54,675 research outputs found

    BrainFrame: A node-level heterogeneous accelerator platform for neuron simulations

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    Objective: The advent of High-Performance Computing (HPC) in recent years has led to its increasing use in brain study through computational models. The scale and complexity of such models are constantly increasing, leading to challenging computational requirements. Even though modern HPC platforms can often deal with such challenges, the vast diversity of the modeling field does not permit for a single acceleration (or homogeneous) platform to effectively address the complete array of modeling requirements. Approach: In this paper we propose and build BrainFrame, a heterogeneous acceleration platform, incorporating three distinct acceleration technologies, a Dataflow Engine, a Xeon Phi and a GP-GPU. The PyNN framework is also integrated into the platform. As a challenging proof of concept, we analyze the performance of BrainFrame on different instances of a state-of-the-art neuron model, modeling the Inferior- Olivary Nucleus using a biophysically-meaningful, extended Hodgkin-Huxley representation. The model instances take into account not only the neuronal- network dimensions but also different network-connectivity circumstances that can drastically change application workload characteristics. Main results: The synthetic approach of three HPC technologies demonstrated that BrainFrame is better able to cope with the modeling diversity encountered. Our performance analysis shows clearly that the model directly affect performance and all three technologies are required to cope with all the model use cases.Comment: 16 pages, 18 figures, 5 table

    Distributed Rate Allocation Policies for Multi-Homed Video Streaming over Heterogeneous Access Networks

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    We consider the problem of rate allocation among multiple simultaneous video streams sharing multiple heterogeneous access networks. We develop and evaluate an analytical framework for optimal rate allocation based on observed available bit rate (ABR) and round-trip time (RTT) over each access network and video distortion-rate (DR) characteristics. The rate allocation is formulated as a convex optimization problem that minimizes the total expected distortion of all video streams. We present a distributed approximation of its solution and compare its performance against H-infinity optimal control and two heuristic schemes based on TCP-style additive-increase-multiplicative decrease (AIMD) principles. The various rate allocation schemes are evaluated in simulations of multiple high-definition (HD) video streams sharing multiple access networks. Our results demonstrate that, in comparison with heuristic AIMD-based schemes, both media-aware allocation and H-infinity optimal control benefit from proactive congestion avoidance and reduce the average packet loss rate from 45% to below 2%. Improvement in average received video quality ranges between 1.5 to 10.7 dB in PSNR for various background traffic loads and video playout deadlines. Media-aware allocation further exploits its knowledge of the video DR characteristics to achieve a more balanced video quality among all streams.Comment: 12 pages, 22 figure

    Rate Splitting for MIMO Wireless Networks: A Promising PHY-Layer Strategy for LTE Evolution

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    MIMO processing plays a central part towards the recent increase in spectral and energy efficiencies of wireless networks. MIMO has grown beyond the original point-to-point channel and nowadays refers to a diverse range of centralized and distributed deployments. The fundamental bottleneck towards enormous spectral and energy efficiency benefits in multiuser MIMO networks lies in a huge demand for accurate channel state information at the transmitter (CSIT). This has become increasingly difficult to satisfy due to the increasing number of antennas and access points in next generation wireless networks relying on dense heterogeneous networks and transmitters equipped with a large number of antennas. CSIT inaccuracy results in a multi-user interference problem that is the primary bottleneck of MIMO wireless networks. Looking backward, the problem has been to strive to apply techniques designed for perfect CSIT to scenarios with imperfect CSIT. In this paper, we depart from this conventional approach and introduce the readers to a promising strategy based on rate-splitting. Rate-splitting relies on the transmission of common and private messages and is shown to provide significant benefits in terms of spectral and energy efficiencies, reliability and CSI feedback overhead reduction over conventional strategies used in LTE-A and exclusively relying on private message transmissions. Open problems, impact on standard specifications and operational challenges are also discussed.Comment: accepted to IEEE Communication Magazine, special issue on LTE Evolutio

    Exploiting Spatial Interference Alignment and Opportunistic Scheduling in the Downlink of Interference Limited Systems

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    In this paper we analyze the performance of single stream and multi-stream spatial multiplexing (SM) systems employing opportunistic scheduling in the presence of interference. In the proposed downlink framework, every active user reports the post-processing signal-to-interference-plus-noise-power-ratio (post-SINR) or the receiver specific mutual information (MI) to its own transmitter using a feedback channel. The combination of scheduling and multi-antenna receiver processing leads to substantial interference suppression gain. Specifically, we show that opportunistic scheduling exploits spatial interference alignment (SIA) property inherent to a multi-user system for effective interference mitigation. We obtain bounds for the outage probability and the sum outage capacity for single stream and multi stream SM employing real or complex encoding for a symmetric interference channel model. The techniques considered in this paper are optimal in different operating regimes. We show that the sum outage capacity can be maximized by reducing the SM rate to a value less than the maximum allowed value. The optimum SM rate depends on the number of interferers and the number of available active users. In particular, we show that the generalized multi-user SM (MU SM) method employing real-valued encoding provides a performance that is either comparable, or significantly higher than that of MU SM employing complex encoding. A combination of analysis and simulation is used to describe the trade-off between the multiplexing rate and sum outage capacity for different antenna configurations
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