Demo Data from EDBT 2026 / reviewers in the wild / expert
Richard P. Boardman
dblp:26/790
· DBLP profile ↗
5ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0002-4008-0098ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 3 · 1 since 2021Databases, data management, data science and information retrieval · 2
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
2 papers |
High-performance computing · 74% Parallel and multicore computing · 24% Distributed systems · 2% |
Topics — the 5 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
High-performance computing
domain decomposition |
0.5 | 1 | 2021 | Scalable FBP decomposition for cone-beam CT reconstruction · SC 2021 |
Parallel and multicore computing
parallel programming models |
0.5 | 1 | 2021 | Scalable FBP decomposition for cone-beam CT reconstruction · SC 2021 |
High-performance computing
scientific computing systems |
0.5 | 1 | 2021 | Scalable FBP decomposition for cone-beam CT reconstruction · SC 2021 |
High-performance computing › scientific computing systems
X-ray CT reconstruction |
0.5 | 1 | 2021 | Scalable FBP decomposition for cone-beam CT reconstruction · SC 2021 |
Distributed systems
grid computing |
0.0 | 1 | 2002 | Grid Services in Action: Grid Enabled Optimisation and Design Search · HPDC 2002 |
Methods — techniques the papers use, named apart from their topics
filtered backprojection · 0.5optimization · 0.0design search · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Scalable FBP decomposition for cone-beam CT reconstructionabstractFiltered Back-Projection (FBP) is a fundamental compute intense algorithm used in tomographic image reconstruction. Cone-Beam Computed Tomography (CBCT) devices use a cone-shaped X-ray beam, in comparison to the parallel beam used in older CT generations. Distributed image reconstruction of cone-beam datasets typically relies on dividing batches of images into different nodes. This simple input decomposition, however, introduces limits on input/output sizes and scalability. Peng Chen 0035, Mohamed Wahib, Xiao Wang 0004, Takahiro Hirofuchi, Hirotaka Ogawa, Ander Biguri, Richard P. Boardman, Thomas Blumensath, Satoshi Matsuoka |
SC | 7 |
| 2020 | Arbitrarily large tomography with iterative algorithms on multiple GPUs using the TIGRE toolbox
Ander Biguri, Reuben Lindroos, Robert Bryll, Hossein Towsyfyan, Hans Deyhle, Ibrahim El Khalil Harrane, Richard P. Boardman, Mark Mavrogordato, Manjit Dosanjh, Steven Hancock, Thomas Blumensath |
J. Parallel Distributed Comput. | 7 |
| 2014 | A framework for user driven data management
Mark Scott, Richard P. Boardman, Philippa A. Reed, Tim Austin, Steven J. Ossont, Kenji Takeda, Simon J. Cox 0001 |
Inf. Syst. | 2 |
| 2014 | Managing heterogeneous datasets
Mark Scott, Richard P. Boardman, Philippa A. Reed, Simon J. Cox 0001 |
Inf. Syst. | 2 |
| 2002 | Grid Services in Action: Grid Enabled Optimisation and Design SearchabstractWe are developing a Grid Enabled Optimisation and Design Search system (GEODISE). It offers grid-based access to a state-of-the-art collection of optimisation and design search tools, industrial strength analysis codes, and distributed computing and data resources. Simon J. Cox 0001, Richard P. Boardman, Liming Chen 0001, Mihai C. Duta, Murat Hakki Eres, Matt J. Fairman, Zhuoan Jiao, Michael B. Giles, Carole A. Goble, Graeme E. Pound, Andy J. Keane, Mark Scott, Nigel Shadbolt, Feng Tao 0001, Jasmin L. Wason |
HPDC | 2 |