TY - GEN
T1 - Window-based greedy contention management for transactional memory
AU - Sharma, Gokarna
AU - Estrade, Brett
AU - Busch, Costas
N1 - Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - We consider greedy contention managers for transactional memory for M × N execution windows of transactions with M threads and N transactions per thread. Assuming that each transaction has duration τ and conflicts with at most C other transactions inside the window, a trivial greedy contention manager can schedule them within τCN time. In this paper, we explore the theoretical performance boundaries of this approach from the worst-case perspective. Particularly, we present and analyze two new randomized greedy contention management algorithms. The first algorithm Offline-Greedy produces a schedule of length O(τ•(C + N log (MN))) with high probability, and gives competitive ratio O(log (MN)) for C ≤ N log (MN). The offline algorithm depends on knowing the conflict graph which evolves while the execution of the transactions progresses. The second algorithm Online-Greedy produces a schedule of length O(τ•(C log (MN) + N log2(MN))), with high probability, which is only a O(log (NM)) factor worse, but does not require knowledge of the conflict graph. Both of the algorithms exhibit competitive ratio very close to O(s), where s is the number of shared resources. Our algorithms provide new tradeoffs for greedy transaction scheduling that parameterize window sizes and transaction conflicts within the window.
AB - We consider greedy contention managers for transactional memory for M × N execution windows of transactions with M threads and N transactions per thread. Assuming that each transaction has duration τ and conflicts with at most C other transactions inside the window, a trivial greedy contention manager can schedule them within τCN time. In this paper, we explore the theoretical performance boundaries of this approach from the worst-case perspective. Particularly, we present and analyze two new randomized greedy contention management algorithms. The first algorithm Offline-Greedy produces a schedule of length O(τ•(C + N log (MN))) with high probability, and gives competitive ratio O(log (MN)) for C ≤ N log (MN). The offline algorithm depends on knowing the conflict graph which evolves while the execution of the transactions progresses. The second algorithm Online-Greedy produces a schedule of length O(τ•(C log (MN) + N log2(MN))), with high probability, which is only a O(log (NM)) factor worse, but does not require knowledge of the conflict graph. Both of the algorithms exhibit competitive ratio very close to O(s), where s is the number of shared resources. Our algorithms provide new tradeoffs for greedy transaction scheduling that parameterize window sizes and transaction conflicts within the window.
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U2 - 10.1007/978-3-642-15763-9_7
DO - 10.1007/978-3-642-15763-9_7
M3 - Conference contribution
AN - SCOPUS:78649874452
SN - 3642157629
SN - 9783642157622
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 64
EP - 78
BT - Distributed Computing - 24th International Symposium, DISC 2010, Proceedings
T2 - 24th International Symposium on Distributed Computing, DISC 2010
Y2 - 13 September 2010 through 15 September 2010
ER -