Demo Data from VLDB 2026 / reviewers in the wild / expert
Annemarie Southwell
dblp:304/6358
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none
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 |
GPUs and heterogeneous computing · 77% High-performance computing · 23% | |
| Software engineering, system software, and programming languages
1 paper |
Compilers and program optimization · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Compilers and program optimization › parallelizing compiler
OpenMP compilation |
0.5 | 1 | 2021 | Non-recurring engineering (NRE) best practices: a case study with the NERSC/NVIDIA OpenMP contract · SC 2021 |
GPUs and heterogeneous computing
GPU computing |
0.5 | 1 | 2021 | Non-recurring engineering (NRE) best practices: a case study with the NERSC/NVIDIA OpenMP contract · SC 2021 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Non-recurring engineering (NRE) best practices: a case study with the NERSC/NVIDIA OpenMP contractabstractThe NERSC supercomputer, Perlmutter, consists of AMD CPUs and NVIDIA GPUs. NERSC users expect to be able to use OpenMP to take advantage of the highly capable GPUs. This paper describes how NERSC/NVIDIA constructed a Non-Recurring Engineering (NRE) contract to add OpenMP GPU-offload support to the NVIDIA HPC compilers. The paper describes how the contract incorporated the strengths of both parties and encouraged collaboration to improve the quality of the final deliverable. We include our best practices and how this particular contract took into account emerging OpenMP specifications, NERSC workload requirements, and how to use OpenMP most efficiently on GPU hardware. This paper includes OpenMP application performance results obtained with the NVIDIA compilers distributed in the NVIDIA HPC SDK. Christopher S. Daley, Annemarie Southwell, Rahulkumar Gayatri, Scott Biersdorfff, Craig Toepfer, Güray Özen, Nicholas J. Wright |
SC | 2 |