论文标题
快速的LDPC GPU解码器用于云运行
Fast LDPC GPU Decoder for Cloud RAN
论文作者
论文摘要
研究了GPU作为云运行的数字信号处理加速器。介绍了在GPU上运行的5G NR低密度均衡检查代码解码器的新设计。该算法灵活地适应GPU体系结构，以实现高资源利用和低延迟。它改进了现有的分层设计，该设计并联以增加利用率。与在FPGA（757K门）上实现的解码器相比，新的GPU（24 Core）解码器具有3倍的吞吐量。 GPU解码器表现出3至5倍的分解功率效率，这是通用处理器的典型特征。因此，GPU可能会发现应用程序作为云加速器，在这些加速器中，快速部署和灵活性优先于解码功率效率。
The GPU as a digital signal processing accelerator for cloud RAN is investigated. A new design for a 5G NR low density parity check code decoder running on a GPU is presented. The algorithm is flexibly adaptable to GPU architecture to achieve high resource utilization as well as low latency. It improves over an existing layered design that processes additional codewords in parallel to increase utilization. In comparison to a decoder implemented on a FPGA (757K gate), the new GPU (24 core) decoder has 3X higher throughput. The GPU decoder exhibits 3 to 5X lower decoding power efficiency, as typical of a general-purpose processor. Thus, GPUs may find application as cloud accelerators where rapid deployment and flexibility are prioritized over decoding power efficiency.
