---
title: "HPDC (A): papers and universities"
description: "HPDC (ACM International Symposium on High Performance Distributed Computing) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 194 of its papers from 2024–2026 (47 in 2024, 52 in 2025, 95 in 2026). By the countries of the authors' institutions, the most papers come from the United States (102), China (31) and Italy (24)."
url: https://scholar4ai.com/proceedings/hpdc
markdown_url: https://scholar4ai.com/proceedings/hpdc.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "HPDC (ACM International Symposium on High Performance Distributed Computing) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 194 of its papers from 2024–2026 (47 in 2024, 52 in 2025, 95 in 2026). (as of 2026-11-02)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-02T12:20:52+09:00
window: 2026-10-04 to 2026-11-02
source: OpenAlex (CC0)
---

# HPDC: ACM International Symposium on High Performance Distributed Computing — papers and institutions, 2024–2026

Papers of HPDC, ACM International Symposium on High Performance Distributed Computing (CORE rank A; field: Distributed computing and systems software, Computer science (general)), 2024–2026: per year, the institutions, countries and topics, and the most-cited papers. Ranks are those of the CORE Conference Rankings, edition ICORE2026 (portal.core.edu.au), applied to every year shown. Papers are the works OpenAlex lists for the conference's proceedings, or for the issues of a conference-linked journal that publishes its papers (such as PACMPL, PVLDB or ACM TOG), by publication year; workshops, companion volumes, posters and Findings are left out. A paper counts once for each institution and country among its authors' affiliations as OpenAlex assigns them; papers without affiliations in OpenAlex count for none. For conferences published in book series that OpenAlex files as one source (LNCS, LIPIcs, SIAM and IOS Press proceedings), the papers are found by DOI: those of the volumes with the conference's title in Crossref, or LIPIcs DOIs, which name the conference. Conferences without DOIs (PMLR, USENIX, OpenReview) are listed without counts. A dash (–) for a year means OpenAlex has no papers of the conference for it yet: the proceedings are not published or indexed yet, or the conference did not meet that year (some meet every other year). 2026 counts what OpenAlex had indexed by 2026-11-02.

All conferences: https://scholar4ai.com/proceedings.md

## Key findings

- HPDC (ACM International Symposium on High Performance Distributed Computing) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 194 of its papers from 2024–2026 (47 in 2024, 52 in 2025, 95 in 2026).
- By the countries of the authors' institutions, the most papers come from the United States (102), China (31) and Italy (24).
- The institutions with the most papers are Argonne National Laboratory (17), Chinese Academy of Sciences (12) and Lawrence Livermore National Laboratory (10).
- Its most-cited paper of these years is “DataStates-LLM: Lazy Asynchronous Checkpointing for Large Language Models” (2024), with 37 citations.

## Papers per year

*HPDC papers per publication year in OpenAlex (–: not in OpenAlex yet)*

| Year | Papers | With affiliations |
|---|---:|---:|
| 2024 | 47 | 45 |
| 2025 | 52 | 51 |
| 2026 | 95 | 95 |

## Sources

*Where OpenAlex lists the papers*

| OpenAlex source | Which papers |
|---|---|
| [S7407087987](https://openalex.org/S7407087987) | The conference's proceedings |

## Who publishes there

*Institutions with the most HPDC papers, 2024–2026*

| # | Institution | Papers |
|---:|---|---:|
| 1 | Argonne National Laboratory | 17 |
| 2 | [Chinese Academy of Sciences](https://scholar4ai.com/institutions/chinese-academy-of-sciences.md) | 12 |
| 3 | Lawrence Livermore National Laboratory | 10 |
| 4 | University of Catania | 9 |
| 5 | Institute of Computing Technology | 9 |
| 6 | [University of Chinese Academy of Sciences](https://scholar4ai.com/institutions/university-of-chinese-academy-of-sciences.md) | 7 |
| 7 | [Shanghai Jiao Tong University](https://scholar4ai.com/institutions/shanghai-jiao-tong-university.md) | 6 |
| 8 | Case Western Reserve University | 6 |
| 9 | [University of Tennessee at Knoxville](https://scholar4ai.com/institutions/university-of-tennessee-at-knoxville.md) | 6 |
| 10 | University of Chicago | 5 |

*Countries with the most HPDC papers, 2024–2026*

| # | Country | Papers |
|---:|---|---:|
| 1 | United States | 102 |
| 2 | China | 31 |
| 3 | Italy | 24 |
| 4 | Germany | 9 |
| 5 | India | 9 |
| 6 | South Korea | 7 |
| 7 | Spain | 6 |
| 8 | Japan | 6 |
| 9 | United Kingdom | 5 |
| 10 | Greece | 4 |

*Keywords with the most HPDC papers, 2024–2026*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | high-performance computing | 13 |
| 2 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 10 |
| 3 | edge computing | 9 |
| 4 | resource allocation | 8 |
| 5 | serverless computing | 8 |
| 6 | fault tolerance | 7 |
| 7 | load balancing | 7 |
| 8 | GPU acceleration | 6 |
| 9 | Grover's algorithm | 6 |
| 10 | lossy compression | 6 |

## Most-cited papers

*Most-cited HPDC papers of 2024–2026 (citations counted by OpenAlex)*

| # | Citations | Title | Published | Authors |
|---:|---:|---|---|---|
| 1 | 37 | [DataStates-LLM: Lazy Asynchronous Checkpointing for Large Language Models](https://doi.org/10.1145/3625549.3658685) | 2024-06-03 | Avinash Maurya, Robert Underwood, M. Mustafa Rafique et al. |
| 2 | 33 | [Can Large Language Models Write Parallel Code?](https://doi.org/10.1145/3625549.3658689) | 2024-06-03 | Daniel Nichols, Joshua Hoke Davis, Zhaojun Xie et al. |
| 3 | 15 | [CarbonEdge: Leveraging Mesoscale Spatial Carbon-Intensity Variations for Low Carbon Edge Computing](https://doi.org/10.1145/3731545.3731576) | 2025-07-20 | Wu Li, Walid A. Hanafy, Abel Souza et al. |
| 4 | 14 | [CereSZ: Enabling and Scaling Error-bounded Lossy Compression on Cerebras CS-2](https://doi.org/10.1145/3625549.3658691) | 2024-06-03 | Shihui Song, Yafan Huang, Peng Jiang et al. |
| 5 | 11 | [ESG: Pipeline-Conscious Efficient Scheduling of DNN Workflows on Serverless Platforms with Shareable GPUs](https://doi.org/10.1145/3625549.3658657) | 2024-06-03 | Xinning Hui, Yuanchao Xu, Zhishan Guo et al. |
| 6 | 9 | [IDT: Intelligent Data Placement for Multi-tiered Main Memory with Reinforcement Learning](https://doi.org/10.1145/3625549.3658659) | 2024-06-03 | Juneseo Chang, Wanju Doh, Yaebin Moon et al. |
| 7 | 8 | [IPComp: Interpolation Based Progressive Lossy Compression for Scientific Applications](https://doi.org/10.1145/3731545.3731578) | 2025-07-20 | Zhuoxun Yang, Sheng Di, Longtao Zhang et al. |
| 8 | 8 | [Near-Optimal Wafer-Scale Reduce](https://doi.org/10.1145/3625549.3658693) | 2024-06-03 | Piotr Łuczyński, Lukas Gianinazzi, Patrick Iff et al. |
| 9 | 8 | [Loki: A System for Serving ML Inference Pipelines with Hardware and Accuracy Scaling](https://doi.org/10.1145/3625549.3658688) | 2024-06-03 | Sohaib Ahmad, Hui Guan, Ramesh K. Sitaraman |
| 10 | 7 | [DPU-KV: On the Benefits of DPU Offloading for In-Memory Key-Value Stores at the Edge](https://doi.org/10.1145/3731545.3731571) | 2025-07-20 | Arjun Kashyap, Yuke Li, Xiaoyi Lu |

## Cite this page

Scholar4AI. (2026). HPDC: ACM International Symposium on High Performance Distributed Computing — papers and institutions, 2024–2026. Journal and Conference Research Rankings. Retrieved November 2, 2026, from https://scholar4ai.com/proceedings/hpdc

```bibtex
@misc{scholar4ai-proceedings-hpdc,
  author = {{Scholar4AI}},
  title = {HPDC: ACM International Symposium on High Performance Distributed Computing — papers and institutions, 2024–2026},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/proceedings/hpdc}},
  urldate = {2026-11-02},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).