A number of NUMA-aware synchronization algorithms have been proposed lately to stress the scalability inefficiencies of existing locks. However their presupposed local lock granularity, a physical processor, is often ...
详细信息
ISBN:
(纸本)9781479961238
A number of NUMA-aware synchronization algorithms have been proposed lately to stress the scalability inefficiencies of existing locks. However their presupposed local lock granularity, a physical processor, is often not the optimum configuration for various workloads. This paper further explores the design space by taking into consideration the physical affinity between the cores within a single processor, and presents FSL to support variable and finely tuned group size for different lock contexts and instances. The new design provides a uniform model for the discussion of affinity locks and can completely subsume the previous NUMA-aware designs because they have only discussed one special case of the model. The interfaces of the new scheme are kernel-compatible and thus largely facilitate kernel incorporation. The investigation with the lock shows that an affinity lock with optimal local lock granularity can outperform its NUMA-aware counterpart by 29.40% and 58.28% at 80 cores with different workloads.
We develop an efficient multicore algorithm, PMS6MC, for the (l;d) -motif discovery problem in which we are to find all strings of length l that appear in every string of a given set of strings with at most d mismatch...
详细信息
We develop an efficient multicore algorithm, PMS6MC, for the (l;d) -motif discovery problem in which we are to find all strings of length l that appear in every string of a given set of strings with at most d mismatches. PMS6MC is based on PMS6, which is currently the fastest single-core algorithm for motif discovery in large instances. The speedup, relative to PMS6, attained by our multicore algorithm ranges from a high of 6.62 for the (17,6) challenging instances to a low of 2.75 for the (13,4) challenging instances on an Intel 6-core system. We estimate that PMS6MC is 2 to 4 times faster than other parallel algorithms for motif search on large instances.
We focus on the constraint-based automated addition of nonmasking and stabilizing fault-tolerance to hierarchical programs. We specify legitimate states of the program in terms of constraints that should be satisfied ...
详细信息
We focus on the constraint-based automated addition of nonmasking and stabilizing fault-tolerance to hierarchical programs. We specify legitimate states of the program in terms of constraints that should be satisfied in those states. To deal with faults that may violate these constraints, we add recovery actions while ensuring interference freedom among the recovery actions added for satisfying different constraints. Since the constraint-based manual design of fault-tolerance is well known, we expect our approach to have a significant benefit in automating the addition of fault-tolerance. We illustrate our algorithm with four case studies: stabilizing mutual exclusion, stabilizing diffusing computation, a data dissemination problem in sensor networks, and tree maintenance. With experimental results, we show that the complexity of our algorithm is reasonable and that it can be reduced using the structure of the hierarchical systems. We also reduced the time complexity of the synthesis using parallelism. We consider two approaches to speedup the synthesis algorithm: first, the use of the multiple constraints that have to be satisfied during synthesis;second, the use of the distributed nature of the programs being synthesized. We show that our approaches provide significant reduction in the synthesis time. To our knowledge, this is the first instance where automated synthesis has been successfully used in synthesizing programs that are correct under fairness assumptions. Moreover, in three of the case studies considered in this paper, the structure of the recovery paths is too complex to permit existing heuristic-based approaches for adding recovery. (C) 2011 Elsevier B.V. All rights reserved.
We focus on the constraint-based automated addition of nonmasking and stabilizing fault-tolerance to hierarchical programs. We specify legitimate states of the program in terms of constraints that should be satisfied ...
详细信息
We focus on the constraint-based automated addition of nonmasking and stabilizing fault-tolerance to hierarchical programs. We specify legitimate states of the program in terms of constraints that should be satisfied in those states. To deal with faults that may violate these constraints, we add recovery actions while ensuring interference freedom among the recovery actions added for satisfying different constraints. Since the constraint-based manual design of fault-tolerance is well known, we expect our approach to have a significant benefit in automating the addition of fault-tolerance. We illustrate our algorithm with four case studies: stabilizing mutual exclusion, stabilizing diffusing computation, a data dissemination problem in sensor networks, and tree maintenance. With experimental results, we show that the complexity of our algorithm is reasonable and that it can be reduced using the structure of the hierarchical systems. We also reduced the time complexity of the synthesis using parallelism. We consider two approaches to speedup the synthesis algorithm: first, the use of the multiple constraints that have to be satisfied during synthesis;second, the use of the distributed nature of the programs being synthesized. We show that our approaches provide significant reduction in the synthesis time. To our knowledge, this is the first instance where automated synthesis has been successfully used in synthesizing programs that are correct under fairness assumptions. Moreover, in three of the case studies considered in this paper, the structure of the recovery paths is too complex to permit existing heuristic-based approaches for adding recovery. (C) 2011 Elsevier B.V. All rights reserved.
暂无评论