Guardado en:
| Autores principales: | Pathak, Nilavra, Biswas, Samadrita, Roy, Nirmalya |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2604.15594 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Transforming Future Data Center Operations and Management via Physical AI
por: Cao, Zhiwei, et al.
Publicado: (2025)
por: Cao, Zhiwei, et al.
Publicado: (2025)
Electricity Cost Minimization for Multi-Workflow Allocation in Geo-Distributed Data Centers
por: Wang, Shuang, et al.
Publicado: (2025)
por: Wang, Shuang, et al.
Publicado: (2025)
Reducing Fragmentation and Starvation in GPU Clusters through Dynamic Multi-Objective Scheduling
por: Mamirov, Akhmadillo
Publicado: (2025)
por: Mamirov, Akhmadillo
Publicado: (2025)
DCSim: Computing and Networking Integration based Container Scheduling Simulator for Data Centers
por: Hu, Jinlong, et al.
Publicado: (2024)
por: Hu, Jinlong, et al.
Publicado: (2024)
Eventually-Consistent Federated Scheduling for Data Center Workloads
por: Thiyyakat, Meghana, et al.
Publicado: (2023)
por: Thiyyakat, Meghana, et al.
Publicado: (2023)
Full Scaling Automation for Sustainable Development of Green Data Centers
por: Wang, Shiyu, et al.
Publicado: (2023)
por: Wang, Shiyu, et al.
Publicado: (2023)
Reinforcement Learning-driven Data-intensive Workflow Scheduling for Volunteer Edge-Cloud
por: Mounesan, Motahare, et al.
Publicado: (2024)
por: Mounesan, Motahare, et al.
Publicado: (2024)
From Barrier to Bridge: The Case for AI Data Center/Power Grid Co-Design
por: Bashir, Noman, et al.
Publicado: (2026)
por: Bashir, Noman, et al.
Publicado: (2026)
Choosing the Right Battery Model for Data Center Simulations
por: Kilian, Paul, et al.
Publicado: (2025)
por: Kilian, Paul, et al.
Publicado: (2025)
A Multi-Objective Framework for Optimizing GPU-Enabled VM Placement in Cloud Data Centers with Multi-Instance GPU Technology
por: Siavashi, Ahmad, et al.
Publicado: (2025)
por: Siavashi, Ahmad, et al.
Publicado: (2025)
Towards Multi-Model LLM Schedulers: Empirical Insights into Offloading and Preemption
por: Yildiz, Mert, et al.
Publicado: (2026)
por: Yildiz, Mert, et al.
Publicado: (2026)
CoRaiS: Lightweight Real-Time Scheduler for Multi-Edge Cooperative Computing
por: Hu, Yujiao, et al.
Publicado: (2024)
por: Hu, Yujiao, et al.
Publicado: (2024)
AI Greenferencing: Routing AI Inferencing to Green Modular Data Centers with Heron
por: Reddy, Tella Rajashekhar, et al.
Publicado: (2025)
por: Reddy, Tella Rajashekhar, et al.
Publicado: (2025)
Mixture-of-Schedulers: An Adaptive Scheduling Agent as a Learned Router for Expert Policies
por: Wang, Xinbo, et al.
Publicado: (2025)
por: Wang, Xinbo, et al.
Publicado: (2025)
Duration-Informed Workload Scheduler
por: Loreti, Daniela, et al.
Publicado: (2026)
por: Loreti, Daniela, et al.
Publicado: (2026)
Workload Schedulers -- Genesis, Algorithms and Differences
por: Sliwko, Leszek, et al.
Publicado: (2025)
por: Sliwko, Leszek, et al.
Publicado: (2025)
Decentralized Distributed Proximal Policy Optimization (DD-PPO) for High Performance Computing Scheduling on Multi-User Systems
por: Sgambati, Matthew, et al.
Publicado: (2025)
por: Sgambati, Matthew, et al.
Publicado: (2025)
Compass: A Decentralized Scheduler for Latency-Sensitive ML Workflows
por: Yang, Yuting, et al.
Publicado: (2024)
por: Yang, Yuting, et al.
Publicado: (2024)
Federated Multi-Objective Learning
por: Yang, Haibo, et al.
Publicado: (2023)
por: Yang, Haibo, et al.
Publicado: (2023)
Power-Aware Scheduling for Multi-Center HPC Electricity Cost Optimization
por: Hossain, Abrar, et al.
Publicado: (2025)
por: Hossain, Abrar, et al.
Publicado: (2025)
Game-Theoretic Deep Reinforcement Learning to Minimize Carbon Emissions and Energy Costs for AI Inference Workloads in Geo-Distributed Data Centers
por: Hogade, Ninad, et al.
Publicado: (2024)
por: Hogade, Ninad, et al.
Publicado: (2024)
Power- and Fragmentation-aware Online Scheduling for GPU Datacenters
por: Lettich, Francesco, et al.
Publicado: (2024)
por: Lettich, Francesco, et al.
Publicado: (2024)
Dynamic Scheduling Strategies for Resource Optimization in Computing Environments
por: Wang, Xiaoye
Publicado: (2024)
por: Wang, Xiaoye
Publicado: (2024)
WORKSWORLD: A Domain for Integrated Numeric Planning and Scheduling of Distributed Pipelined Workflows
por: Paul, Taylor, et al.
Publicado: (2026)
por: Paul, Taylor, et al.
Publicado: (2026)
Data-Juicer 2.0: Cloud-Scale Adaptive Data Processing for and with Foundation Models
por: Chen, Daoyuan, et al.
Publicado: (2024)
por: Chen, Daoyuan, et al.
Publicado: (2024)
A Scheduling Framework for Efficient MoE Inference on Edge GPU-NDP Systems
por: Wu, Qi, et al.
Publicado: (2026)
por: Wu, Qi, et al.
Publicado: (2026)
Resource Allocation and Workload Scheduling for Large-Scale Distributed Deep Learning: A Survey
por: Liang, Feng, et al.
Publicado: (2024)
por: Liang, Feng, et al.
Publicado: (2024)
Topology-aware Preemptive Scheduling for Co-located LLM Workloads
por: Zhang, Ping, et al.
Publicado: (2024)
por: Zhang, Ping, et al.
Publicado: (2024)
Equinox: Holistic Fair Scheduling in Serving Large Language Models
por: Wei, Zhixiang, et al.
Publicado: (2025)
por: Wei, Zhixiang, et al.
Publicado: (2025)
Capacity Planning and Scheduling for Jobs with Uncertainty in Resource Usage and Duration
por: Patra, Sunandita, et al.
Publicado: (2025)
por: Patra, Sunandita, et al.
Publicado: (2025)
Turning AI Data Centers into Grid-Interactive Assets: Results from a Field Demonstration in Phoenix, Arizona
por: Colangelo, Philip, et al.
Publicado: (2025)
por: Colangelo, Philip, et al.
Publicado: (2025)
HiveMind: OS-Inspired Scheduling for Concurrent LLM Agent Workloads
por: Agyemang, Justice Owusu, et al.
Publicado: (2026)
por: Agyemang, Justice Owusu, et al.
Publicado: (2026)
Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling
por: Da, Wei, et al.
Publicado: (2025)
por: Da, Wei, et al.
Publicado: (2025)
TAPAS: Thermal- and Power-Aware Scheduling for LLM Inference in Cloud Platforms
por: Stojkovic, Jovan, et al.
Publicado: (2025)
por: Stojkovic, Jovan, et al.
Publicado: (2025)
Evaluating the Efficacy of LLM-Based Reasoning for Multiobjective HPC Job Scheduling
por: Jadhav, Prachi, et al.
Publicado: (2025)
por: Jadhav, Prachi, et al.
Publicado: (2025)
AgileLog: A Forkable Shared Log for Agents on Data Streams
por: Bhat, Shreesha G., et al.
Publicado: (2026)
por: Bhat, Shreesha G., et al.
Publicado: (2026)
Semantic Parallelism: Redefining Efficient MoE Inference via Model-Data Co-Scheduling
por: Li, Yan, et al.
Publicado: (2025)
por: Li, Yan, et al.
Publicado: (2025)
TCM-Serve: Modality-aware Scheduling for Multimodal Large Language Model Inference
por: Papaioannou, Konstantinos, et al.
Publicado: (2026)
por: Papaioannou, Konstantinos, et al.
Publicado: (2026)
Automated Planning for Optimal Data Pipeline Instantiation
por: Amado, Leonardo Rosa, et al.
Publicado: (2025)
por: Amado, Leonardo Rosa, et al.
Publicado: (2025)
Reconstruction-Based Adaptive Scheduling Using AI Inferences in Safety-Critical Systems
por: Alshaer, Samer, et al.
Publicado: (2025)
por: Alshaer, Samer, et al.
Publicado: (2025)
Ejemplares similares
-
Transforming Future Data Center Operations and Management via Physical AI
por: Cao, Zhiwei, et al.
Publicado: (2025) -
Electricity Cost Minimization for Multi-Workflow Allocation in Geo-Distributed Data Centers
por: Wang, Shuang, et al.
Publicado: (2025) -
Reducing Fragmentation and Starvation in GPU Clusters through Dynamic Multi-Objective Scheduling
por: Mamirov, Akhmadillo
Publicado: (2025) -
DCSim: Computing and Networking Integration based Container Scheduling Simulator for Data Centers
por: Hu, Jinlong, et al.
Publicado: (2024) -
Eventually-Consistent Federated Scheduling for Data Center Workloads
por: Thiyyakat, Meghana, et al.
Publicado: (2023)