Operating systems have historically had to manage only a single type of memory device. The imminent availability of heterogeneous memory devices based on emerging memory technologies confronts the classic single memory model and opens a new spectrum of possibilities for memory management. Transparent data movement between different memory devices based on access patterns of applications is a desired feature to make optimal use of such devices and to hide the complexity of memory management to the end-user. However, capturing memory access patterns of an application at runtime comes at a cost, which is particularly challenging for large scale parallel applications that may be sensitive to system noise. In this work, we focus on the access pattern profiling phase prior to the actual memory relocation. We study the feasibility of using Intel's Processor Event-Based Sampling (PEBS) feature to record memory accesses by sampling at runtime and study the overhead at scale. We have implemented a custom PEBS driver in the IHK/McKernel lightweight multi-kernel operating system, one of whose advantages is minimal system interference due to the lightweight kernel's simple design compared to other OS kernels such as Linux. We present the PEBS overhead of a set of scientific applications and show the access patterns identified in noise-sensitive HPC applications. Our results show that clear access patterns can be captured with a 10% overhead in the worst-case and 1% in the best case when running on up to 128k CPU cores (2,048 Intel Xeon Phi Knights Landing nodes). We conclude that online memory access profiling using PEBS at large scale is promising for memory management in heterogeneous memory environments.

中文翻译：

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基于PEBS的在线内存访问跟踪在大规模异构内存管理中的适用性。

过去，操作系统只能管理一种类型的存储设备。基于新兴存储技术的异构存储设备即将问世，这与经典的单存储模型相冲突，并为存储管理开辟了新的可能性。基于应用程序访问模式在不同存储设备之间进行透明数据移动是一种理想的功能，可以优化此类设备的使用并向最终用户隐藏存储管理的复杂性。但是，在运行时捕获应用程序的内存访问模式是有代价的，这对于可能对系统噪声敏感的大规模并行应用程序尤其具有挑战性。在这项工作中，我们将重点放在实际内存重定位之前的访问模式分析阶段。我们研究了使用英特尔 处理器的基于事件的采样（PEBS）功能可通过在运行时进行采样来记录内存访问，并大规模研究开销。我们已经在IHK / McKernel轻量级多内核操作系统中实现了自定义PEBS驱动程序，与其他操作系统内核（例如Linux）相比，由于轻量级内核的简单设计，其优势之一是系统干扰最小。我们介绍了一组科学应用程序的PEBS开销，并显示了在对噪声敏感的HPC应用程序中确定的访问模式。我们的结果表明，当在多达128k CPU内核（2,048个Intel Xeon Phi Knights Landing节点）上运行时，在最坏的情况下可以捕获清晰的访问模式，开销为10％，在最佳情况下为1％。