MULTIMAP AND MULTISET DATA STRUCTURES IN STAPL

The Standard Template Adaptive Parallel Library (STAPL) is an e_cient programming framework whose components make it easier to implement parallel applications that can utilize multiple processors to solve large problems concurrently [1]. STAPL is developed using the C++ programming language and provides parallel equivalents of many algorithms and data structures (containers) found in its Standard Template Library (STL). Although STAPL contains a large collection of parallel data structures and algorithms, there are still many algorithms and containers that are not yet implemented in STAPL. Multimap and multiset are two associative containers that are included in STL but not yet implemented in STAPL. The goal of this work is to design and implement the parallel multimap and parallel multiset containers that provide the same functionality as their STL counterparts while enabling parallel computation on large scale data

Unordered Associative Containers in STAPL

The Standard Template Adaptive Parallel Library (STAPL) is a parallel programming framework for C++ that provides parallel algorithms and containers similar to those found in the Standard Template Library (STL). Currently STAPL is lacking implementations for three unordered associative containers: unordered set, unordered multiset, and unordered multimap. These are commonly used containers in the field of computer science; therefore, their implementations are a necessity for STAPL. The similarity of operations and structure between each container will allow a large portion of code to be reused. The goal of this work is to design and create a parallel implementation of these containers that provides the same user-level facilities as their STL equivalents and displays a high level of scalability when executed on a large number of processors