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Many parallel algorithms which solve basic problems in computer science use auxiliary space linear in the input to facilitate conflict-free computation. There has been significant work on improving these parallel algorithms to be in-place,…

Data Structures and Algorithms · Computer Science 2025-03-11 Chase Hutton , Adam Melrod

This paper presents the design and analysis of parallel approximation algorithms for facility-location problems, including $\NC$ and $\RNC$ algorithms for (metric) facility location, $k$-center, $k$-median, and $k$-means. These problems…

Data Structures and Algorithms · Computer Science 2010-06-11 Guy E. Blelloch , Kanat Tangwongsan

In this paper, we present several improvements in the parallelization of the in-place merge algorithm, which merges two contiguous sorted arrays into one with an O(T) space complexity (where T is the number of threads). The approach divides…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-05-27 Berenger Bramas , Quentin Bramas

Randomized parallel algorithms for many fundamental problems achieve optimal linear work in expectation, but upgrading this guarantee to hold with high probability (whp) remains a recurring theoretical challenge. In this paper, we address…

Data Structures and Algorithms · Computer Science 2026-03-03 Chase Hutton , Adam Melrod

Whether or not the problem of finding maximal independent sets (MIS) in hypergraphs is in (R)NC is one of the fundamental problems in the theory of parallel computing. Unlike the well-understood case of MIS in graphs, for the hypergraph…

Data Structures and Algorithms · Computer Science 2014-08-14 Ioana O. Bercea , Navin Goyal , David G. Harris , Aravind Srinivasan

We present a sorting algorithm that works in-place, executes in parallel, is cache-efficient, avoids branch-mispredictions, and performs work O(n log n) for arbitrary inputs with high probability. The main algorithmic contributions are new…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-07-03 Michael Axtmann , Sascha Witt , Daniel Ferizovic , Peter Sanders

We present sorting algorithms that represent the fastest known techniques for a wide range of input sizes, input distributions, data types, and machines. A part of the speed advantage is due to the feature to work in-place. Previously, the…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-02-05 Michael Axtmann , Sascha Witt , Daniel Ferizovic , Peter Sanders

Multicore shared cache processors pose a challenge for designers of embedded systems who try to achieve minimal and predictable execution time of workloads consisting of several jobs. To address this challenge the cache is statically…

Data Structures and Algorithms · Computer Science 2012-11-26 Avinatan Hassidim , Haim Kaplan , Omry Tuval

Many parallel algorithms use at least linear auxiliary space in the size of the input to enable computations to be done independently without conflicts. Unfortunately, this extra space can be prohibitive for memory-limited machines,…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-02 Yan Gu , Omar Obeya , Julian Shun

In this paper we develop optimal algorithms in the binary-forking model for a variety of fundamental problems, including sorting, semisorting, list ranking, tree contraction, range minima, and ordered set union, intersection and difference.…

Data Structures and Algorithms · Computer Science 2020-06-26 Guy E. Blelloch , Jeremy T. Fineman , Yan Gu , Yihan Sun

Emerging memory technologies have a significant gap between the cost, both in time and in energy, of writing to memory versus reading from memory. In this paper we present models and algorithms that account for this difference, with a focus…

Data Structures and Algorithms · Computer Science 2016-03-15 Guy E. Blelloch , Jeremy T. Fineman , Phillip B. Gibbons , Yan Gu , Julian Shun

Hypergraph partitioning is a recurring NP-hard problem in engineering; its efficient solution at scale hinges on parallelism. This work proposes a GPU-centric algorithm for multi-level hypergraph partitioning aimed at a specific set of…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-21 Marco Ronzani , Cristina Silvano

Interval scheduling is a basic problem in the theory of algorithms and a classical task in combinatorial optimization. We develop a set of techniques for partitioning and grouping jobs based on their starting and ending times, that enable…

Data Structures and Algorithms · Computer Science 2023-02-27 Spencer Compton , Slobodan Mitrović , Ronitt Rubinfeld

Data processing systems offer an ever increasing degree of parallelism on the levels of cores, CPUs, and processing nodes. Query optimization must exploit high degrees of parallelism in order not to gradually become the bottleneck of query…

Databases · Computer Science 2015-11-06 Immanuel Trummer , Christoph Koch

This paper introduces a new method of partitioning the solution space of a multi-objective optimisation problem for parallel processing, called Efficient Projection Partitioning. This method projects solutions down into a single dimension,…

Optimization and Control · Mathematics 2017-11-23 William Pettersson , Melih Ozlen

We investigate distributed memory parallel sorting algorithms that scale to the largest available machines and are robust with respect to input size and distribution of the input elements. The main outcome is that four sorting algorithms…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-01-17 Michael Axtmann , Peter Sanders

Partitioning a graph into blocks of "roughly equal" weight while cutting only few edges is a fundamental problem in computer science with a wide range of applications. In particular, the problem is a building block in applications that…

Data Structures and Algorithms · Computer Science 2021-05-06 Lars Gottesbüren , Tobias Heuer , Peter Sanders , Christian Schulz , Daniel Seemaier

This note makes an observation that significantly simplifies a number of previous parallel, two-way merge algorithms based on binary search and sequential merge in parallel. First, it is shown that the additional merge step of distinguished…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-07-02 Jesper Larsson Träff

Parallelism has become extremely popular over the past decade, and there have been a lot of new parallel algorithms and software. The randomized work-stealing (RWS) scheduler plays a crucial role in this ecosystem. In this paper, we study…

Data Structures and Algorithms · Computer Science 2021-11-10 Yan Gu , Zachary Napier , Yihan Sun

Mergesort is one of the few efficient sorting algorithms and, despite being the oldest one, often still the method of choice today. In contrast to some alternative algorithms, it always runs efficiently using O(n log n) element comparisons…

Data Structures and Algorithms · Computer Science 2025-09-30 Christian Siebert
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