Abstract. STL dictionaries like map and set are commonly used in C++ programs. We consider parallelizing two of their bulk operations, namely the construction from many elements, and the insertion of many elements at a time. Practical algorithms are proposed for these tasks. The implementation is completely generic and engineered to provide best performance for the variety of possible input characteristics. It features transparent integration into the STL. This can make programs profit in an easy way from multi-core processing power. The performance measurements show the practical usefulness on real-world multi-core machines with up to eight cores.

In this paper we consider parallel algorithms to partition an array with respect to a pivot. We focus on implementations for current widely available multi-core architectures. After reviewing existing algorithms, we propose a modification to obtain the minimal number of comparisons. We have implemented these algorithms and drawn an experimental comparison.

Abstract. We present three cache conscious implementations of STL standard compliant lists. Up to now, one could either find simple double linked list implementations that easily cope with standard strict requirements, or theoretical approaches that do not take into account any of these requirements in their design. In contrast, we have merged both approaches, paying special attention to iterators constraints. In this paper, we show the competitiveness of our implementations with an extensive experimental analysis. This shows, for instance, 5-10 times faster traversals and 3-5 times faster internal sort.

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We present three cache-conscious implementations of STL standard compliant lists. Until now, one could either find simple doubly linked list implementations that easily cope with standard strict requirements, or theoretical approaches that do not take into account any of these requirements in their design. In contrast, we have merged both approaches, paying special attention to iterators constraints. In this article, the competitiveness of our implementations is evinced with an extensive experimental analysis. This shows, for instance, 5 to 10 times faster traversals and 3 to 5 times faster internal sort.