EDBT 2026 Demo / reviewers in the wild / expert
Charles McMillan
dblp:10/2543
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1997
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 first-author
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 |
High-performance computing · 67% Parallel and multicore computing · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Parallel and multicore computing › parallel architecture
massively parallel processing |
0.0 | 1 | 1997 | ASCI Applications · HPDC 1997 |
High-performance computing
multi-physics simulation |
0.0 | 1 | 1997 | ASCI Applications · HPDC 1997 |
High-performance computing
scientific computing systems |
0.0 | 1 | 1997 | ASCI Applications · HPDC 1997 |
Methods — techniques the papers use, named apart from their topics
parallel vector processing · 0.0massively parallel processing · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1997 | ASCI ApplicationsabstractIn discussions of ASCI, the high-profile procurements of large computers frequently figure prominently. However, from the outset of the ASCI program, applications have been recognized as the driver. These applications feature complex, multi-physics simulations of natural phenomena that generate massive data sets as output. As we have moved from computing systems dominated by parallel vector processing to massively parallel processing we have designed new applications from the ground up to take advantage of the new capabilities. Early payoffs from this effort include running problems that are one to two orders of magnitude larger than any we have been able to run in the past. With these larger problems, we are begining the computational exploration of domains in physics, chemistry and engineering that were previously closed. As we write these codes, issues associated with languages, debuggers and visualization tools have quickly risen to the surface. The process of running large problems has strained the computational infrastructure almost to the breaking point but indicates the direction for future work. Charles McMillan |
HPDC | 1 |