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Nearest Neighbor search is one of the simplest and most intuitive ideas in data mining. Due to it's simplicity and diverse utility, Nearest Neighbor search is often found to be the workhorse of a variety of data mining, machine learning, and computer vision algorithms. For very high dimensional data, the naive linear search tends to be optimal. This is due to the so called curse of dimensionality...
The current trend toward heterogeneous architectures motivates us to reconsider current software and hardware paradigms. The focus is centered around new parallel programming models, compiler design, and runtime resource management techniques to exploit the features of many-core processor architectures. Graphics Processing Units (GPU) have become the platform of choice in this area for accelerating...
In our paper we present an abstract object oriented runtime system that helps to develop scientific applications for new her erogenous architectures based on multi-node of multi-core processors enhanced with accelerator boards. Its architecture, based on abstract concepts, enables to follow hardware technology by extending these concepts with new implementations modeling new hardware components, while...
As the scale of high performance computing systems grows, three main challenges arise: the programmability, reliability, and energy efficiency of those systems. Accomplishing all three without sacrificing performance requires a rethinking of legacy distributed programming models and homogeneous clusters. In this work, we integrate Hadoop MapReduce with OpenCL to enable the use of heterogeneous processors...
Despite the vast interest in accelerator-based systems, programming large multinode GPUs is still a complex task, particularly with respect to optimal data movement across the host-GPU PCIe connection and then across the network. In order to address such issues, GPU-integrated MPI solutions have been developed that integrate GPU data movement into existing MPI implementations. Currently available...
In recent years, heterogeneous clusters using accelerators have been widely used in high performance computing systems. In such clusters, inter-node communication among accelerators requires several memory copies via CPU memory, and the communication latency causes severe performance degradation. In order to address this problem, we propose the Tightly Coupled Accelerators (TCA) architecture to reduce...
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