---
title: "HPCA (A*): papers and universities"
description: "HPCA (International Symposium on High Performance Computer Architecture) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 349 of its papers from 2024–2026 (93 in 2024, 133 in 2025, 123 in 2026). By the countries of the authors' institutions, the most papers come from the United States (152), China (127) and South Korea (53)."
url: https://scholar4ai.com/proceedings/hpca
markdown_url: https://scholar4ai.com/proceedings/hpca.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "HPCA (International Symposium on High Performance Computer Architecture) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 349 of its papers from 2024–2026 (93 in 2024, 133 in 2025, 123 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)
---

# HPCA: International Symposium on High Performance Computer Architecture — papers and institutions, 2024–2026

Papers of HPCA, International Symposium on High Performance Computer Architecture (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

- HPCA (International Symposium on High Performance Computer Architecture) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 349 of its papers from 2024–2026 (93 in 2024, 133 in 2025, 123 in 2026).
- By the countries of the authors' institutions, the most papers come from the United States (152), China (127) and South Korea (53).
- The institutions with the most papers are Tsinghua University (31), Shanghai Jiao Tong University (26) and University of Illinois Urbana-Champaign (20).
- Its most-cited paper of these years is “DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency” (2025), with 112 citations.

## Papers per year

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

| Year | Papers | With affiliations |
|---|---:|---:|
| 2024 | 93 | 81 |
| 2025 | 133 | 119 |
| 2026 | 123 | 122 |

## Sources

*Where OpenAlex lists the papers*

| OpenAlex source | Which papers |
|---|---|
| [S4210184388](https://openalex.org/S4210184388) | The conference's proceedings |

## Who publishes there

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

| # | Institution | Papers |
|---:|---|---:|
| 1 | [Tsinghua University](https://scholar4ai.com/institutions/tsinghua-university.md) | 31 |
| 2 | [Shanghai Jiao Tong University](https://scholar4ai.com/institutions/shanghai-jiao-tong-university.md) | 26 |
| 3 | University of Illinois Urbana-Champaign | 20 |
| 4 | [Peking University](https://scholar4ai.com/institutions/peking-university.md) | 19 |
| 5 | [Chinese Academy of Sciences](https://scholar4ai.com/institutions/chinese-academy-of-sciences.md) | 17 |
| 6 | Georgia Institute of Technology | 16 |
| 7 | [Seoul National University](https://scholar4ai.com/institutions/seoul-national-university.md) | 16 |
| 8 | Korea Advanced Institute of Science and Technology | 16 |
| 9 | [Yonsei University](https://scholar4ai.com/institutions/yonsei-university.md) | 14 |
| 10 | ETH Zurich | 14 |

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

| # | Country | Papers |
|---:|---|---:|
| 1 | United States | 152 |
| 2 | China | 127 |
| 3 | South Korea | 53 |
| 4 | Hong Kong | 19 |
| 5 | United Kingdom | 16 |
| 6 | Switzerland | 14 |
| 7 | Singapore | 11 |
| 8 | Spain | 9 |
| 9 | Belgium | 7 |
| 10 | Canada | 7 |

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

| # | Keyword | Papers |
|---:|---|---:|
| 1 | energy efficiency | 70 |
| 2 | in-memory computing | 23 |
| 3 | large language model inference | 20 |
| 4 | hardware-software co-design | 19 |
| 5 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 15 |
| 6 | hardware accelerators | 12 |
| 7 | GPU acceleration | 10 |
| 8 | fully homomorphic encryption | 10 |
| 9 | DRAM | 9 |
| 10 | load balancing | 9 |

## Most-cited papers

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

| # | Citations | Title | Published | Authors |
|---:|---:|---|---|---|
| 1 | 112 | [DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency](https://doi.org/10.1109/hpca61900.2025.00102) | 2025-03-01 | Jovan Stojkovic, Chaojie Zhang, Íñigo Goiri et al. |
| 2 | 69 | [Gemini: Mapping and Architecture Co-exploration for Large-scale DNN Chiplet Accelerators](https://doi.org/10.1109/hpca57654.2024.00022) | 2024-03-02 | Jingwei Cai, Zuotong Wu, Sen Peng et al. |
| 3 | 68 | [An LPDDR-based CXL-PNM Platform for TCO-efficient Inference of Transformer-based Large Language Models](https://doi.org/10.1109/hpca57654.2024.00078) | 2024-03-02 | Sangsoo Park, Kyung-Soo Kim, Jinin So et al. |
| 4 | 62 | [Pathfinding Future PIM Architectures by Demystifying a Commercial PIM Technology](https://doi.org/10.1109/hpca57654.2024.00029) | 2024-03-02 | Bongjoon Hyun, Taehun Kim, Dongjae Lee et al. |
| 5 | 57 | [ECO-CHIP: Estimation of Carbon Footprint of Chiplet-based Architectures for Sustainable VLSI](https://doi.org/10.1109/hpca57654.2024.00058) | 2024-03-02 | Chetan Choppali Sudarshan, Nikhil Matkar, Sarma B. K. Vrudhula et al. |
| 6 | 53 | [SPARK: Scalable and Precision-Aware Acceleration of Neural Networks via Efficient Encoding](https://doi.org/10.1109/hpca57654.2024.00082) | 2024-03-02 | Fangxin Liu, Ning Yang, Haoming Li et al. |
| 7 | 50 | [Lightening-Transformer: A Dynamically-Operated Optically-Interconnected Photonic Transformer Accelerator](https://doi.org/10.1109/hpca57654.2024.00059) | 2024-03-02 | Hanqing Zhu, Jiaqi Gu, Hanrui Wang et al. |
| 8 | 47 | [BitWave: Exploiting Column-Based Bit-Level Sparsity for Deep Learning Acceleration](https://doi.org/10.1109/hpca57654.2024.00062) | 2024-03-02 | Man Shi, Vikram Jain, Antony Joseph et al. |
| 9 | 45 | [MIMDRAM: An End-to-End Processing-Using-DRAM System for High-Throughput, Energy-Efficient and Programmer-Transparent Multiple-Instruction Multiple-Data Computing](https://doi.org/10.1109/hpca57654.2024.00024) | 2024-03-02 | Geraldo Francisco de Oliveira Junior, Ataberk Olgun, A. Giray Yağlıkçı et al. |
| 10 | 45 | [FIGNA: Integer Unit-Based Accelerator Design for FP-INT GEMM Preserving Numerical Accuracy](https://doi.org/10.1109/hpca57654.2024.00064) | 2024-03-02 | Jaeyong Jang, Yulhwa Kim, J.B. Lee et al. |

## Cite this page

Scholar4AI. (2026). HPCA: International Symposium on High Performance Computer Architecture — papers and institutions, 2024–2026. Journal and Conference Research Rankings. Retrieved November 2, 2026, from https://scholar4ai.com/proceedings/hpca

```bibtex
@misc{scholar4ai-proceedings-hpca,
  author = {{Scholar4AI}},
  title = {HPCA: International Symposium on High Performance Computer Architecture — papers and institutions, 2024–2026},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/proceedings/hpca}},
  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/).