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Jassim M. Aljuraidan

dblp:419/8072 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0009-0451-0298ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Hardware accelerators and domain-specific architectures · 30% Interconnection networks and networks-on-chip · 30% Reconfigurable computing and FPGAs · 30%

Topics — the 3 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Reconfigurable computing and FPGAs › FPGA accelerator
FPGA-based sorting
0.912025
Competition-Style Sorting Networks (CSN): A Framework for Hardware-Based Sorting Operations · IEEE Trans. Computers 2025
Hardware accelerators and domain-specific architectures › domain-specific accelerator
sorting accelerator
0.912025
Competition-Style Sorting Networks (CSN): A Framework for Hardware-Based Sorting Operations · IEEE Trans. Computers 2025
Interconnection networks and networks-on-chip
sorting network
0.912025
Competition-Style Sorting Networks (CSN): A Framework for Hardware-Based Sorting Operations · IEEE Trans. Computers 2025

Methods — techniques the papers use, named apart from their topics

pairwise comparison network · 0.9bitonic sort · 0.9
YearPublicationVenuePosition
2025 Competition-Style Sorting Networks (CSN): A Framework for Hardware-Based Sorting Operations
abstract
Sorting operations are considered to be a significant part of any computer system and are widely used in many applications. In applications where sorting has to be efficiently accomplished (i.e., inO(1) time) on small-sized entries, hardware accelerators, such as ASICs, FPGAs, or GPUs, are used to speed up the sorting operations. In the literature, the bitonic sort algorithm (or variants thereof) is still considered to be the most commonly used approach in many hardware sort implementations for decades. However, the time complexity of the bitonic sort isO((log(n))2) for sortingnelements, which does not satisfy the constant-time constraint we demand for our setting. In this paper, we proposecompetition-style sorting networks(CSNs), a framework for designing hardware-based competition-style class of sorting networks that captures all forms of two-stage sorting networks where the first stage (competition) consists of pairwise comparisons and the second stage (evaluation) ranks the entries and sorts them. To illustrate the utility of this framework, we develop and test one instance of this design, called the Competition Sort Algorithm (CSA), which has a time complexity ofO(1), and specifically, one clock cycle. We implemented and tested CSA on both an Intel Cyclone V FPGA and the NVIDIA Quadro T1000 GPU then measured itsgain, which combines the trade-offs between the relative speedup and the relative area increase, against the bitonic sort. Our results show that the CSA achieves a significant gain of up to 11.01× on the FPGA and a relative speedup of up to 3.32× on the GPU. We also compare the area, power, and latency of CSA with the bitonic sort algorithm on the FPGA.
Abbas A. Fairouz, Jassim M. Aljuraidan, Ameer Mohammed
IEEE Trans. Computers2