Demo Data from EDBT 2026 / reviewers in the wild / expert
Charles Bachmeier
dblp:175/6600
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2016
—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 |
Parallel and multicore computing · 100% | |
| Theoretical computer science
1 paper |
Algorithms and data structures · 100% | |
| 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 |
|---|---|---|---|---|
Parallel and multicore computing › parallel algorithms
divide-and-conquer |
0.2 | 1 | 2016 | AUTOGEN: automatic discovery of cache-oblivious parallel recursive algorithms for solving dynamic programs · PPoPP 2016 |
Algorithms and data structures
dynamic programming |
0.2 | 1 | 2016 | AUTOGEN: automatic discovery of cache-oblivious parallel recursive algorithms for solving dynamic programs · PPoPP 2016 |
Methods — techniques the papers use, named apart from their topics
recursive access pattern identification · 0.8automatic algorithm discovery · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | AUTOGEN: automatic discovery of cache-oblivious parallel recursive algorithms for solving dynamic programsabstractWe present AUTOGEN---an algorithm that for a wide class of dynamic programming (DP) problems automatically discovers highly efficient cache-oblivious parallel recursive divide-and-conquer algorithms from inefficient iterative descriptions of DP recurrences. AUTOGEN analyzes the set of DP table locations accessed by the iterative algorithm when run on a DP table of small size, and automatically identifies a recursive access pattern and a corresponding provably correct recursive algorithm for solving the DP recurrence. We use AUTOGEN to autodiscover efficient algorithms for several well-known problems. Our experimental results show that several autodiscovered algorithms significantly outperform parallel looping and tiled loop-based algorithms. Also these algorithms are less sensitive to fluctuations of memory and bandwidth compared with their looping counterparts, and their running times and energy profiles remain relatively more stable. To the best of our knowledge, AUTOGEN is the first algorithm that can automatically discover new nontrivial divide-and-conquer algorithms. Rezaul Alam Chowdhury, Pramod Ganapathi, Jesmin Jahan Tithi, Charles Bachmeier, Bradley C. Kuszmaul, Charles E. Leiserson, Armando Solar-Lezama |
PPoPP | 4 |