多任务计算和Blue Waters
Many-Task Computing and Blue Waters
摘要：
本报告讨论了多任务计算（MTC）一般和背景下提出的蓝水系统，这是计划成为最大的NSF资助的超级计算机时，它开始生产使用在2012年。本报告的目的是告知BW项目有关MTC的信息，包括了解可用于表征域的MTC应用的各个方面，并了解这些方面对中间件和策略的影响。许多MTC应用并不完全符合高性能计算（HPC）或高吞吐量计算（HTC）应用的刻板印象。像HTC应用一样，根据定义，MTC应用被构造为离散任务的图，其中显式输入和输出依赖性形成图边缘。然而，MTC应用具有将它们与典型的HTC应用区分开的显著特征。特别是，为了支持这些应用，必须满足硬件和软件的不同工程约束。HTC应用程序传统上通过工作流系统或并行编程系统在网格和集群等平台上运行。相比之下，MTC应用通常将需要短的解决时间，可以是通信密集型或数据密集型的，并且可以包括非常短的任务。因此，用于MTC的硬件和软件必须被设计为支持附加的通信和I/O，并且必须最小化任务分派开销。大规模HPC系统的硬件具有高度的并行性和对密集通信的支持，非常适合MTC应用。然而，HPC系统通常缺乏动态资源供应特征，对于经由文件系统的任务通信来说不是理想的，并且具有未针对MTC风格的应用程序进行优化的I/O系统。因此，可能需要额外的软件支持才能从HPC硬件中获得全部好处。
英文摘要：
This report discusses many-task computing (MTC) generically and in the context of the proposed Blue Waters systems, which is planned to be the largest NSF-funded supercomputer when it begins production use in 2012. The aim of this report is to inform the BW project about MTC, including understanding aspects of MTC applications that can be used to characterize the domain and understanding the implications of these aspects to middleware and policies. Many MTC applications do not neatly fit the stereotypes of high-performance computing (HPC) or high-throughput computing (HTC) applications. Like HTC applications, by definition MTC applications are structured as graphs of discrete tasks, with explicit input and output dependencies forming the graph edges. However, MTC applications have significant features that distinguish them from typical HTC applications. In particular, different engineering constraints for hardware and software must be met in order to support these applications. HTC applications have traditionally run on platforms such as grids and clusters, through either workflow systems or parallel programming systems. MTC applications, in contrast, will often demand a short time to solution, may be communication intensive or data intensive, and may comprise very short tasks. Therefore, hardware and software for MTC must be engineered to support the additional communication and I/O and must minimize task dispatch overheads. The hardware of large-scale HPC systems, with its high degree of parallelism and support for intensive communication, is well suited for MTC applications. However, HPC systems often lack a dynamic resource-provisioning feature, are not ideal for task communication via the file system, and have an I/O system that is not optimized for MTC-style applications. Hence, additional software support is likely to be required to gain full benefit from the HPC hardware.
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