congestion and wirelength, established a new minimum track count for the FPGA Place and Route Challenge. For the problem of long-path timing-driven FPGA detailed routing, we show that long-path budgeted detailed routability is NP-complete by reduction to universal detailed routability. We generalise the lexicographic composition to any finite length and verify its optimality under A* search. The application of the timing budget solution of Ghiasi et al. is used to solve the long-path timing budget problem for FPGA connections. Our delay-clamped spiral lexicographic composition design, SpiralRoute, ensures connection based budgets are always met, thus achieves timing closure when it successfully routes. For 113 test routing instances derived from standard benchmarks, SpiralRoute found 13 routable instances with timing closure that were unroutable by a scalar negotiated congestion router and achieved timing closure in another 27 cases when the scalar router did not, at the expense of increased runtime. We also study techniques to improve SpiralRoute runtimes, including a data structure of a trie augmented by data stacks for minimum element retrieval, and the technique of step tomonoid elimination in reducing the retrieval depth in a trie of stacks structure

    Circuit delay optimization by buffering the logic gates

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    Avec la miniaturisation actuelle, les circuits démontrent de plus en plus l'importance des délais d'interconnexion. Afin de réduire ce délai, l'insertion de tampons doit être effectuée durant la synthèse logique et la synthèse physique. Cette activité d'optimisation est souvent basée sur la programmation dynamique. Dans ce mémoire, la technique branch-and-bound est utilisé et le problème pour le cas spécifique d'arbres de tampons équilibrés est résolu, où toutes les charges ont un temps requis et une capacité identique. Une analyse mathématique est faite pour tenir compte d'une variété de questions de conception telles que la topologie, la bibliothèque de tampons et le changement de phase en présence d'inverseur. En combinant la programmation dynamique et les techniques branch-and-bound, une méthode hybride est présentée qui améliore le temps d'exécution tout en conservant une utilisation de mémoire raisonnable. Les concepts mathématiques et algorithmiques fondamentaux utilisés dans ce mémoire peuvent être employés pour généraliser la méthode proposée pour un ensemble de charges avec des capacités et des temps requis différents

    Submicron Systems Architecture Project: Semiannual Technial Report

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    New FPGA design tools and architectures

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    Algorithmic techniques for nanometer VLSI design and manufacturing closure

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    As Very Large Scale Integration (VLSI) technology moves to the nanoscale regime, design and manufacturing closure becomes very difficult to achieve due to increasing chip and power density. Imperfections due to process, voltage and temperature variations aggravate the problem. Uncertainty in electrical characteristic of individual device and wire may cause significant performance deviations or even functional failures. These impose tremendous challenges to the continuation of Moore's law as well as the growth of semiconductor industry. Efforts are needed in both deterministic design stage and variation-aware design stage. This research proposes various innovative algorithms to address both stages for obtaining a design with high frequency, low power and high robustness. For deterministic optimizations, new buffer insertion and gate sizing techniques are proposed. For variation-aware optimizations, new lithography-driven and post-silicon tuning-driven design techniques are proposed. For buffer insertion, a new slew buffering formulation is presented and is proved to be NP-hard. Despite this, a highly efficient algorithm which runs > 90x faster than the best alternatives is proposed. The algorithm is also extended to handle continuous buffer locations and blockages. For gate sizing, a new algorithm is proposed to handle discrete gate library in contrast to unrealistic continuous gate library assumed by most existing algorithms. Our approach is a continuous solution guided dynamic programming approach, which integrates the high solution quality of dynamic programming with the short runtime of rounding continuous solution. For lithography-driven optimization, the problem of cell placement considering manufacturability is studied. Three algorithms are proposed to handle cell flipping and relocation. They are based on dynamic programming and graph theoretic approaches, and can provide different tradeoff between variation reduction and wire- length increase. For post-silicon tuning-driven optimization, the problem of unified adaptivity optimization on logical and clock signal tuning is studied, which enables us to significantly save resources. The new algorithm is based on a novel linear programming formulation which is solved by an advanced robust linear programming technique. The continuous solution is then discretized using binary search accelerated dynamic programming, batch based optimization, and Latin Hypercube sampling based fast simulation

    Low-overhead fault-tolerant logic for field-programmable gate arrays

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    While allowing for the fabrication of increasingly complex and efficient circuitry, transistor shrinkage and count-per-device expansion have major downsides: chiefly increased variation, degradation and fault susceptibility. For this reason, design-time consideration of faults will have to be given to increasing numbers of electronic systems in the future to ensure yields, reliabilities and lifetimes remain acceptably high. Many mathematical operators commonly accelerated in hardware are suited to modification resulting in datapath error detection and correction capabilities with far lower area, performance and/or power consumption overheads than those incurred through the utilisation of more established, general-purpose fault tolerance methods such as modular redundancy. Field-programmable gate arrays are uniquely placed to allow further area savings to be made thanks to their dynamic reconfigurability. The majority of the technical work presented within this thesis is based upon a benchmark hardware accelerator---a matrix multiplier---that underwent several evolutions in order to detect and correct faults manifesting along its datapath at runtime. In the first instance, fault detectability in excess of 99% was achieved in return for 7.87% additional area and 45.5% extra latency. In the second, the ability to correct errors caused by those faults was added at the cost of 4.20% more area, while 50.7% of this---and 46.2% of the previously incurred latency overhead---was removed through the introduction of partial reconfiguration in the third. The fourth demonstrates further reductions in both area and performance overheads---of 16.7% and 8.27%, respectively---through systematic data width reduction by allowing errors of less than ±0.5% of the maximum output value to propagate.Open Acces
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