UMD Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/3
New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.
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Item Variability of terrestrial carbon cycle and its interaction with climate under global warming(2008-08-04) qian, haifeng; Zeng, Ning; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Land-atmosphere carbon exchange makes a significant contribution to the variability of atmospheric CO2 concentration on time scales of seasons to centuries. In this thesis, a terrestrial vegetation and carbon model, VEgetation-Global-Atmosphere-Soil (VEGAS), is used to study the interactions between the terrestrial carbon cycle and climate over a wide-range of temporal and spatial scales. The VEGAS model was first evaluated by comparison with FLUXNET observations. One primary focus of the thesis was to investigate the interannual variability of terrestrial carbon cycle related to climate variations, in particular to El Niño-Southern Oscillation (ENSO). Our analysis indicates that VEGAS can properly capture the response of terrestrial carbon cycle to ENSO: suppression of vegetative activity coupled with enhancement of soil decomposition, due to predominant warmer and drier climate patterns over tropical land associated with El Niño. The combined affect of these forcings causes substantial carbon flux into the atmosphere. A unique aspect of this work is to quantify the direct and indirect effects of soil wetness vegetation activities and consequently on land-atmosphere carbon fluxes. Besides this canonic dominance of the tropical response to ENSO, our modeling study simulated a large carbon flux from the northern mid-latitudes, triggered by the 1998-2002 drought and warming in the region. Our modeling indicates that this drought could be responsible for the abnormally high increase in atmospheric CO2 growth rate (2 ppm/yr) during 2002-2003. We then investigated the carbon cycle-climate feedback in the 21st century. A modest feedback was identified, and the result was incorporated into the Coupled Carbon Cycle Climate Model Inter-comparison Project (C4MIP). Using the fully coupled carbon cycle-climate simulations from C4MIP, we examined the carbon uptake in the Northern High Latitudes poleward of 60˚N (NHL) in the 21st century. C4MIP model results project that the NHL will be a carbon sink by 2100, as CO2 fertilization and warming stimulate vegetation growth, canceling the effect of enhancement of soil decomposition by warming. However, such competing mechanisms may lead to a switch of NHL from a net carbon sink to source after 2100. All these effects are enhanced as a result of positive carbon cycle-climate feedbacks.Item Variability-Aware VLSI Design Automation For Nanoscale Technologies(2007-05-16) Khandelwal, Vishal; Srivastava, Ankur; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)As technology scaling enters the nanometer regime, design of large scale ICs gets more challenging due to shrinking feature sizes and increasing design complexity. Aggressive scaling causes significant degradation in reliability, increased susceptibility to fabrication and environmental randomness and increased dynamic and leakage power dissipation. In this work, we investigate these scaling issues in large scale integrated systems. This dissertation proposes to develop variability-aware design methodologies by proposing design analysis, design-time optimization, post-silicon tunability and runtime-adaptivity based optimization techniques for handling variability. We discuss our research in the area of variability-aware analysis, specifically focusing on the problem of statistical timing analysis. The first technique presents the concept of error budgeting that achieves significant runtime speedups during statistical timing analysis. The second work presents a general framework for non-linear non-Gaussian statistical timing analysis considering correlations. Further, we present our work on design-time optimization schemes that are applicable during physical synthesis. Firstly, we present a buffer insertion technique that considers wire-length uncertainty and proposes algorithms to perform probabilistic buffer insertion. Secondly, we present a stochastic optimization framework based on Monte-Carlo technique considering fabrication variability. This optimization framework can be applied to problems that can be modeled as linear programs without without imposing any assumptions on the nature of the variability. Subsequently, we present our work on post-silicon tunability based design optimization. This work presents a design management framework that can be used to balance the effort spent on pre-silicon (through gate sizing) and post-silicon optimization (through tunable clock-tree buffers) while maximizing the yield gains. Lastly, we present our work on variability-aware runtime optimization techniques. We look at the problem of runtime supply voltage scaling for dynamic power optimization, and propose a framework to consider the impact of variability on the reliability of such designs. We propose a probabilistic design synthesis technique where reliability of the design is a primary optimization metric.