EDBT 2026 Demo / reviewers in the wild / expert
Ashkan Vedadi Gargary
dblp:378/1250
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2026
0009-0004-2128-5735ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 first-author · 1 since 2021Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021
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 · 67% GPUs and heterogeneous computing · 33% | |
| Databases, data mining, and information retrieval
1 paper |
Data integration and cleaning · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
GPUs and heterogeneous computing
GPU computing |
1.0 | 1 | 2026 | cuJSON: A Highly Parallel JSON Parser for GPUs · ASPLOS (1) 2026 |
Parallel and multicore computing
parallel algorithms |
1.0 | 1 | 2026 | cuJSON: A Highly Parallel JSON Parser for GPUs · ASPLOS (1) 2026 |
Parallel and multicore computing › parallel algorithms › parallel string algorithms
parallel parsing |
1.0 | 1 | 2026 | cuJSON: A Highly Parallel JSON Parser for GPUs · ASPLOS (1) 2026 |
Data integration and cleaning › data transformation
data parsing |
0.3 | 1 | 2026 | cuJSON: A Highly Parallel JSON Parser for GPUs · ASPLOS (1) 2026 |
Methods — techniques the papers use, named apart from their topics
branch-minimizing parallel parsing · 2.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | cuJSON: A Highly Parallel JSON Parser for GPUsabstractJSON (JavaScript Object Notation) data is widely used in modern computing, yet its parsing performance can be a major bottleneck. Conventional wisdom suggests that GPUs are ill-suited for parsing due to the branch-heavy nature of parsing algorithms. This work challenges that notion by presenting cuJSON, a novel JSON parser built on a new parsing algorithm, specifically tailored for GPU architectures with minimal branching and maximal parallelism. Ashkan Vedadi Gargary, Soroosh Safari Loaliyan, Zhijia Zhao 0001 |
ASPLOS (1) | 1 |