Evidence map›Paper›PMID 42553158›Full record

ArticleEngineering with computers2026

Distributed semi-speculative parallel anisotropic mesh adaptation.

Kevin Garner, Polykarpos Thomadakis, Nikos Chrisochoides

Abstract read
In one paragraph

Article in Engineering with computers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Kevin GarnerCenter for Real-time Computing, Department of Computer Science, Old Dominion University, Norfolk, VA USA.ORCID https://orcid.org/0000-0003-4138-1017
Polykarpos ThomadakisCenter for Real-time Computing, Department of Computer Science, Old Dominion University, Norfolk, VA USA.
Nikos ChrisochoidesCenter for Real-time Computing, Department of Computer Science, Old Dominion University, Norfolk, VA USA.

Funding

G-RISE at Old Dominion UniversityT32GM140911 · NIGMS · OLD DOMINION UNIVERSITY · PI NAWARATHNA, DHARMAKEERTHI · 2021 to 2024
$1.3M
NIGMS NIH HHS T32 GM140911
6 · The paper itself

Abstract

This paper presents a distributed memory method for anisotropic mesh adaptation that is designed to avoid the use of collective communication and global synchronization techniques. In the presented method, meshing functionality is separated from performance aspects by utilizing a separate entity for each - a multicore cc-NUMA-based (shared memory) mesh generation software and a parallel runtime system that is designed to help applications leverage the concurrency offered by emerging high-performance computing (HPC) architectures. First, an initial mesh is decomposed and its interface elements (subdomain boundaries) are adapted on a single multicore node (shared memory). Subdomains are then distributed among the nodes of an HPC cluster so that their interior elements are adapted while interface elements (already adapted) remain frozen to maintain mesh conformity. Lessons are presented regarding some re-designs of the shared memory software and how its speculative execution model is utilized by the distributed memory method to achieve good performance. The presented method is shown to generate meshes (of up to approximately 1 billion elements) with comparable quality and performance to existing state-of-the-art HPC meshing software.

Indexed as

Anisotropic mesh adaptationDistributed memoryHigh-performance computingShared memory

Identifiers

PMID42553158
PMCPMC13433493

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.