5,937 research outputs found
Lock-free Concurrent Data Structures
Concurrent data structures are the data sharing side of parallel programming.
Data structures give the means to the program to store data, but also provide
operations to the program to access and manipulate these data. These operations
are implemented through algorithms that have to be efficient. In the sequential
setting, data structures are crucially important for the performance of the
respective computation. In the parallel programming setting, their importance
becomes more crucial because of the increased use of data and resource sharing
for utilizing parallelism.
The first and main goal of this chapter is to provide a sufficient background
and intuition to help the interested reader to navigate in the complex research
area of lock-free data structures. The second goal is to offer the programmer
familiarity to the subject that will allow her to use truly concurrent methods.Comment: To appear in "Programming Multi-core and Many-core Computing
Systems", eds. S. Pllana and F. Xhafa, Wiley Series on Parallel and
Distributed Computin
Boosting Multi-Core Reachability Performance with Shared Hash Tables
This paper focuses on data structures for multi-core reachability, which is a
key component in model checking algorithms and other verification methods. A
cornerstone of an efficient solution is the storage of visited states. In
related work, static partitioning of the state space was combined with
thread-local storage and resulted in reasonable speedups, but left open whether
improvements are possible. In this paper, we present a scaling solution for
shared state storage which is based on a lockless hash table implementation.
The solution is specifically designed for the cache architecture of modern
CPUs. Because model checking algorithms impose loose requirements on the hash
table operations, their design can be streamlined substantially compared to
related work on lockless hash tables. Still, an implementation of the hash
table presented here has dozens of sensitive performance parameters (bucket
size, cache line size, data layout, probing sequence, etc.). We analyzed their
impact and compared the resulting speedups with related tools. Our
implementation outperforms two state-of-the-art multi-core model checkers (SPIN
and DiVinE) by a substantial margin, while placing fewer constraints on the
load balancing and search algorithms.Comment: preliminary repor
Concurrent High-performance Persistent Hash Table In Java
Current trading systems must handle both high volumes of trading and large amounts of trading data. One crucial module in high-performance trading is fast storage and retrieval of large volumes of data simultaneously accessed by multiple computer traders. To speed up access, a high-performance in-memory software-cache stores the dynamic working-set of trades during a trading day. To utilize memory effeciently, it is beneficial to provide a single shared cache for multiple trading applications. Much of the cache access is read-only, as information is gathered before a transaction to determine its value. Hence, extremely fast lookup is essential to support quick information gathering for assessment. This thesis presents a software-cache, called MapHash, that is a high-performance hash-table for use in Java
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