论文标题
评估英特尔的内存带宽分配以实时系统中的资源限制
Assessing Intel's Memory Bandwidth Allocation for resource limitation in real-time systems
论文作者
论文摘要
最近，行业正在考虑采用云计算来托管安全关键应用。但是，由于共享资源（例如内存子系统）的争议，云中通常采用的多核处理器的使用会引入时间异常。在本文中，我们探讨了Xeon可伸缩处理器可用的英特尔内存带宽分配（MBA）技术的潜力。通过在实际硬件上采用系统的测量方法，我们通过应用MBA延迟来评估可实现的间接内存带宽限制，这表明只有给定的延迟值（即70、80和90）在我们的环境中有效。我们还将在同一台计算机上存在干扰内核（例如，生成同时的内存访问工作负载）时，将确保的派生带宽确保为假设的临界核心。我们的结果可以通过提供对共享内存的影响以实现云环境中安全关键应用的可预测进展来支持设计师的支持。
Industries are recently considering the adoption of cloud computing for hosting safety critical applications. However, the use of multicore processors usually adopted in the cloud introduces temporal anomalies due to contention for shared resources, such as the memory subsystem. In this paper we explore the potential of Intel's Memory Bandwidth Allocation (MBA) technology, available on Xeon Scalable processors. By adopting a systematic measurement approach on real hardware, we assess the indirect memory bandwidth limitation achievable by applying MBA delays, showing that only given delay values (namely 70, 80 and 90) are effective in our setting. We also test the derived bandwidth assured to a hypothetical critical core when interfering cores (e.g., generating a concurrent memory access workload) are present on the same machine. Our results can support designers by providing understanding of impact of the shared memory to enable predictable progress of safety critical applications in cloud environments.
