EDBT 2026 Demo / reviewers in the wild / expert
Doug James
dblp:155/9969
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 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 |
Storage systems · 70% High-performance computing · 30% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Storage systems › file systems › distributed file system
parallel file system |
0.2 | 1 | 2014 | A User-Friendly Approach for Tuning Parallel File Operations · SC 2014 |
High-performance computing
parallel i/o |
0.2 | 1 | 2014 | A User-Friendly Approach for Tuning Parallel File Operations · SC 2014 |
Storage systems › i/o optimization
parallel i/o optimization |
0.2 | 1 | 2014 | A User-Friendly Approach for Tuning Parallel File Operations · SC 2014 |
Storage systems › file systems › distributed file system › parallel file system
lustre file system |
0.1 | 1 | 2014 | A User-Friendly Approach for Tuning Parallel File Operations · SC 2014 |
Methods — techniques the papers use, named apart from their topics
performance modeling · 0.2auto-tuning library · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | A User-Friendly Approach for Tuning Parallel File OperationsabstractThe Lustre file system provides high aggregated I/O bandwidth and is in widespread use throughout the HPC community. Here we report on work (1) developing a model for understanding collective parallel MPI write operations on Lustre, and (2) producing a library that optimizes parallel write performance in a user-friendly way. We note that a system's default stripe count is rarely a good choice for parallel I/O, and that performance depends on a delicate balance between the number of stripes and the actual (not requested) number of collective writers. Unfortunate combinations of these parameters may degrade performance considerably. For the programmer, however, it's all about the stripe count: an informed choice of this single parameter allows MPI to assign writers in a way that achieves near-optimal performance. We offer recommendations for those who wish to tune performance manually and describe the easy-to-use T3PIO library that manages the tuning automatically. Robert T. McLay, Doug James, Si Liu 0008, John Cazes, William L. Barth |
SC | 2 |