Vincent Lannurien
d822cdaa6a
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58 lines
3.7 KiB
YAML
58 lines
3.7 KiB
YAML
venue: SEC
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year: 2025
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papers:
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- title: 'lm-Meter: Unveiling Runtime Inference Latency for On-Device Language Models'
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authors:
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- Haoxin Wang 0003
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reason: "Provides the first detailed runtime profiling framework for on-device LLM inference, revealing key latency bottlenecks across diverse edge hardware configurations."
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- title: 'SLED: A Speculative LLM Decoding Framework for Efficient Edge Serving'
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authors:
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- Xiangchen Li
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reason: "Adapts speculative decoding to edge serving constraints, reducing LLM token generation latency while respecting the tight memory and compute budgets of edge nodes."
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- title: 'SledgeScale: Load-Aware Dispatch and Deadline-Driven Scheduling for Scalable,
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Dense Serverless Computing in Edge Data Centers'
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authors:
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- Xiaosu Lyu
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reason: "Introduces a load-aware dispatch and deadline-driven scheduler for dense serverless edge data centers, demonstrating substantial SLA compliance improvements over baseline policies."
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- title: 'Warping the Edge: Enabling Instant Mobility for Stateful Applications over
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5G and Beyond'
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authors:
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- Mukhtiar Ahmad
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reason: "Achieves near-instantaneous stateful application migration across 5G edge nodes by combining memory snapshotting with network-layer forwarding continuity."
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- title: Uncertainty-Aware RL-Based Scheduling of Multi-DNN Workloads on Edge MPSoCs
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authors:
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- Soroush Heidari
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reason: "Uses uncertainty-aware reinforcement learning to schedule concurrent DNN workloads on heterogeneous edge MPSoCs, reducing deadline misses under dynamic arrival patterns."
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- title: 'SEEB-GPU: Early-Exit Aware Scheduling and Batching for Edge GPU Inference'
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authors:
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- Srinivasan Subramaniyan
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reason: "Exploits early-exit branching in DNN inference to build an adaptive batching and scheduling policy for edge GPUs that cuts average latency without sacrificing throughput."
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- title: 'Elastoformer: Enabling Dynamic Adaptivity via Elastic Model Transformation'
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authors:
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- Sudaksh Kalra
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reason: "Proposes elastic transformer transformations that resize model capacity at runtime to match available edge resources, enabling continuous inference under fluctuating conditions."
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- title: 'PlatformX: An End-to-End Transferable Platform for Energy-Efficient Neural
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Architecture Search'
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authors:
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- Xiaolong Tu
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reason: "Presents a transferable NAS platform that searches for energy-efficient DNN architectures deployable across heterogeneous edge targets with minimal re-search overhead."
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- title: 'Bayes-Split-Edge: Bayesian Optimization for Constrained Collaborative Inference
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in Wireless Edge Systems'
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authors:
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- Fatemeh Zahra Safaeipour
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reason: "Applies Bayesian optimization to find optimal split points for collaborative inference in wireless edge systems, accounting for dynamic channel and computation constraints."
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- title: Energy-efficient DNN Dividing Technique for Latency Optimization in Dynamic
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Mobile Edge Networks
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authors:
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- Eldiyar Zhantileuov
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reason: "Develops a DNN partitioning strategy for mobile edge networks that minimizes end-to-end latency while satisfying energy budgets under time-varying link conditions."
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- title: LLM-Driven Auto Configuration for Transient IoT Device Collaboration
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authors:
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- Hetvi Shastri
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reason: "Leverages LLMs to automate the configuration of transient IoT device coalitions, reducing manual setup overhead and adapting collaboration policies to changing device membership."
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- title: 'fReeLoaders: An IoT Ecosystem for Real-Time Deadline-Driven Task Scheduling
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using Reinforcement Learning'
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authors:
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- Marshall Clyburn
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reason: "Builds a reinforcement-learning scheduler for IoT ecosystems that meets real-time task deadlines by exploiting opportunistic idle capacity across heterogeneous edge devices."
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