14,593 research outputs found

    Modeling and Energy Optimization of LDPC Decoder Circuits with Timing Violations

    Full text link
    This paper proposes a "quasi-synchronous" design approach for signal processing circuits, in which timing violations are permitted, but without the need for a hardware compensation mechanism. The case of a low-density parity-check (LDPC) decoder is studied, and a method for accurately modeling the effect of timing violations at a high level of abstraction is presented. The error-correction performance of code ensembles is then evaluated using density evolution while taking into account the effect of timing faults. Following this, several quasi-synchronous LDPC decoder circuits based on the offset min-sum algorithm are optimized, providing a 23%-40% reduction in energy consumption or energy-delay product, while achieving the same performance and occupying the same area as conventional synchronous circuits.Comment: To appear in IEEE Transactions on Communication

    Bayesian Optimization with Unknown Constraints

    Full text link
    Recent work on Bayesian optimization has shown its effectiveness in global optimization of difficult black-box objective functions. Many real-world optimization problems of interest also have constraints which are unknown a priori. In this paper, we study Bayesian optimization for constrained problems in the general case that noise may be present in the constraint functions, and the objective and constraints may be evaluated independently. We provide motivating practical examples, and present a general framework to solve such problems. We demonstrate the effectiveness of our approach on optimizing the performance of online latent Dirichlet allocation subject to topic sparsity constraints, tuning a neural network given test-time memory constraints, and optimizing Hamiltonian Monte Carlo to achieve maximal effectiveness in a fixed time, subject to passing standard convergence diagnostics.Comment: 14 pages, 3 figure

    Composite load spectra for select space propulsion structural components

    Get PDF
    The work performed to develop composite load spectra (CLS) for the Space Shuttle Main Engine (SSME) using probabilistic methods. The three methods were implemented to be the engine system influence model. RASCAL was chosen to be the principal method as most component load models were implemented with the method. Validation of RASCAL was performed. High accuracy comparable to the Monte Carlo method can be obtained if a large enough bin size is used. Generic probabilistic models were developed and implemented for load calculations using the probabilistic methods discussed above. Each engine mission, either a real fighter or a test, has three mission phases: the engine start transient phase, the steady state phase, and the engine cut off transient phase. Power level and engine operating inlet conditions change during a mission. The load calculation module provides the steady-state and quasi-steady state calculation procedures with duty-cycle-data option. The quasi-steady state procedure is for engine transient phase calculations. In addition, a few generic probabilistic load models were also developed for specific conditions. These include the fixed transient spike model, the poison arrival transient spike model, and the rare event model. These generic probabilistic load models provide sufficient latitude for simulating loads with specific conditions. For SSME components, turbine blades, transfer ducts, LOX post, and the high pressure oxidizer turbopump (HPOTP) discharge duct were selected for application of the CLS program. They include static pressure loads and dynamic pressure loads for all four components, centrifugal force for the turbine blade, temperatures of thermal loads for all four components, and structural vibration loads for the ducts and LOX posts

    Magellan/M2FS Spectroscopy of Galaxy Clusters: Stellar Population Model and Application to Abell 267

    Get PDF
    We report the results of a pilot program to use the Magellan/M2FS spectrograph to survey the galactic populations and internal kinematics of galaxy clusters. For this initial study, we present spectroscopic measurements for 223223 quiescent galaxies observed along the line of sight to the galaxy cluster Abell 267 (z∌0.23z\sim0.23). We develop a Bayesian method for modeling the integrated light from each galaxy as a simple stellar population, with free parameters that specify redshift (vlos/cv_\mathrm{los}/c) and characteristic age, metallicity ([Fe/H]\mathrm{[Fe/H]}), alpha-abundance ([α/Fe][\alpha/\mathrm{Fe}]), and internal velocity dispersion (σint\sigma_\mathrm{int}) for individual galaxies. Parameter estimates derived from our 1.5-hour observation of A267 have median random errors of σvlos=20 km s−1\sigma_{v_\mathrm{los}}=20\ \mathrm{km\ s^{-1}}, σAge=1.2 Gyr\sigma_{\mathrm{Age}}=1.2\ \mathrm{Gyr}, $\sigma_{\mathrm{[Fe/H]}}=0.11\ \mathrm{dex},, \sigma_{[\alpha/\mathrm{Fe}]}=0.07\ \mathrm{dex},and, and \sigma_{\sigma_\mathrm{int}}=20\ \mathrm{km\ s^{-1}}$. In a companion paper, we use these results to model the structure and internal kinematics of A267.Comment: 16 pages, 11 figures, accepted for publication in The Astronomical Journa

    Impact of phenylpropanoid compounds on heat stress tolerance in carrot cell cultures

    Get PDF
    The phenylpropanoid and flavonoid families include thousands of specialized metabolites that influence a wide range of processes in plants, including seed dispersal, auxin transport, photoprotection, mechanical support and protection against insect herbivory. Such metabolites play a key role in the protection of plants against abiotic stress, in many cases through their well-known ability to inhibit the formation of reactive oxygen species (ROS). However, the precise role of specific phenylpropanoid and flavonoid molecules is unclear. We therefore investigated the role of specific anthocyanins (ACs) and other phenylpropanoids that accumulate in carrot cells cultivated in vitro, focusing on their supposed ability to protect cells from heat stress. First we characterized the effects of heat stress to identify quantifiable morphological traits as markers of heat stress susceptibility. We then fed the cultures with precursors to induce the targeted accumulation of specific compounds, and compared the impact of heat stress in these cultures and unfed controls. Data modeling based on Projection to Latent Structures (PLS) regression revealed that metabolites containing coumaric or caffeic acid, including ACs, correlate with less heat damage. Further experiments suggested that one of the cellular targets damaged by heat stress and protected by these metabolites is the actin microfilament cytoskeleton
    • 

    corecore