GPF: A GPU-based Design to Achieve ~100 μs Scheduling for 5G NR
GPF: A GPU-based Design to Achieve ~100 μs Scheduling for 5G NR
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DOI：
10.1145/3241539.3241552
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发表时间：
2018-10
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通讯作者：
Yan Huang;Shaoran Li;Yiwei Thomas Hou;Wenjing Lou
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文献类型：
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作者：
Yan Huang;Shaoran Li;Yiwei Thomas Hou;Wenjing Lou
5G新无线电(NR)设计为在广泛的频段下运行，并以超低延迟支持新应用。为了支持其不同的操作条件，标准机构中定义了一组不同的ofdm数字表示法。在这种情况下，需要以∼100LTE S的时间分辨率进行调度。这一要求提出了新的挑战，这是μ中不存在的，也是任何现有的LTE调度器都无法支持的。本文提出了一种满足∼100μS时间要求的基于图形处理器的比例公平(PF)调度器--GPF的设计。其核心思想包括将调度问题分解为大量小而独立的子问题，并从最有希望的搜索空间中选择子问题的子集以适合于GPU。通过在现成的NVIDIA Quadro P6000图形处理器上实现GPF，我们证明了GPF能够在满足∼100美元\mathmμS的时间要求的同时获得接近最优的性能。GPF代表了第一个成功的基于GPU的PF调度器的设计，该调度器能够满足NR中新的时间需求。
5G New Radio (NR) is designed to operate under a broad range of frequency bands and support new applications with ultra-low latency. To support its diverse operating conditions, a set of different OFDM numerologies has been defined in the standards body. Under this numerology, it is necessary to perform scheduling with a time resolution of ∼100 μs. This requirement poses a new challenge that does not exist in LTE and cannot be supported by any existing LTE schedulers. In this paper, we present the design of GPF -- a GPU-based proportional fair (PF) scheduler that can meet the ∼100 μs time requirement. The key ideas include decomposing the scheduling problem into a large number of small and independent sub-problems and selecting a subset of sub-problems from the most promising search space to fit into a GPU. By implementing GPF on an off-the-shelf Nvidia Quadro P6000 GPU, we show that GPF is able to achieve near-optimal performance while meeting the ∼100 $\mathrmμs time requirement. GPF represents the first successful design of a GPU-based PF scheduler that can meet the new time requirement in NR.