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In pursuit of graph processing performance, the systems community has largely abandoned general-purpose distributed dataflow frameworks in favor of specialized graph processing systems that provide tailored programming abstractions and accelerate the execution of iterative graph algorithms. In this paper we argue that many of the advantages of specialized(More)
From social networks to language modeling, the growing scale and importance of graph data has driven the development of numerous new graph-parallel systems (e.g., Pregel, GraphLab). By restricting the computation that can be expressed and introducing new techniques to partition and distribute the graph, these systems can efficiently execute iterative graph(More)
BACKGROUND Movement in response to painful stimulation is the end point classically used to assess the potency of anesthetic agents. In this study, the ability of modeled propofol effect-site concentration to predict movement in volunteers during propofol/nitrous oxide anesthesia was tested, then it was compared with the predictive abilities of the(More)
To enable complex data-intensive applications such as personalized recommendations, targeted advertising, and intelligent services, the data management community has focused heavily on the design of systems to train complex models on large datasets. Unfortunately, the design of these systems largely ignores a critical component of the overall analytics(More)
The anesthetic concentration just suppressing appropriate response to command (minimum alveolar anesthetic concentration awake [MAC-awake] for volatile anesthetics or plasma concentration to prevent a response in 50% of patients [Cp50]-awake for intravenous anesthetics) provides three important measures. First, along with pharmacokinetics, the ratio of the(More)
We describe the challenges arising from tracking dark matter particles in state of the art cosmological simulations. We are in the process of running the Indra suite of simulations, with an aggregate count of more than 35 trillion particles and 1.1PB of total raw data volume. However, it is not enough just to store the particle positions and velocities in(More)
Whether anesthetized patients register emotionally charged information remains controversial. We tested this possibility using subanesthetic concentrations of propofol or desflurane. Twenty-two volunteers (selected for hypnosis susceptibility) received propofol and desflurane (on separate occasions, and in a random order) at a concentration 1.5-2 times each(More)
Machine learning is being deployed in a growing number of applications which demand real-time, accurate, and robust predictions under heavy query load. However, most machine learning frameworks and systems only address model training and not deployment. In this paper, we introduce Clipper, a general-purpose low-latency prediction serving system. Interposing(More)
The growing scale and importance of graph data has driven the development of specialized graph computation engines capable of inferring complex recursive properties of graph-structured data. However, these systems are unable to express many of the inherently data-parallel stages in a typical graph-analytics pipeline. As a consequence, existing graph(More)
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