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The complete Voronoi map of a binary image with black and white pixels is a matrix of the same size such that each element is the closest black pixel of the corresponding pixel. The complete Voronoi map visualizes the influence region of each black pixel. However, each region may not be connected due to exclave pixels. The connected Voronoi map is a modification of the complete Voronoi map so that...
Lambda architecture is a novel event-driven serverless paradigm that allows companies to build scalable and reliable enterprise applications. As an attractive alternative to traditional service oriented architecture (SOA), Lambda architecture can be used in many use cases including BI tools, in-memory graph databases, OLAP, and streaming data processing. In practice, an important aim of Lambda's service...
In this paper, we study the link scheduling problem considering the fluctuating fading effect in transmissions. We extend the previous deterministic physical interference model to the Rayleigh-fading model that uses the stochastic propagation to address fading effects. Based on this model, we formulate a problem called Fading-Resistant Link Scheduling (Fading-R-LS) problem, which aims to maximize...
This paper investigates how to improve the memory locality of graph-structured analytics on large-scale shared memory systems. We demonstrate that a graph partitioning where all in-edges for a vertex are placed in the same partition improves memory locality. However, realising performance improvement through such graph partitioning poses several challenges and requires rethinking the classification...
Improving the performance of I/O virtualization is a key issue for cloud and datacenter infrastructures, especially with the rapid increase of network interconnection speeds. Previous efforts have made the performance overhead associated with the virtual I/O data path largely negligible. The remaining bottlenecks mainly lie in the event path: hypervisor interventions trigger costly virtual machine...
Broadcast operations (e.g. MPI_Bcast) have been widely used in deep learning applications to exchange a large amount of data among multiple graphics processing units (GPUs). Recent studies have shown that leveraging the InfiniBand hardware-based multicast (IB-MCAST) protocol can enhance scalability of GPU-based broadcast operations. However, these initial designs with IB-MCAST are not optimized for...
As we move towards an era of hundreds of cores, the research community has witnessed the emergence of optoelectronic network on-chip designs based on nanophotonics, in order to achieve higher network throughput, lower latencies, and lower dynamic power. However, traditional nanophotonics options face limitations such as large device footprints compared with electronics, higher static power due to...
Low-rank sparse tensor factorization is a populartool for analyzing multi-way data and is used in domainssuch as recommender systems, precision healthcare, and cybersecurity.Imposing constraints on a factorization, such asnon-negativity or sparsity, is a natural way of encoding priorknowledge of the multi-way data. While constrained factorizationsare useful for practitioners, they can greatly increasefactorization...
We present a set of new batched CUDA kernels for the LU factorization of a large collection of independent problems of different size, and the subsequent triangular solves. All kernels heavily exploit the registers of the graphics processing unit (GPU) in order to deliver high performance for small problems. The development of these kernels is motivated by the need for tackling this embarrasingly-parallel...
While GPUs are becoming common in HPC systems, the CPU is still responsible for managing both GPU-side and CPU-side compute, communication, and synchronization operations. For instance, if a result from a GPU-side computation is to be transferred to a remote destination, then the CPU must synchronize on GPU compute completion issuing a communication operation. Both CPU cycles and energy are consumed...
Fast, accurate three dimensional reconstructions of plasma equilibria, crucial for physics interpretation of fusion data generated within confinement devices like stellarators/ tokamaks, are computationally very expensive and routinely require days, even weeks, to complete using serial approaches. Here, we present a parallel implementation of the three dimensional plasma reconstruction code, V3FIT...
String pattern matching with finite automata (FAs) is a well-established method across many areas in computer science. Until now, data dependencies inherent in the pattern matching algorithm have hampered effective parallelization. To overcome the dependency-constraint between subsequent matching steps, simultaneous deterministic finite automata (SFAs) have been recently introduced. Although an SFA...
With the development of cloud computing, disk arrays tolerating triple disk failures (3DFTs) are receiving more attention nowadays because they can provide high data reliability with low monetary cost. However, a challenging issue in these arrays is how to efficiently reconstruct the lost data, especially for partial stripe errors (e.g., sector and chunk errors). It is one of the most significant...
Transactional Memory (TM) promises both to provide a scalable mechanism for synchronization in concurrent programs, and to offer ease-of-use benefits to programmers. The most straightforward use of TM in real-world programs is in the form of Transactional Lock Elision (TLE). In TLE, critical sections are attempted as transactions, with a fall-back to a lock if conflicts manifest. Thus TLE expects...
Hyperspectral image classification has been proved significant in remote sensing field. Traditional classification methods have meet bottlenecks due to the lack of remote sensing background knowledge or high dimensionality. Deep learning based methods, such as deep convolutional neural network (CNN), can effectively extract high level features from raw data. But the training of deep CNN is rather...
In parallel computing, a valid graph coloring yields a lock-free processing of the colored tasks, data points, etc., without expensive synchronization mechanisms. However, coloring is not free and the overhead can be significant. In particular, for the bipartite-graph partial coloring (BGPC) and distance-2 graph coloring (D2GC) problems, which have various use-cases within the scientific computing...
Projections and measurements of error rates in near-exascale and exascale systems suggest a dramatic growth, due to extreme scale (10^9 cores), concurrency, software complexity, and deep submicron transistor scaling. Such a growth makes resilience a critical concern, and may increase the incidence of errors that "escape", silently corrupting application state. Such errors can often be revealed...
Mobile edge cloud has been increasingly concerned by researchers due to its closer distance to mobile users than the traditional cloud on Internet. Offloading computations from mobile devices to the nearby edge cloud is an effective technique to accelerate the applications and/or save energy on the mobile devices. However, the mobile edge cloud usually has limited computation resources and constrained...
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