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Scheduling

Project or Job Scheduling

Papers

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Showing 1701–1725 of 3104 papers

TitleStatusHype
Study of BSM Inter-Packet Gap Tails in C-V2X Networks—0
Study on the Large Batch Size Training of Neural Networks Based on the Second Order Gradient—0
Subgraph Extraction-based Feedback-guided Iterative Scheduling for HLS—0
Submodular Function Maximization for Group Elevator Scheduling—0
Sum Throughput Maximization in Multi-BD Symbiotic Radio NOMA Network Assisted by Active-STAR-RIS—0
SuperNeurons: Dynamic GPU Memory Management for Training Deep Neural Networks—0
SuperScaler: Supporting Flexible DNN Parallelization via a Unified Abstraction—0
SuperServe: Fine-Grained Inference Serving for Unpredictable Workloads—0
Supervised-learning-based Optimal Thermal Management in an Electric Vehicle—0
Surgical Scheduling via Optimization and Machine Learning with Long-Tailed Data—0
SURREAL-System: Fully-Integrated Stack for Distributed Deep Reinforcement Learning—0
Survey of Distributed Algorithms for Resource Allocation over Multi-Agent Systems—0
Survey on Multi-Agent Q-Learning frameworks for resource management in wireless sensor network—0
Sustainable AIGC Workload Scheduling of Geo-Distributed Data Centers: A Multi-Agent Reinforcement Learning Approach—0
Sustainable Carbon-Aware and Water-Efficient LLM Scheduling in Geo-Distributed Cloud Datacenters—0
SwapNet: Efficient Swapping for DNN Inference on Edge AI Devices Beyond the Memory Budget—0
SWIPT in Mixed Near- and Far-Field Channels: Joint Beam Scheduling and Power Allocation—0
SWIS -- Shared Weight bIt Sparsity for Efficient Neural Network Acceleration—0
Switched Max-Plus Linear-Dual Inequalities: Application in Scheduling of Multi-Product Processing Networks—0
Symmetry-Preserving Architecture for Multi-NUMA Environments (SPANE): A Deep Reinforcement Learning Approach for Dynamic VM Scheduling—0
Symphony: Optimized DNN Model Serving using Deferred Batch Scheduling—0
Synergy: Resource Sensitive DNN Scheduling in Multi-Tenant Clusters—0
System-Agnostic Meta-Learning for MDP-based Dynamic Scheduling via Descriptive Policy—0
Tabular and Deep Reinforcement Learning for Gittins Index—0
Tackling the Dynamicity in a Production LLM Serving System with SOTA Optimizations via Hybrid Prefill/Decode/Verify Scheduling on Efficient Meta-kernels—0
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