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A parallel multi-unit resource deadlock detection algorithm with O(log_2(min(m, n))) overall run-time complexity

机译:具有O(log_2(min(m,n)))总运行时复杂度的并行多单元资源死锁检测算法

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Current MPSoCs typically consist of less than a dozen processing units. Future MPSoCs are likely to integrate many more. With this trend, dozens of applications can be running on an MPSoC concurrently and application deadlock on MPSoCs will become a severe problem. To address the application deadlock problem in current and future MPSoCs, this article proposes a parallel multi-unit resource deadlock detection algorithm, incorporating four contributions: (1) a classification of resource events that enables each category of events to be handled efficiently, (2) a parallel node hopping mechanism that explores the entire graph exponentially in parallel to obtain information about reachable processes of every resource, (3) an innovative hardware implementation of the node hopping mechanism using bit-wise computations, and (4) proofs of correctness and run-time complexity of the proposed algorithm. Based on information about reachable processes as well as sink nodes in the graph, the proposed algorithm detects deadlock in 0(1) run-time. Compared with the worst case run-time of any previous algorithm, which employs a single scheme to handle all resource events, ours is considerably reduced to O(log_2(min(m, n))) when implemented in hardware, where m and n are the number of processes and resources, respectively.
机译:当前的MPSoC通常包含少于十二个处理单元。未来的MPSoC可能会集成更多。随着这种趋势,MPSoC上可以同时运行数十个应用程序,而MPSoC上的应用程序死锁将成为一个严重的问题。为了解决当前和将来的MPSoC中的应用程序死锁问题,本文提出了一种并行的多单元资源死锁检测算法,该算法包含四个方面:(1)资源事件的分类,使每个事件类别都能得到有效处理,(2 )并行节点跳跃机制,以指数方式并行探索整个图,以获得有关每个资源可到达过程的信息,(3)使用逐位计算的节点跳跃机制的创新硬件实现,以及(4)正确性和有效性的证明该算法的运行时复杂度。基于图中有关可达进程以及宿节点的信息,该算法在运行时间为0(1)时检测死锁。与任何以前采用单一方案处理所有资源事件的算法在最坏情况下的运行时间相比,当在硬件中实现m和n时,我们的算法大大降低为O(log_2(min(m,n)))。分别是进程数和资源数。

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