---
title: "IPDPS (A): papers and universities"
description: "IPDPS (IEEE International Parallel and Distributed Processing Symposium (was IPPS and SPDP)) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 333 of its papers from 2024–2026 (100 in 2024, 118 in 2025, 115 in 2026). By the countries of the authors' institutions, the most papers come from the United States (160), China (68) and Germany (19)."
url: https://scholar4ai.com/proceedings/ipdps
markdown_url: https://scholar4ai.com/proceedings/ipdps.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "IPDPS (IEEE International Parallel and Distributed Processing Symposium (was IPPS and SPDP)) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 333 of its papers from 2024–2026 (100 in 2024, 118 in… (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)
---

# IPDPS: IEEE International Parallel and Distributed Processing Symposium (was IPPS and SPDP) — papers and institutions, 2024–2026

Papers of IPDPS, IEEE International Parallel and Distributed Processing Symposium (was IPPS and SPDP) (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

- IPDPS (IEEE International Parallel and Distributed Processing Symposium (was IPPS and SPDP)) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 333 of its papers from 2024–2026 (100 in 2024, 118 in 2025, 115 in 2026).
- By the countries of the authors' institutions, the most papers come from the United States (160), China (68) and Germany (19).
- The institutions with the most papers are Argonne National Laboratory (24), The Ohio State University (14) and Pacific Northwest National Laboratory (12).
- Its most-cited paper of these years is “Benchmarking and Dissecting the Nvidia Hopper GPU Architecture” (2024), with 58 citations.
- OpenAlex has affiliations for only 90% of its papers, so the institution and country counts are incomplete.

## Papers per year

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

| Year | Papers | With affiliations |
|---|---:|---:|
| 2024 | 100 | 88 |
| 2025 | 118 | 110 |
| 2026 | 115 | 101 |

## Sources

*Where OpenAlex lists the papers*

| OpenAlex source | Which papers |
|---|---|
| [S4210174069](https://openalex.org/S4210174069) | The conference's proceedings |

## Who publishes there

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

| # | Institution | Papers |
|---:|---|---:|
| 1 | Argonne National Laboratory | 24 |
| 2 | The Ohio State University | 14 |
| 3 | Pacific Northwest National Laboratory | 12 |
| 4 | Georgia Institute of Technology | 11 |
| 5 | University of Iowa | 10 |
| 6 | Lawrence Berkeley National Laboratory | 10 |
| 7 | [National University of Defense Technology](https://scholar4ai.com/institutions/national-university-of-defense-technology.md) | 10 |
| 8 | [Chinese Academy of Sciences](https://scholar4ai.com/institutions/chinese-academy-of-sciences.md) | 10 |
| 9 | University of Delaware | 10 |
| 10 | Institut national de recherche en sciences et technologies du numérique | 9 |

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

| # | Country | Papers |
|---:|---|---:|
| 1 | United States | 160 |
| 2 | China | 68 |
| 3 | Germany | 19 |
| 4 | United Kingdom | 16 |
| 5 | France | 13 |
| 6 | Switzerland | 12 |
| 7 | Spain | 12 |
| 8 | Japan | 8 |
| 9 | Hong Kong | 7 |
| 10 | Italy | 6 |

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

| # | Keyword | Papers |
|---:|---|---:|
| 1 | GPU acceleration | 32 |
| 2 | energy efficiency | 20 |
| 3 | high-performance computing | 18 |
| 4 | scalability | 16 |
| 5 | [graph neural networks](https://scholar4ai.com/keywords/graph-neural-networks.md) | 14 |
| 6 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 14 |
| 7 | exascale computing | 12 |
| 8 | load balancing | 10 |
| 9 | lossy compression | 10 |
| 10 | [federated learning](https://scholar4ai.com/keywords/federated-learning.md) | 9 |

## Most-cited papers

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

| # | Citations | Title | Published | Authors |
|---:|---:|---|---|---|
| 1 | 58 | [Benchmarking and Dissecting the Nvidia Hopper GPU Architecture](https://doi.org/10.1109/ipdps57955.2024.00064) | 2024-05-27 | Weile Luo, Ruibo Fan, Zeyu Li et al. |
| 2 | 22 | [An Optimized Error-controlled MPI Collective Framework Integrated with Lossy Compression](https://doi.org/10.1109/ipdps57955.2024.00072) | 2024-05-27 | Jiajun Huang, Sheng Di, Xiaodong Yu et al. |
| 3 | 19 | [MeanCache: User-Centric Semantic Caching for LLM Web Services](https://doi.org/10.1109/ipdps64566.2025.00117) | 2025-06-03 | Waris Gill, Mohamed Elidrisi, Pallavi Kalapatapu et al. |
| 4 | 19 | [Comparative Study of Large Language Model Architectures on Frontier](https://doi.org/10.1109/ipdps57955.2024.00056) | 2024-05-27 | Junqi Yin, Avishek Bose, Guojing Cong et al. |
| 5 | 18 | [LightDAG: A Low-latency DAG-based BFT Consensus through Lightweight Broadcast](https://doi.org/10.1109/ipdps57955.2024.00093) | 2024-05-27 | Xiaohai Dai, Guanxiong Wang, Jiang Xiao et al. |
| 6 | 16 | [Performance Characterization of CXL Memory and Its Use Cases](https://doi.org/10.1109/ipdps64566.2025.00097) | 2025-06-03 | Xi Wang, Jie Liu, Jianbo Wu et al. |
| 7 | 16 | [Tackling Cold Start in Serverless Computing with Multi-Level Container Reuse](https://doi.org/10.1109/ipdps57955.2024.00017) | 2024-05-27 | Amelie Chi Zhou, Rongzheng Huang, Zhoubin Ke et al. |
| 8 | 15 | [Accelerating Lossy and Lossless Compression on Emerging BlueField DPU Architectures](https://doi.org/10.1109/ipdps57955.2024.00040) | 2024-05-27 | Yuke Li, Arjun Kashyap, Weicong Chen et al. |
| 9 | 13 | [HiCCL: A Hierarchical Collective Communication Library](https://doi.org/10.1109/ipdps64566.2025.00089) | 2025-06-03 | Mert Hidayetoğlu, Simon Garcia de Gonzalo, Elliott Slaughter et al. |
| 10 | 13 | [Optimizing General Matrix Multiplications on Modern Multi-core DSPs](https://doi.org/10.1109/ipdps57955.2024.00090) | 2024-05-27 | Kainan Yu, Xinxin Qi, Peng Zhang et al. |

## Cite this page

Scholar4AI. (2026). IPDPS: IEEE International Parallel and Distributed Processing Symposium (was IPPS and SPDP) — papers and institutions, 2024–2026. Journal and Conference Research Rankings. Retrieved November 2, 2026, from https://scholar4ai.com/proceedings/ipdps

```bibtex
@misc{scholar4ai-proceedings-ipdps,
  author = {{Scholar4AI}},
  title = {IPDPS: IEEE International Parallel and Distributed Processing Symposium (was IPPS and SPDP) — papers and institutions, 2024–2026},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/proceedings/ipdps}},
  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/).