HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics
Summary: HetCache co-optimizes data placement and access paths across NVMe, host DRAM and GPU memory for heterogeneous CPU–GPU servers, treating bandwidth/costs as access-path- and device-dependent. Using proportional, access-path-aware caching, it yields 1.14–1.78× speedups on NVMe-resident workloads and near in-memory performance for hybrid CPU–GPU execution while greatly improving memory efficiency. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Hamish Nicholson (EPFL)
- 2. Aunn Raza (EPFL)
- 3. Periklis Chrysogelos (EPFL; Oracle)
- 4. Anastasia Ailamaki (EPFL)
BibTeX Citation
@inproceedings{nicholson_cidr23,
address = {Amsterdam, Netherlands},
series = {{CIDR} '23},
title = {{HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Nicholson, Hamish and Raza, Aunn and Chrysogelos, Periklis and Ailamaki, Anastasia},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,778 | GOLAP: A GPU-in-Data-Path Architecture for High-Speed OLAP | 2024 | SIGMOD | 6.0918646e-05 |
| 7,432 | Powerful GPUs or Fast Interconnects: Analyzing Relational Workloads on Modern GPUs | 2025 | VLDB | 5.6199783e-05 |
| 8,808 | Scaling your Hybrid CPU-GPU DBMS to Multiple GPUs | 2024 | VLDB | 5.3661351e-05 |
| 9,873 | Workload Placement on Heterogeneous CPU-GPU Systems | 2024 | VLDB | 5.2043672e-05 |
| 10,127 | Declarative Memory Services | 2026 | CIDR | 5.093636e-05 |
| 11,200 | High-Performance Query Processing with NVMe Arrays: Spilling without Killing Performance | 2024 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 14 of 14 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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