Evaluating Memory-Hard Proof-of-Work Algorithms on Three Processors
Summary: Benchmarks memory-hard PoW across CPU, GPU, and Intel KNL under varying threads and scratchpad sizes. GPUs consistently dominate; memory-footprint sensitivity motivates CryptoNight with configurable scratchpads as the most egalitarian choice. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zonghao Feng (Hong Kong University of Science and Technology)
- 2. Qiong Luo (Hong Kong University of Science and Technology)
BibTeX Citation
@article{feng_vldb20,
title = {{Evaluating Memory-Hard Proof-of-Work Algorithms on Three Processors}},
author = {Feng, Zonghao and Luo, Qiong},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {6},
pages = {898--911},
doi = {10.14778/3380750.3380759},
url = {https://doi.org/10.14778/3380750.3380759},
year = {2020}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,045 | Do the Rich Get Richer? Fairness Analysis for Blockchain Incentives | 2021 | SIGMOD | 6.3879469e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 478 | BLOCKBENCH: A Framework for Analyzing Private Blockchains | 2017 | SIGMOD | 0.00017829906 |
| 657 | Towards Scaling Blockchain Systems via Sharding | 2019 | SIGMOD | 0.00015236213 |
| 823 | The Yin and Yang of Processing Data Warehousing Queries on GPU Devices | 2013 | VLDB | 0.00013792901 |
| 1,120 | BlockchainDB - A Shared Database on Blockchains | 2019 | VLDB | 0.00012096593 |
| 1,545 | Blockchain Meets Database: Design and Implementation of a Blockchain Relational Database | 2019 | VLDB | 0.00010408717 |
| 2,851 | Fine-Grained, Secure and Efficient Data Provenance on Blockchain Systems | 2019 | VLDB | 8.0462369e-05 |
| 3,208 | ForkBase: An Efficient Storage Engine for Blockchain and Forkable Applications | 2018 | VLDB | 7.635872e-05 |
| 4,171 | Accelerating Dynamic Graph Analytics on GPUs | 2018 | VLDB | 6.8537202e-05 |
| 5,207 | Unifying Consensus and Atomic Commitment for Effective Cloud Data Management | 2019 | VLDB | 6.3171846e-05 |
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