虚拟到物理地址转换为一个基于fpga的互连与主机和GPU远程DMA能力

R. Ammendola, A. Biagioni, O. Frezza, F. L. Cicero, A. Lonardo, P. Paolucci, D. Rossetti, F. Simula, L. Tosoratto, P. Vicini
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引用次数: 22

摘要

我们开发了一个定制的基于fpga的网络接口控制器,名为APEnet+,针对GPU加速集群进行高性能计算。该卡为最新的NVIDIA GPGPU设备和RDMA范例利用点对点功能(GPU-Direct RDMA)在计算节点之间执行快速直接通信,从网络任务执行中卸载主机CPU。在这项工作中,我们着重于使用FPGA嵌入式软处理器实现虚拟到物理地址转换机制。对于NIC接收端来说,地址管理是要求最高的任务——我们估计高达70%的μC负载,这是导致数据瓶颈的罪魁祸首。为了提高该任务的性能,从而改善网络上的数据传输,我们添加了一个专门的硬件逻辑块作为翻译Lookaside Buffer。这个块使用了一种特殊的内容地址内存实现,设计用于可伸缩性和速度。我们提供了详细的测量来证明引入这种自定义逻辑所带来的好处:在给定的消息大小范围内,大幅降低了地址转换延迟(从1.9 μs的测量值降至124 ns),增强了主机绑定和gpu绑定数据传输的性能(高达60%的带宽增加)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Virtual-to-Physical address translation for an FPGA-based interconnect with host and GPU remote DMA capabilities
We developed a custom FPGA-based Network Interface Controller named APEnet+ aimed at GPU accelerated clusters for High Performance Computing. The card exploits peer-to-peer capabilities (GPU-Direct RDMA) for latest NVIDIA GPGPU devices and the RDMA paradigm to perform fast direct communication between computing nodes, offloading the host CPU from network tasks execution. In this work we focus on the implementation of a Virtual to Physical address translation mechanism, using the FPGA embedded soft-processor. Address management is the most demanding task - we estimated up to 70% of the μC load - for the NIC receiving side, resulting being the main culprit for data bottleneck. To improve the performance of this task and hence improve data transfer over the network, we added a specialized hardware logic block acting as a Translation Lookaside Buffer. This block makes use of a peculiar Content Address Memory implementation designed for scalability and speed. We present detailed measurements to demonstrate the benefits coming from the introduction of such custom logic: a substantial address translation latency reduction (from a measured value of 1.9 μs to 124 ns) and a performance enhancement of both host-bound and GPU-bound data transfers (up to ~ 60% of bandwidth increase) in given message size ranges.
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