Demo Data from EDBT 2026 / reviewers in the wild / expert
Carter McCardwell
dblp:174/7108
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 2Software engineering, systems software and programming languages · 1
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 |
Performance modeling and evaluation · 65% GPUs and heterogeneous computing · 35% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Performance modeling and evaluation › processor performance modeling › accelerator performance modeling
GPU performance modeling |
0.4 | 1 | 2019 | MGPUSim: enabling multi-GPU performance modeling and optimization · ISCA 2019 |
Performance modeling and evaluation › simulation › parallel architecture simulation
GPU simulation |
0.4 | 1 | 2019 | MGPUSim: enabling multi-GPU performance modeling and optimization · ISCA 2019 |
GPUs and heterogeneous computing
multi-GPU computing |
0.4 | 1 | 2019 | MGPUSim: enabling multi-GPU performance modeling and optimization · ISCA 2019 |
Performance modeling and evaluation
simulation |
0.4 | 1 | 2019 | MGPUSim: enabling multi-GPU performance modeling and optimization · ISCA 2019 |
GPUs and heterogeneous computing
GPU microarchitecture |
0.1 | 1 | 2019 | MGPUSim: enabling multi-GPU performance modeling and optimization · ISCA 2019 |
GPUs and heterogeneous computing › multi-GPU computing
multi-GPU interconnect |
0.1 | 1 | 2019 | MGPUSim: enabling multi-GPU performance modeling and optimization · ISCA 2019 |
Methods — techniques the papers use, named apart from their topics
simulation · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | MGPUSim: enabling multi-GPU performance modeling and optimizationabstractThe rapidly growing popularity and scale of data-parallel workloads demand a corresponding increase in raw computational power of Graphics Processing Units (GPUs). As single-GPU platforms struggle to satisfy these performance demands, multi-GPU platforms have started to dominate the high-performance computing world. The advent of such systems raises a number of design challenges, including the GPU microarchitecture, multi-GPU interconnect fabric, runtime libraries, and associated programming models. The research community currently lacks a publicly available and comprehensive multi-GPU simulation framework to evaluate next-generation multi-GPU system designs. Yifan Sun 0002, Trinayan Baruah, Saiful A. Mojumder, Shi Dong 0002, Shane Treadway, Yuhui Bao, Spencer Hance, Carter McCardwell, Vincent Zhao, Harrison Barclay, Amir Kavyan Ziabari, Zhongliang Chen, Rafael Ubal, José L. Abellán, John Kim 0001, Ajay Joshi, David R. Kaeli |
ISCA | 9 |
| 2018 | Student cluster competition 2017, team Northeastern University: Reproducing vectorization of the Tersoff multi-body potential on the NVIDIA V100
Z. Marcus, J. Booth, Christopher C. Bunn, M. Leger, Spencer Hance, T. Sweeney, Carter McCardwell, David R. Kaeli |
Parallel Comput. | 7 |