41,019 research outputs found

    A Framework for Megascale Agent Based Model Simulations on Graphics Processing Units

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    Agent-based modeling is a technique for modeling dynamic systems from the bottom up. Individual elements of the system are represented computationally as agents. The system-level behaviors emerge from the micro-level interactions of the agents. Contemporary state-of-the-art agent-based modeling toolkits are essentially discrete-event simulators designed to execute serially on the Central Processing Unit (CPU). They simulate Agent-Based Models (ABMs) by executing agent actions one at a time. In addition to imposing an un-natural execution order, these toolkits have limited scalability. In this article, we investigate data-parallel computer architectures such as Graphics Processing Units (GPUs) to simulate large scale ABMs. We have developed a series of efficient, data parallel algorithms for handling environment updates, various agent interactions, agent death and replication, and gathering statistics. We present three fundamental innovations that provide unprecedented scalability. The first is a novel stochastic memory allocator which enables parallel agent replication in O(1) average time. The second is a technique for resolving precedence constraints for agent actions in parallel. The third is a method that uses specialized graphics hardware, to gather and process statistical measures. These techniques have been implemented on a modern day GPU resulting in a substantial performance increase. We believe that our system is the first ever completely GPU based agent simulation framework. Although GPUs are the focus of our current implementations, our techniques can easily be adapted to other data-parallel architectures. We have benchmarked our framework against contemporary toolkits using two popular ABMs, namely, SugarScape and StupidModel.GPGPU, Agent Based Modeling, Data Parallel Algorithms, Stochastic Simulations

    DPP-PMRF: Rethinking Optimization for a Probabilistic Graphical Model Using Data-Parallel Primitives

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    We present a new parallel algorithm for probabilistic graphical model optimization. The algorithm relies on data-parallel primitives (DPPs), which provide portable performance over hardware architecture. We evaluate results on CPUs and GPUs for an image segmentation problem. Compared to a serial baseline, we observe runtime speedups of up to 13X (CPU) and 44X (GPU). We also compare our performance to a reference, OpenMP-based algorithm, and find speedups of up to 7X (CPU).Comment: LDAV 2018, October 201

    Rethinking State-Machine Replication for Parallelism

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    State-machine replication, a fundamental approach to designing fault-tolerant services, requires commands to be executed in the same order by all replicas. Moreover, command execution must be deterministic: each replica must produce the same output upon executing the same sequence of commands. These requirements usually result in single-threaded replicas, which hinders service performance. This paper introduces Parallel State-Machine Replication (P-SMR), a new approach to parallelism in state-machine replication. P-SMR scales better than previous proposals since no component plays a centralizing role in the execution of independent commands---those that can be executed concurrently, as defined by the service. The paper introduces P-SMR, describes a "commodified architecture" to implement it, and compares its performance to other proposals using a key-value store and a networked file system

    Scalable Interactive Volume Rendering Using Off-the-shelf Components

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    This paper describes an application of a second generation implementation of the Sepia architecture (Sepia-2) to interactive volu-metric visualization of large rectilinear scalar fields. By employingpipelined associative blending operators in a sort-last configuration a demonstration system with 8 rendering computers sustains 24 to 28 frames per second while interactively rendering large data volumes (1024x256x256 voxels, and 512x512x512 voxels). We believe interactive performance at these frame rates and data sizes is unprecedented. We also believe these results can be extended to other types of structured and unstructured grids and a variety of GL rendering techniques including surface rendering and shadow map-ping. We show how to extend our single-stage crossbar demonstration system to multi-stage networks in order to support much larger data sizes and higher image resolutions. This requires solving a dynamic mapping problem for a class of blending operators that includes Porter-Duff compositing operators

    Three-dimensional architecture and biogenesis of membrane structures associated with hepatitis C virus replication

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    All positive strand RNA viruses are known to replicate their genomes in close association with intracellular membranes. In case of the hepatitis C virus (HCV), a member of the family Flaviviridae, infected cells contain accumulations of vesicles forming a membranous web (MW) that is thought to be the site of viral RNA replication. However, little is known about the biogenesis and three-dimensional structure of the MW. In this study we used a combination of immunofluorescence- and electron microscopy (EM)-based methods to analyze the membranous structures induced by HCV in infected cells. We found that the MW is derived primarily from the endoplasmic reticulum (ER) and contains markers of rough ER as well as markers of early and late endosomes, COP vesicles, mitochondria and lipid droplets (LDs). The main constituents of the MW are single and double membrane vesicles (DMVs). The latter predominate and the kinetic of their appearance correlates with kinetics of viral RNA replication. DMVs are induced primarily by NS5A whereas NS4B induces single membrane vesicles arguing that MW formation requires the concerted action of several HCV replicase proteins. Three-dimensional reconstructions identify DMVs as protrusions from the ER membrane into the cytosol, frequently connected to the ER membrane via a neck-like structure. In addition, late in infection multi-membrane vesicles become evident, presumably as a result of a stress-induced reaction. Thus, the morphology of the membranous rearrangements induced in HCV-infected cells resemble those of the unrelated picorna-, corona- and arteriviruses, but are clearly distinct from those of the closely related flaviviruses. These results reveal unexpected similarities between HCV and distantly related positive-strand RNA viruses presumably reflecting similarities in cellular pathways exploited by these viruses to establish their membranous replication factories

    An Open-Source Simulator for Cognitive Robotics Research: The Prototype of the iCub Humanoid Robot Simulator

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    This paper presents the prototype of a new computer simulator for the humanoid robot iCub. The iCub is a new open-source humanoid robot developed as a result of the “RobotCub” project, a collaborative European project aiming at developing a new open-source cognitive robotics platform. The iCub simulator has been developed as part of a joint effort with the European project “ITALK” on the integration and transfer of action and language knowledge in cognitive robots. This is available open-source to all researchers interested in cognitive robotics experiments with the iCub humanoid platform

    Loss of unstably amplified dihydrofolate reductase genes from mouse cells is greatly accelerated by hydroxyurea

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    Previous work has shown that mammalian cells that carry unstably amplified genes for dihydrofolate reductase (DHFR) gradually lose the amplified DHFR genes when grown in the absence of the DHFR inhibitor methotrexate (MTX). Unstably amplified genes occur on small acentric chromosomes called double minutes (DMs) or even smaller chromatin fragments, in contrast to stably amplified genes, which reside in centromere-containing chromosomes. We have found that the rate of loss of the unstably amplified DHFR genes can be greatly increased by growing the cells in the presence of a nonlethal concentration of hydroxyurea. For example, in one MTX-resistant subline studied, approximate to 90% of the original DHFR gene dosage is lost in 25-30 cell doublings in the absence of MTX. The same degree of loss is achieved, however, in <4 doublings if cells are grown in the presence of 50 μM hydroxyurea. This new effect of hydroxyurea does not appear to be due to changes in plating efficiency or selective cytotoxicity. In particular, no increase in cell death occurs at 50 μM hydroxyurea, and cells continue to multiply, albeit 1/2 to 2/3 as fast as in the absence of hydroxyurea. The ability to selectively accelerate the loss of amplified genes from mammalian cells as shown in the present work may have important implications both for the problem of drug resistance in cancer chemotherapy and for curing mammalian cells of extrachromosomally maintained DNA genomes of pathogenic viruses
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