Información de la conferencia

CCGRID 2027: International Symposium on Cluster, Cloud and Grid Computing

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Día de Entrega:
2026-11-24 Faltan 19 días
Fecha de Notificación:
2027-02-01
Fecha de conferencia:
2027-05-24
Ubicación:
Dallas-Fort Worth, Texas, USA
Ediciones:
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CCF: C   ICORE: B   QUALIS: A1   Vistas: 343765   Seguidores: 160   Asistentes: 43
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Índice Conference Partner (CP-I)

90,5 / 100
Puesto n.º 69 de 5.769 congresos · 2% superior

N.º 19 de 342 en Sistemas y arquitectura

Reconocimiento académico (35%)
100
Selectividad en la revisión (20%)
85
Ediciones celebradas (20%)
90
Atención de la comunidad (10%)
77
Integridad del registro público (15%)
85

Datos utilizados: Categorías: CCF C, ICORE B, QUALIS A1 · Tasa de aceptación: 24.1% (media de 5 ediciones registradas) · Ediciones documentadas: 27 · Investigadores que lo siguen aquí: 160 · Investigadores que abrieron esta página en los últimos 24 meses: 42

Falta en el registro público: Premios al mejor artículo (+2,3)
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Solicitud de Artículos

CCGRID 2027 (International Symposium on Cluster, Cloud and Grid Computing) is a CCF C / ICORE B / QUALIS A1 conference held in Dallas-Fort Worth, Texas, USA on 2027-05-24. The paper submission deadline is 2026-11-24. Acceptance notifications are sent on 2027-02-01.

We invite original, high-quality papers that address fundamental research and emerging challenges across a broad spectrum of distributed systems and applications. Submissions may focus on theoretical foundations, system design, implementation, or real-world deployments. We particularly encourage contributions stemming from industry efforts and academia-industry collaborations, including practical experiences, deployed systems, and applied research with tangible impact. Technical Tracks Track 1 – Hardware Systems, Architectures, and Quantum Future Compute Platforms: Innovations in computing and networking hardware, system architectures, and emerging compute paradigms. Topics include accelerators, heterogeneous systems, reconfigurable architectures, and quantum or neuromorphic computing platforms across cloud, edge, and HPC environments. This track also covers advanced networking technologies such as software-defined networking (SDN) and high-performance interconnects for distributed systems. Track 2 – Software Systems, Applications, and Programming Models: Advances in middleware, operating systems, programming frameworks, cloud-native systems, and distributed application development. Topics include serverless computing, microservices, container orchestration, and resource management and scheduling. This track also welcomes contributions on data-intensive systems, distributed storage architectures, and scalable data management frameworks. Track 3 – Sustainable Computing and Green Technologies: Energy-efficient computing, carbon-aware platforms, carbon-intelligent scheduling, and sustainable systems design across the cloud-to-edge continuum. Topics also include cost-aware computing, economic modeling, and optimization of resource usage to support sustainability goals. Track 4 – Performance Modeling, Analysis, and Optimization: Techniques for performance engineering, benchmarking, system tuning, and modeling of distributed, parallel, and cloud-based systems. Topics include optimization of scientific workflows, reproducibility-aware benchmarking methodologies, and pipeline performance engineering. Track 5 – Distributed Systems Security, Privacy, and Reliability: Innovative solutions for securing distributed infrastructures, enabling confidential computing, preserving data privacy, and enhancing cyber-resilience. Topics include trustworthy systems, intrusion detection, self-healing mechanisms, and approaches for building robust, fault-tolerant, and reliable computing platforms. Track 6 – Systems for AI/ML and Distributed Intelligence: Techniques and systems for scalable and efficient execution of AI/ML workloads across distributed platforms, addressing challenges in foundation models, Large Language Models (LLMs), model serving, and MLOps, including the compute continuum, osmotic computing, and liquid computing. Topics include edge intelligence, collaborative and federated learning, and system-level support for distributed AI.
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Tasa de aceptación

Tasa de aceptación media: 27.5% en 16 años (2001–2021).

AñoEnviadosAceptadosAceptados(%)
20212306026.1%
20152686925.7%
20142835419.1%
20132575722.2%
20123028327.5%
20111895529.1%
20102195123.3%
20092715721%
20082016532.3%
20072187233%
20062576123.7%
20052357632.3%
20041383827.5%
20031143934.2%
20021082725%
20011264838.1%

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