3 research outputs found

    Understanding the Hydromechanical Effects of Extreme Events To Improve the Performance of Infrastructure Foundations

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    Extreme hydroclimatic events like heavy rainfall, flooding, and prolonged drought can potentially cause the failure of infrastructure foundations, leading to socio-economic losses. The objective of this dissertation is to understand the deformation and bearing capacity behavior of drilled shafts subjected to extreme hydroclimatic events, including heavy rainfall, prolonged drought, and earthquake. The Finite Element Method (FEM) results show that during rainfall, the drilled shaft settled caused by a decrease in the porewater pressure in the sand leading to a decrease in the axial bearing capacity. The axial force variation from an experimental investigation showed good agreement with the FEM. The impact of natural hazards on deep foundations can be critical and highly unpredictable when extreme hydrological and seismic events occur simultaneously or in sequence. A multi-hazard analysis was carried out to understand the structural response of deep foundations. When the drilled shaft was subjected to the dynamic load from heavy rainfall followed by dynamic load from the earthquake, the vertical settlement for the drilled shaft was significantly high compared to the case where the drilled shaft was subjected to dynamic load from the earthquake. A case study was adopted to predict the structural response of drilled shaft at the end bent of a proposed bridge subjected to liquefaction-induced lateral spreading caused by extreme earthquake events. The structural response of the bridge foundation before, during, and after liquefaction-induced lateral spreading was predicted using analytical methods and FEM. The comparison results showed that the during-liquefaction scenario was the worst-case

    The NEBULA RPC-Optimized Architecture

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    Large-scale online services are commonly structured as a network of software tiers, which communicate over the datacenter network using RPCs. Ongoing trends towards software decomposition have led to the prevalence of tiers receiving and generating RPCs with runtimes of only a few microseconds. With such small software runtimes, even the smallest latency overheads in RPC handling have a significant relative performance impact. In particular, we find that growing network bandwidth introduces queuing effects within a server’s memory hierarchy, considerably hurting the response latency of fine-grained RPCs. In this work we introduce NeBuLa, an architecture optimized to accelerate the most challenging microsecond-scale RPCs, by leveraging two novel mechanisms to drastically improve server throughput under strict tail latency goals. First, NeBuLa reduces detrimental queuing at the memory controllers via hardware support for efficient in-LLC network buffer management. Second, NeBuLa’s network interface steers incoming RPCs into the CPU cores’ L1 caches, improving RPC startup latency. Our evaluation shows that NeBuLa boosts the throughput of a state-of-the-art key- value store by 1.25–2.19x compared to existing proposals, while maintaining strict tail latency goals
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