| Summary: | The increasing number of cores in both desktops and servers leads to a demand for efficient parallel algorithms. This project focuses on the fundamental collective operation reduce, which merges several arrays into one by applying a binary operation element wise. Several reduce algorithms are evaluated in terms of performance and scalability and a novel algorithm is introduced that takes advantage of shared memory and exploits load imbalance. To do so, the concept of dynamic pair generation is introduced which implies constructing a binary reduce tree dynamically based on the order of thread arrival, where pairs are formed in a lock-free manner. We conclude that the dynamic algorithm, given enough spread in the arriving times, can outperform the reference algorithms for some or all array sizes.
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