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The Scalability of Disjoint Data Structures on a New Hardware Transactional Memory System

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Abstract

In this paper we present our experiences constructing and testing in-memory data structures designed to be disjoint enough for transactional memory to be profitable as a serialization mechanism with no fallback to traditional locking. Our goal was to restrict memory conflicts to actual contention situations so that transactional memory techniques could be used as efficiently as possible. We describe the hardware transactional execution facility in the IBM zEnterprise EC12 server. We present an order preserving hashed structure that permits insertion, deletion, and traversal operations typically supported by a sorted linked list. We also present a concurrent open addressing hash table structure. We measure the performance and scalability for these data structures on the IBM zEnterprise EC12 server. Our results show near linear scalability of the insertion and deletion operations for up to 96 CPUs. We also discuss transaction abort frequency and hardware/software interactions.

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Acknowledgments

The authors would like to thank their colleagues for valuable help in this work. Christian Jacobi provided many insights into the Transactional Execution Facility hardware in zEnterprise EC12. Maged Michael discussed issues related to disjoint data structures. Robin Tanenbaum was critical in wrangling the unreleased hardware so the authors could actually conduct the experiments.

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  1. IBM T.J. Watson Research Center, Yorktown Heights, NY, 10598, USA

    Gong Su & Stephen Heisig

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  1. Gong Su
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  2. Stephen Heisig
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Correspondence to Gong Su.

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Su, G., Heisig, S. The Scalability of Disjoint Data Structures on a New Hardware Transactional Memory System. Int J Parallel Prog 43, 1192–1217 (2015). https://doi.org/10.1007/s10766-014-0322-9

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