Результаты поиска по 'high data throughput computing':
Найдено статей: 3
  1. Cox M.A., Reed R.G., Mellado B.
    The development of an ARM system on chip based processing unit for data stream computing
    Computer Research and Modeling, 2015, v. 7, no. 3, pp. 505-509

    Modern big science projects are becoming highly data intensive to the point where offline processing of stored data is infeasible. High data throughput computing, or Data Stream Computing, for future projects is required to deal with terabytes of data per second which cannot be stored in long-term storage elements. Conventional data-centres based on typical server-grade hardware are expensive and are biased towards processing power. The overall I/O bandwidth can be increased with massive parallelism, usually at the expense of excessive processing power and high energy consumption. An ARM System on Chip (SoC) based processing unit may address the issue of system I/O and CPU balance, affordability and energy efficiency since ARM SoCs are mass produced and designed to be energy efficient for use in mobile devices. Such a processing unit is currently in development, with a design goal of 20 Gb/s I/O throughput and significant processing power. The I/O capabilities of consumer ARM System on Chips are discussed along with to-date performance and I/O throughput tests.

    Keywords: high data throughput computing, big data, arm system on chips.
    Views (last year): 1.
  2. Reed R.G., Cox M.A., Wrigley T., Mellado B.
    A CPU benchmarking characterization of ARM based processors
    Computer Research and Modeling, 2015, v. 7, no. 3, pp. 581-586

    Big science projects are producing data at ever increases rates. Typical techniques involve storing the data to disk, after minor filtering, and then processing it in large computer farms. Data production has reached a point where on-line processing is required in order to filter the data down to manageable sizes. A potential solution involves using low-cost, low-power ARM processors in large arrays to provide massive parallelisation for data stream computing (DSC). The main advantage in using System on Chips (SoCs) is inherent in its design philosophy. SoCs are primarily used in mobile devices and hence consume less power while maintaining relatively good performance. A benchmarking characterisation of three different models of ARM processors will be presented.

    Keywords: High data throughput, Computing, Big Data, ARM System on Chips, Benchmarking.
    Views (last year): 1.
  3. Wrigley T., Reed R.G., Mellado B.
    Memory benchmarking characterisation of ARM-based SoCs
    Computer Research and Modeling, 2015, v. 7, no. 3, pp. 607-613

    Computational intensity is traditionally the focus of large-scale computing system designs, generally leaving such designs ill-equipped to efficiently handle throughput-oriented workloads. In addition, cost and energy consumption considerations for large-scale computing systems in general remain a source of concern. A potential solution involves using low-cost, low-power ARM processors in large arrays in a manner which provides massive parallelisation and high rates of data throughput (relative to existing large-scale computing designs). Giving greater priority to both throughput-rate and cost considerations increases the relevance of primary memory performance and design optimisations to overall system performance. Using several primary memory performance benchmarks to evaluate various aspects of RAM and cache performance, we provide characterisations of the performances of four different models of ARM-based system-on-chip, namely the Cortex-A9, Cortex- A7, Cortex-A15 r3p2 and Cortex-A15 r3p3. We then discuss the relevance of these results to high volume computing and the potential for ARM processors.

    Keywords: ARM, memory, benchmarks, throughput-oriented computing, high-volume computing.

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