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Stencil computation is one of the most important kernels in various scientific and engineering applications. A variety of work has focused on vectorization techniques, aiming at exploiting the in-core data parallelism. Briefly, they either…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-18 Kun Li , Liang Yuan , Yunquan Zhang , Yue Yue , Hang Cao , Pengqi Lu

The deep learning revolution has greatly been accelerated by the 'hardware lottery': Recent advances in modern hardware accelerators and compilers paved the way for large-scale batch gradient optimization. Evolutionary optimization, on the…

Neural and Evolutionary Computing · Computer Science 2022-12-09 Robert Tjarko Lange

Quicksort is an instructive classroom approach to parallel sorting on distributed memory parallel computers with many opportunities for illustrating specific implementation alternatives and tradeoffs with common communication interfaces…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-10-25 Jesper Larsson Träff

Neural document ranking approaches, specifically transformer models, have achieved impressive gains in ranking performance. However, query processing using such over-parameterized models is both resource and time intensive. In this paper,…

Information Retrieval · Computer Science 2022-04-05 Jurek Leonhardt , Koustav Rudra , Megha Khosla , Abhijit Anand , Avishek Anand

We propose a new hybrid topology optimization algorithm based on multigrid approach that combines the parallelization strategy of CPU using OpenMP and heavily multithreading capabilities of modern Graphics Processing Units (GPU). In…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-02-01 Arya Prakash Padhi , Souvik Chakraborty , Anupam Chakrabarti , Rajib Chowdhury

This work evaluates the impact of sparse matrix reordering on the performance of sparse matrix-vector multiplication across different multicore CPU platforms. Reordering can significantly enhance performance by optimizing the non-zero…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-09-23 Omid Asudeh , Sina Mahdipour Saravani , Gerald Sabin , Fabrice Rastello , P Sadayappan

The whole computer hardware industry embraced multicores. For these machines, the extreme optimisation of sequential algorithms is no longer sufficient to squeeze the real machine power, which can be only exploited via thread-level…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-09-21 Marco aldinucci , Salvatore Ruggieri , Massimo Torquati

Hypergraph partitioning is an important preprocessing step for optimizing data placement and minimizing communication volumes in high-performance computing applications. To cope with ever growing problem sizes, it has become increasingly…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-12-15 Lars Gottesbüren , Tobias Heuer , Peter Sanders , Sebastian Schlag

AMD Xilinx's new Versal Adaptive Compute Acceleration Platform (ACAP) is an FPGA architecture combining reconfigurable fabric with other on-chip hardened compute resources. AI engines are one of these and, by operating in a highly…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-01-31 Nick Brown

We present a stable mergesort variant, Multiway Powersort, that exploits existing runs and finds nearly-optimal merging orders for k-way merges with negligible overhead. This builds on Powersort (Munro & Wild, ESA2018), which has recently…

Data Structures and Algorithms · Computer Science 2023-01-18 William Cawley Gelling , Markus E. Nebel , Benjamin Smith , Sebastian Wild

I discuss the new dual-pivot Quicksort that is nowadays used to sort arrays of primitive types in Java. I sketch theoretical analyses of this algorithm that offer a possible, and in my opinion plausible, explanation why (a) dual-pivot…

Data Structures and Algorithms · Computer Science 2016-09-29 Sebastian Wild

Compared to the first generation of deep neural networks, dominated by regular, compute-intensive kernels such as matrix multiplications (MatMuls) and convolutions, modern decoder-based transformers interleave attention, normalization, and…

Hardware Architecture · Computer Science 2026-03-06 Max Wipfli , Gamze İslamoğlu , Navaneeth Kunhi Purayil , Angelo Garofalo , Luca Benini

The emergence and rapid development of the open RISC-V instruction set architecture opens up new horizons on the way to efficient devices, ranging from existing low-power IoT boards to future high-performance servers. The effective use of…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-04-04 Evgeny Kozinov , Evgeny Vasiliev , Andrey Gorshkov , Valentina Kustikova , Artem Maklaev , Valentin Volokitin , Iosif Meyerov

To meet the computational requirements of modern workloads under tight energy constraints, general-purpose accelerator architectures have to integrate an ever-increasing number of extremely area- and energy-efficient processing elements…

Hardware Architecture · Computer Science 2025-11-11 Luca Colagrande , Luca Benini

The ever-growing scale of data parallelism in today's HPC and ML applications presents a big challenge for computing architectures' energy efficiency and performance. Vector processors address the scale-up challenge by decoupling Vector…

Hardware Architecture · Computer Science 2025-08-14 Navaneeth Kunhi Purayil , Matteo Perotti , Tim Fischer , Luca Benini

In this paper, we present FLiMS, a highly-efficient and simple parallel algorithm for merging two sorted lists residing in banked and/or wide memory. On FPGAs, its implementation uses fewer hardware resources than the state-of-the-art…

Hardware Architecture · Computer Science 2022-03-08 Philippos Papaphilippou , Wayne Luk , Chris Brooks

Real-time systems, particularly those used in domains like automated driving, are increasingly adopting neural networks. From this trend arises the need for high-performance hardware exhibiting predictable timing behavior. While…

Hardware Architecture · Computer Science 2026-02-26 Maximilian Kirschner , Konstantin Dudzik , Ben Krusekamp , Jürgen Becker

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

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

Sorting algorithms have attracted a great deal of attention and study, as they have numerous applications to Mathematics, Computer Science and related fields. In this thesis, we first deal with the mathematical analysis of the Quicksort…

Data Structures and Algorithms · Computer Science 2015-10-05 Vasileios Iliopoulos