Collaborative Research: Dynamic Staging Architecture for Accelerating I/O Pipelines

Petascale应用程序正在以很高的速度产生TB级的数据。大规模机器中的存储系统压力很大，因为I/O速率的增长速度不足以科普数据生产。各种HPC活动（如写入输出和检查点数据）都受到I/O带宽瓶颈的阻碍。此外，由于超级计算机和用户本地集群的存储/处理能力之间的差距越来越大，计算结果的后处理和后续分析/可视化越来越耗时。本研究的重点是建立一个新的工作动态数据分级架构，并使其承担迫在眉睫的千万亿I/O危机。为此，研究了以下目标：（i）协调使用来自专用节点集的节点本地存储器和新兴硬件（诸如固态硬盘（SSD）），作为缓解I/O带宽瓶颈的手段，（ii）传统的用户后处理流水线和二级计算与登台上的异步I/O的复用，以执行可扩展的I/O和数据分析，（iii）绕过存储器以访问暂存区域，以及（iv）在暂存地和将其连接到计算客户端和持久存储器的通信信道中启用QoS。这项研究将对未来提供极端规模的机器产生广泛的影响，并将为此提供形成性的指导方针。这项研究的结果将是一套集成的技术，可以从根本上改变目前的并行I/O模型和加速千万亿次I/O流水线。此外，这项研究将有助于分析SSD在日常超级计算I/O中的实用性，并向更广泛的HPC社区通报其可行性。

Petascale applications are producing terabytes of data at a great rate. Storage systems in large-scale machines are significantly stressed as I/O rates are not growing as fast to cope with data production. A variety of HPC activities such as writing output and checkpoint data are all stymied by the I/O bandwidth bottleneck. Further to this, the post-processing and subsequent analysis/visualization of computational results is increasingly time consuming due to the widening gap between the storage/processing capacities of supercomputers and users' local clusters. This research focuses on building a novel in-job dynamic data staging architecture and in bringing it to bear on the looming petascale I/O crisis. To this end, the following objectives are investigated: (i) the concerted use of node-local memory and emerging hardware such as Solid State Disks (SSDs), from a dedicated set of nodes, as a means to alleviate the I/O bandwidth bottleneck, (ii) the multiplexing of traditional user post-processing pipelines and secondary computations with asynchronous I/O on the staging ground to perform scalable I/O and data analytics, (iii) bypassing memory to access the staging area, and (iv) enabling QoS both in the staging ground and in the communication channel connecting it to compute client and persistent storage. This study will have a wide-ranging impact on future provisioning of extreme-scale machines and will provide formative guidelines to this end. The result of this research will be a set of integrated techniques that can fundamentally change the current parallel I/O model and accelerate petascale I/O pipelines. Further, this research will help analyze the utility of SSDs in day-to-day supercomputing I/O and inform the wider HPC community of its viability.