---
title: "SC (A): papers and universities"
description: "SC (International Conference for High Performance Computing, Networking, Storage and Analysis (was Supercomputing Conference)) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 812 of its papers from 2024–2026 (379 in 2024, 433 in 2025; 2026 not in OpenAlex yet). By the countries of the authors' institutions, the most papers come from the United States (506), China (96) and Germany (72)."
url: https://scholar4ai.com/proceedings/sc
markdown_url: https://scholar4ai.com/proceedings/sc.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "SC (International Conference for High Performance Computing, Networking, Storage and Analysis (was Supercomputing Conference)) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 812 of its papers… (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)
---

# SC: International Conference for High Performance Computing, Networking, Storage and Analysis (was Supercomputing Conference) — papers and institutions, 2024–2026

Papers of SC, International Conference for High Performance Computing, Networking, Storage and Analysis (was Supercomputing Conference) (CORE rank A; field: Computer science (general), Distributed computing and systems software), 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

- SC (International Conference for High Performance Computing, Networking, Storage and Analysis (was Supercomputing Conference)) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 812 of its papers from 2024–2026 (379 in 2024, 433 in 2025; 2026 not in OpenAlex yet).
- By the countries of the authors' institutions, the most papers come from the United States (506), China (96) and Germany (72).
- The institutions with the most papers are Argonne National Laboratory (90), Oak Ridge National Laboratory (87) and Lawrence Berkeley National Laboratory (44).
- Its most-cited paper of these years is “LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators” (2024), with 40 citations.

## Papers per year

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

| Year | Papers | With affiliations |
|---|---:|---:|
| 2024 | 379 | 333 |
| 2025 | 433 | 432 |
| 2026 | – | – |

## Sources

*Where OpenAlex lists the papers*

| OpenAlex source | Which papers |
|---|---|
| [S4363608557](https://openalex.org/S4363608557) | The conference's proceedings |

## Who publishes there

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

| # | Institution | Papers |
|---:|---|---:|
| 1 | Argonne National Laboratory | 90 |
| 2 | Oak Ridge National Laboratory | 87 |
| 3 | Lawrence Berkeley National Laboratory | 44 |
| 4 | Lawrence Livermore National Laboratory | 32 |
| 5 | Los Alamos National Laboratory | 26 |
| 6 | ETH Zurich | 26 |
| 7 | Nvidia (United States) | 25 |
| 8 | [Chinese Academy of Sciences](https://scholar4ai.com/institutions/chinese-academy-of-sciences.md) | 22 |
| 9 | University of Chicago | 22 |
| 10 | RIKEN Center for Computational Science | 21 |

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

| # | Country | Papers |
|---:|---|---:|
| 1 | United States | 506 |
| 2 | China | 96 |
| 3 | Germany | 72 |
| 4 | United Kingdom | 38 |
| 5 | Japan | 38 |
| 6 | Switzerland | 35 |
| 7 | France | 24 |
| 8 | Italy | 20 |
| 9 | Spain | 16 |
| 10 | Sweden | 15 |

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

| # | Keyword | Papers |
|---:|---|---:|
| 1 | high-performance computing | 104 |
| 2 | GPU acceleration | 52 |
| 3 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 47 |
| 4 | energy efficiency | 35 |
| 5 | scalability | 35 |
| 6 | reproducibility | 33 |
| 7 | performance portability | 32 |
| 8 | exascale computing | 29 |
| 9 | load balancing | 21 |
| 10 | OpenMP | 20 |

## Most-cited papers

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

| # | Citations | Title | Published | Authors |
|---:|---:|---|---|---|
| 1 | 40 | [LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators](https://doi.org/10.1109/scw63240.2024.00178) | 2024-11-17 | Krishna Teja Chitty-Venkata, Siddhisanket Raskar, Bharat Kale et al. |
| 2 | 40 | [Accurate and Convenient Energy Measurements for GPUs: A Detailed Study of NVIDIA GPU’s Built-In Power Sensor](https://doi.org/10.1109/sc41406.2024.00028) | 2024-11-17 | Zeyu Yang, Karel Adámek, Wesley Armour |
| 3 | 29 | [CUSZP2: A GPU Lossy Compressor with Extreme Throughput and Optimized Compression Ratio](https://doi.org/10.1109/sc41406.2024.00021) | 2024-11-17 | Yafan Huang, Sheng Di, Guanpeng Li et al. |
| 4 | 25 | [Boosting Earth System Model Outputs And Saving PetaBytes in Their Storage Using Exascale Climate Emulators](https://doi.org/10.1109/sc41406.2024.00008) | 2024-11-17 | Sameh Abdulah, Allison H. Baker, George Bosilca A et al. |
| 5 | 24 | [Exploring GPU-to-GPU Communication: Insights into Supercomputer Interconnects](https://doi.org/10.1109/sc41406.2024.00039) | 2024-11-17 | Daniele De Sensi, Lorenzo Pichetti, Flavio Vella et al. |
| 6 | 23 | [A Digital Twin Framework for Liquid-cooled Supercomputers as Demonstrated at Exascale](https://doi.org/10.1109/sc41406.2024.00029) | 2024-11-17 | Wesley H. Brewer, Matthias Maiterth, Vineet Kumar et al. |
| 7 | 21 | [ParvaGPU: Efficient Spatial GPU Sharing for Large-Scale DNN Inference in Cloud Environments](https://doi.org/10.1109/sc41406.2024.00048) | 2024-11-17 | Munkyu Lee, Sihoon Seong, Minki Kang et al. |
| 8 | 21 | [Fire-Flyer AI-HPC: A Cost-Effective Software-Hardware Co-Design for Deep Learning](https://doi.org/10.1109/sc41406.2024.00089) | 2024-11-17 | Wei An, Xiao Bi, Guan-Ting Chen et al. |
| 9 | 20 | [Breaking the Million-Electron and 1 EFLOP/s Barriers: Biomolecular-Scale Ab Initio Molecular Dynamics Using MP2 Potentials](https://doi.org/10.1109/sc41406.2024.00015) | 2024-11-17 | Ryan Stocks, Jorge Luis Galvez Vallejo, Fiona Yu et al. |
| 10 | 19 | [AmgT: Algebraic Multigrid Solver on Tensor Cores](https://doi.org/10.1109/sc41406.2024.00058) | 2024-11-17 | Yuechen Lu, Lijie Zeng, Tengcheng Wang et al. |

## Cite this page

Scholar4AI. (2026). SC: International Conference for High Performance Computing, Networking, Storage and Analysis (was Supercomputing Conference) — papers and institutions, 2024–2026. Journal and Conference Research Rankings. Retrieved November 2, 2026, from https://scholar4ai.com/proceedings/sc

```bibtex
@misc{scholar4ai-proceedings-sc,
  author = {{Scholar4AI}},
  title = {SC: International Conference for High Performance Computing, Networking, Storage and Analysis (was Supercomputing Conference) — papers and institutions, 2024–2026},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/proceedings/sc}},
  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/).