Holistic Routing Algorithm Design to Support Workload Consolidation in NoCs
Holistic Routing Algorithm Design to Support Workload Consolidation in NoCs
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DOI：
10.1109/tc.2012.201
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发表时间：
2014-03
影响因子：
3.7
通讯作者：
Sheng Ma;Natalie D. Enright Jerger;Zhiying Wang;Ming-che Lai;Libo Huang
中科院分区：
文献类型：
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作者：
Sheng Ma;Natalie D. Enright Jerger;Zhiying Wang;Ming-che Lai;Libo Huang
为了提供高效、高性能的路由算法，应该采取整体方法。路由算法设计的关键方面包括自适应性、路径选择策略、VC分配、隔离和硬件实现成本，这些设计方面不是独立的。这项工作的主要贡献在于设计了一种新的选择策略，即基于目的地的选择策略（DBSS），该策略针对运行整合工作负载的众核系统中可能出现的干扰。在设计过程中，我们从整体上考虑了各个方面，以确保设计的高效性。现有的路由算法在很大程度上忽略了与工作负载整合相关的问题。局部自适应算法没有考虑足够的状态信息来避免网络拥塞。全局自适应路由算法通过利用邻居节点以外的网络状态来解决这个问题。然而，它们可能会受到干扰，耦合其他独立应用程序的行为。为了解决这些问题，DBSS利用本地和非本地网络状态来提供更有效的自适应性。更重要的是，通过将目的地集成到选择过程中，DBSS减轻了干扰，并在应用程序之间提供了动态隔离。结果表明，DBSS提供了更好的性能比最好的基线选择策略，并提高了中，高注入速率的能量延迟产品，它是非常适合工作负载整合。
To provide efficient, high-performance routing algorithms, a holistic approach should be taken. The key aspects of routing algorithm design include adaptivity, path selection strategy, VC allocation, isolation, and hardware implementation cost; these design aspects are not independent. The key contribution of this work lies in the design of a novel selection strategy, Destination-Based Selection Strategy (DBSS), which targets interference that can arise in many-core systems running consolidation workloads. In the process of this design, we holistically consider all aspects to ensure an efficient design. Existing routing algorithms largely overlook issues associated with workload consolidation. Locally adaptive algorithms do not consider enough status information to avoid network congestion. Globally adaptive routing algorithms attack this issue by utilizing network status beyond neighboring nodes. However, they may suffer from interference, coupling the behavior of otherwise independent applications. To address these issues, DBSS leverages both local and nonlocal network status to provide more effective adaptivity. More importantly, by integrating the destination into the selection procedure, DBSS mitigates interference and offers dynamic isolation among applications. Results show that DBSS offers better performance than the best baseline selection strategy and improves the energy-delay product for medium and high injection rates; it is well suited for workload consolidation.