EDBT 2026 Demo / reviewers in the wild / expert
Juechu Dong
dblp:390/7634
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2026
0000-0002-8855-9962ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 2 · 1 first-author · 2 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
2 papers |
Memory systems · 70% GPUs and heterogeneous computing · 30% | |
| Artificial intelligence
1 paper |
Efficient and distributed learning · 100% | |
| Network and information security
1 paper |
Hardware security and side channels · 50% Authentication and access control · 50% |
Topics — the 8 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Efficient and distributed learning › inference efficiency
inference optimization |
1.0 | 1 | 2026 | Accelerating Block Low-Rank Foundation Model Inference on Memory-Constrained GPUs · HPDC 2026 |
Machine learning › Efficient and distributed learning › inference efficiency
memory-efficient inference |
1.0 | 1 | 2026 | Accelerating Block Low-Rank Foundation Model Inference on Memory-Constrained GPUs · HPDC 2026 |
GPUs and heterogeneous computing
GPU memory management |
1.0 | 1 | 2026 | Accelerating Block Low-Rank Foundation Model Inference on Memory-Constrained GPUs · HPDC 2026 |
Memory systems › processing-in-memory
intelligent memory |
0.8 | 1 | 2024 | Toleo: Scaling Freshness to Tera-scale Memory Using CXL and PIM · ASPLOS (4) 2024 |
Memory systems › secure memory
memory integrity |
0.8 | 1 | 2024 | Toleo: Scaling Freshness to Tera-scale Memory Using CXL and PIM · ASPLOS (4) 2024 |
Memory systems
processing-in-memory |
0.8 | 1 | 2024 | Toleo: Scaling Freshness to Tera-scale Memory Using CXL and PIM · ASPLOS (4) 2024 |
Authentication and access control
replay attack prevention |
0.2 | 1 | 2024 | Toleo: Scaling Freshness to Tera-scale Memory Using CXL and PIM · ASPLOS (4) 2024 |
Hardware security and side channels
trusted execution environments |
0.2 | 1 | 2024 | Toleo: Scaling Freshness to Tera-scale Memory Using CXL and PIM · ASPLOS (4) 2024 |
Methods — techniques the papers use, named apart from their topics
foundation model inference · 2.0block low-rank approximation · 2.0merkle tree · 1.5CXL · 1.5version numbers · 0.8version number · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Accelerating Block Low-Rank Foundation Model Inference on Memory-Constrained GPUs
Pierre Abillama, Changwoo Lee 0001, Juechu Dong, David T. Blaauw, Dennis Sylvester, Hun-Seok Kim |
HPDC | 3 |
| 2024 | Toleo: Scaling Freshness to Tera-scale Memory Using CXL and PIMabstractTrusted hardware's freshness guarantee ensures that an adversary cannot replay an old value in response to a memory read request. They rely on maintaining a version number for each cache block and ensuring their integrity using a Merkle tree. However, these existing solutions protect only a small amount of main memory (few MBs), as the extraneous memory accesses to the Merkle tree increase prohibitively with the protected memory size. We present Toleo, which uses trusted smart memory connected through a secure CXL IDE network to safely store version numbers. Toleo eliminates the need for an unscalable Merkle tree to protect the integrity of version numbers by instead using smart memory as the root of trust. Additionally, Toleo ensures version confidentiality which enables stealth versions that reduce the version storage overhead in half. Juechu Dong, Jonah Rosenblum, Satish Narayanasamy |
ASPLOS (4) | 1 |