VLDB 2026 Research / reviewers in the wild / expert
Ningzhi Ai
dblp:426/4218
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2025
0009-0003-6747-8500ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 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 |
Memory systems · 77% Processor architecture and microarchitecture · 23% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Processor architecture and microarchitecture
latency hiding |
0.9 | 1 | 2025 | RICH Prefetcher: Storing Rich Information in Memory to Trade Capacity and Bandwidth for Latency Hiding · MICRO 2025 |
Memory systems
memory access latency |
0.9 | 1 | 2025 | RICH Prefetcher: Storing Rich Information in Memory to Trade Capacity and Bandwidth for Latency Hiding · MICRO 2025 |
Memory systems › cache
prefetching |
0.9 | 1 | 2025 | RICH Prefetcher: Storing Rich Information in Memory to Trade Capacity and Bandwidth for Latency Hiding · MICRO 2025 |
Memory systems › cache › prefetching
spatial prefetching |
0.9 | 1 | 2025 | RICH Prefetcher: Storing Rich Information in Memory to Trade Capacity and Bandwidth for Latency Hiding · MICRO 2025 |
Memory systems
non-volatile memory |
0.3 | 1 | 2025 | RICH Prefetcher: Storing Rich Information in Memory to Trade Capacity and Bandwidth for Latency Hiding · MICRO 2025 |
Methods — techniques the papers use, named apart from their topics
hierarchical on-chip/off-chip storage · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | RICH Prefetcher: Storing Rich Information in Memory to Trade Capacity and Bandwidth for Latency HidingabstractMemory systems characterized by high bandwidth and/or capacity alongside high access latency are becoming increasingly critical.This trend can be observed both at the device level-for instance, in non-volatile memory-and at the system level, as seen in CXL-based memory pooling architectures.To benefit from such memory in general-purpose computing systems, it is essential to employ techniques that can tolerate high memory access latency.Although prefetching has long been recognized as a classical approach for latency tolerance, conventional prefetching techniques are typically either optimized for area efficiency or constrained by limited prefetching patterns.Consequently, they often fail to convert the abundant metadata into significant performance improvements at minimal cost.To address these challenges, we propose RICH-a prefetcher that strategically consumes memory capacity and bandwidth to reduce memory access latency.First, RICH is capable of leveraging abundant metadata to improve performance by integrating spatial prefetching with diverse region sizes and prefetch triggers.Second, RICH implements such metadata with minimal overheads by employing a hierarchical on-chip/off-chip storage mechanism, thereby avoiding both large on-chip storage and critical off-chip accesses.We propose a specific implementation of RICH and evaluate it across a wide range of workloads.With increased memory latency, RICH achieves performance improvements of 8.3% over Bingo and 6.2% over PMP.This highlights the RICH's suitability for future memory systems.In a conventional system, RICH still outperforms Bingo by 3.4%. Ningzhi Ai, Wenjian He, Hu He 0001, Heng Liao, Guowei Zhang 0002 |
MICRO | 1 |