skip to main content

Search for: All records

Creators/Authors contains: "Gifford, Robert"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Modern latency-sensitive and real-time systems often use multi-core platforms; thus, tasks on different cores share certain hardware resources, such as the memory bus and certain cache levels. This has two undesirable consequences: (1) tasks can interfere with each other, causing high latency for the system as a whole, and (2) it becomes difficult to meet deadlines, since the worst-case timing of a given task depends on the worst task it might have to compete with. Static partitioning isolates tasks from each other by allocating a certain fraction of the resources to each; however, many tasks execute in different phases (e.g., memory-intensive and CPU-intensive) that have different requirements. Thus, system designers are left with a choice between overprovisioning, based on the most demanding phase, or suboptimal performance. In this paper, we propose a pair of techniques, called DNA and DADNA, to address the above challenge. DNA increases throughput and decreases latency, by building an execution profile of each task to identify the phases, and then dynamically allocating resources based on which task can benefit the most; DADNA further adds support for soft real-time workloads by taking deadlines into account. We have built a prototype of both techniques in the Xen hypervisor;more »our experimental results show that, compared to a state-of-the-art solution, DNA and DADNA can substantially improve schedulability, reduce job deadline miss ratios, and cut latencies by more than a factor of two even in extremely overloaded situations.« less