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—The process of detecting logical faults in integrated circuits (ICs) due to manufacturing variations is bottlenecked by the I/O cost of scanning in test vectors and offloading test results. Traditionally, the output bottleneck is alleviated by reducing the number of bits in output responses using XOR networks, or computing signatures from the responses of(More)
In this paper, we use a finite-state model to predict the performance of the Transmission Control Protocol (TCP) over a varying wireless channel between an unmanned aerial vehicle (UAV) and ground nodes. As a UAV traverses its flight path, the wireless channel may experience periods of significant packet loss, successful packet delivery, and intermittent(More)
—Wireless data transfer under high mobility, as found in unmanned aerial vehicle (UAV) applications, is a challenge due to varying channel quality and extended link outages. We present FlowCode, an easily deployable link-layer solution utilizing multiple transmitters and receivers for the purpose of supporting existing transport protocols such as TCP in(More)
—We consider the problem of mitigating a highly varying wireless channel between a transmitting ground node and receivers on a small, low-altitude unmanned aerial vehicle (UAV) in a 802.11 wireless mesh network. One approach is to use multiple transmitter and receiver nodes that exploit the channel's spatial/temporal diversity and that cooperate to improve(More)
Network firewalls remain the forefront defense for most computer systems. These critical devices filter traffic by comparing arriving packets to a list of rules, or security policy, in a sequential manner. Unfortunately packet filtering in this fashion can result in significant traffic delays, which is problematic for applications that require strict(More)
Conjugate gradient is an important iterative method used for solving least squares problems. It is compute-bound and generally involves only simple matrix computations. One would expect that we could fully parallelize such computation on the GPU architecture with multiple Stream Multiprocessors (SMs), each consisting of many SIMD processing units. While(More)
—We consider the problem of mitigating a highly varying wireless channel between a ground node transmitting to a small, low-altitude unmanned aerial vehicle (UAV) in a wireless mesh network. One approach is to use multiple receiver nodes on the UAV that exploit the channel's spatial/temporal diversity and that cooperate to improve overall packet reception.(More)
We characterize a general class of algorithms common in machine learning, scientific computing, and signal processing, whose computational dependencies are both sparse, and dynamically defined throughout execution. Existing parallel computing runtimes, like MapReduce and GraphLab, are a poor fit for this class because they assume statically defined(More)
—We apply hierarchical sparse coding, a form of deep learning, to model user-driven workloads based on on-chip hardware performance counters. We then predict periods of low instruction throughput, during which frequency and voltage can be scaled to reclaim power. Using a multi-layer coding structure, our method progressively codes counter values in terms of(More)