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CLUSTER 2026: IEEE International Conference on Cluster Computing

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CLUSTER
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투고 마감일:
2026-04-23
통보일:
2026-07-05
개최일:
2026-09-22
개최지:
Alexandria, Virginia, USA
개최 횟수:
28
CCF: B   ICORE: C   조회: 135550   팔로우: 116   참가: 19

회반 지수 (CP-I)

78.7 / 100
전체 5,682개 중 217위 · 상위 4%

시스템·아키텍처 분야 341개 중 43위

학술적 인정 (35%)
82
투고 선별성 (20%)
74
개최 횟수 (20%)
91
커뮤니티 관심도 (10%)
72
공개 자료 충실도 (15%)
65

사용한 입력: 수록 등급: CCF B, ICORE C · 게재율: 33.2%(기록이 있는 5개 회차의 평균) · 확인되는 개최 횟수: 28 · 회반에서 팔로우 중인 연구자: 116명 · 지난 24개월 동안 이 페이지를 연 연구자: 32명

공개 자료에서 빠진 항목: 역대 회차 (+3.0) · 최우수 논문 기록 (+2.3)
주최자는 학회를 인증 신청한 뒤 이 페이지에서 바로 추가할 수 있습니다. 점수는 매일 밤 다시 계산됩니다. 이 점수를 올리는 방법

신뢰도 100% — 점수 중 중립 기준값이 아니라 실제 관측된 데이터에 근거한 비율. 이 점수는 어떻게 계산되나 · 전체 순위 보기 · 알고리즘 버전 1.1 · 산출일 2026-09-20

논문 모집

CLUSTER 2026 (IEEE International Conference on Cluster Computing) is a CCF B / ICORE C conference held in Alexandria, Virginia, USA on 2026-09-22. The paper submission deadline is 2026-04-23. Acceptance notifications are sent on 2026-07-05.

IEEE Cluster 2026 is the 28th edition of the IEEE Cluster conference series. It is being held in cooperation with SIGHPC. Computing clusters remain the primary system architecture for building many of today’s rapidly evolving computing infrastructures including high-performance computing, cloud computing, machine learning training and inference systems, and big data, and are used to solve some of the most complex problems. The challenges posed making them scalable, efficient, productive, and increasingly effective require community efforts in the areas of cluster system design, advancing the capabilities of the software stack, system management and monitoring, and the design of algorithms, methods, and applications to leverage the overall infrastructure. For IEEE Cluster 2026, which will be held September 22-25, 2026 in Alexandria, Virginia, United States of America, we again solicit high-quality original work that advances the state-of-the-art in clusters and closely related fields. All papers will be rigorously peer-reviewed for their originality, technical depth and correctness, potential impact, relevance to the conference, and quality of presentation. Generally research papers must clearly demonstrate novel research contributions, however papers reporting experiences are also welcome, but they must clearly describe the lessons learned and the resulting impact, along with the utility of the approach in comparison to previous work. Authors must indicate the primary topic area of their submissions from the four topic areas provided below. In addition, they may optionally rank their paper relative to the overall set of topics. Transversal and emerging topics such as AI for HPC, HPC for AI, quantum computing, accelerators, and many others, are welcome within the respective areas even if they are not mentioned explicitly. Papers are limited to 10 pages, although references do not need to fit within this page limit. IEEE Cluster 2026 follows a dual-anonymous review process. For an explanation and description of this review process, please refer to the following link: https://clustercomp.org/2026/dual_anonymous.html Guidelines for Artificial Intelligence (AI)-Generated Text The use of content generated by artificial intelligence (AI) in a paper (including but not limited to text, figures, images, and code) shall be disclosed in the acknowledgments section of any paper submitted to an IEEE publication. The AI system used shall be identified, and specific sections of the paper that use AI-generated content shall be identified and accompanied by a brief explanation regarding the level at which the AI system was used to generate the content. The use of AI systems for editing and grammar enhancement is common practice and, as such, is generally outside the intent of the above policy. In this case, disclosure as noted above is recommended. Please also refer to the IEEE Submission Policies Area 1: Application, Algorithms, and Libraries HPC and Big Data application studies on large-scale clusters Applications at the boundary of HPC and Big Data New applications for converged HPC/Big Data clusters Application-level performance and energy modeling and measurement Novel algorithms on clusters Hybrid programming techniques in applications and libraries (e.g., MPI+X) Cluster benchmarks Application-level libraries on clusters Effective use of clusters in novel applications Performance evaluation tools Area 2: Architecture, Network/Communications, and Management Node and system architecture for HPC and Big Data clusters Architecture for converged HPC/Big Data clusters Energy-efficient cluster architectures Packaging, power and cooling Accelerators, reconfigurable and domain-specific hardware Heterogeneous clusters Interconnect/memory architectures Single system/distributed image clusters Administration, monitoring and maintenance tools Area 3: Programming and System Software Cluster system software/operating systems Programming models for converged HPC/Big Data/Machine Learning systems System software supporting the convergence of HPC, Big Data, and Machine Learning processing Cloud-enabling cluster technologies and virtualization Energy-efficient middleware Cluster system-level protocols and APIs Cluster security Management of local, center-wide and disaggregate resources and job Programming and software development environments on clusters Fault tolerance and high-availability Administration, monitoring and maintenance tools Area 4: Data, Storage, and Visualization Cluster architectures for Big Data storage and processing Middleware for Big Data management Cluster-based cloud architectures for Big Data Storage systems supporting the convergence of HPC and Big Data processing File systems and I/O libraries Support and integration of non-volatile memory Visualization clusters and tiled displays Big Data/Large scale visualization tools Big Data application studies on cluster architectures
최종 수정: Dou Sun ()

게재율

평균 게재율: 34% 13년간 (2000–2012).

연도투고 수게재 수게재율(%)
20122015828.9%
20111403927.9%
20101073330.8%
20091004848%
2008922830.4%
20071064239.6%
20061274233.1%
20051384532.6%
20041504832%
20031644829.3%
20021164538.8%
2001743547.3%
20001443423.6%

관련 학회

CCFICORECP-I약칭정식 명칭투고 마감개최일
48.7HPCCTHigh Performance Computing and Cluster Technologies Conference2026-05-252026-07-03
CB90.1CCGRIDInternational Symposium on Cluster, Cloud and Grid Computing2026-12-082027-05-17
BA*89.7ICRAInternational Conference on Robotics and Automation2026-09-152027-05-24
BA*94.1IJCAIInternational Joint Conference on Artificial Intelligence2026-01-312026-08-15
B91.2ICASSPInternational Conference on Acoustics, Speech and Signal Processing2026-09-162027-05-16
BA*79.5PODSACM SIGMOD Conference on Principles of DB Systems2026-12-032027-06-13
BA76.5ICMEInternational Conference on Multimedia and Expo2025-12-312026-07-05
B84.4BIBMInternational Conference on Bioinformatics & Biomedicine2026-07-052026-12-01
BA*94.1ICDMInternational Conference on Data Mining2026-06-062026-11-12
BA*89.0ECCVEuropean Conference on Computer Vision2026-03-062026-09-08

관련 저널

CCF정식 명칭영향력 지수출판사ISSN
Cluster Computing4.1Springer1386-7857
BSoftware & Systems Modeling3.2Springer1619-1366
BPattern Recognition7.6Elsevier0031-3203
BIEEE Transactions on Neural Networks and Learning Systems8.9IEEE1045-9227
BInformation Sciences6.0Elsevier0020-0255
BComputer Networks4.7Elsevier1389-1286
BComputers & Security5.4Elsevier0167-4048
BIEEE Transactions on Intelligent Transportation Systems8.4IEEE1524-9050
BJournal of Systems and Software3.8Elsevier0164-1212
BInformation Processing & Management6.9Elsevier0306-4573

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