1 citations · 1 across the 6 of their papers we have counts for
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CarbonEdge: Carbon-Aware Deep Learning Inference Framework for Sustainable Edge Computing
Guilin Zhang, Wulan Guo, Ziqi Tan +2
Deep learning applications at the network edge lead to a significant growth in AI-related carbon emissions, presenting a critical sustainability challenge. The existing edge comput…
Serverless GPU Architecture for Enterprise HR Analytics: A Production-Scale BDaaS Implementation
Guilin Zhang, Wulan Guo, Ziqi Tan +8
Industrial and government organizations increasingly depend on data-driven analytics for workforce, finance, and regulated decision processes, where timeliness, cost efficiency, an…
AAPA: An Archetype-Aware Predictive Autoscaler with Uncertainty Quantification for Serverless Workloads on Kubernetes
Guilin Zhang, Srinivas Vippagunta, Raghavendra Nandagopal +7
Serverless platforms such as Kubernetes are increasingly adopted in high-performance computing, yet autoscaling remains challenging under highly dynamic and heterogeneous workloads…
KIS-S: A GPU-Aware Kubernetes Inference Simulator with RL-Based Auto-Scaling
Guilin Zhang, Wulan Guo, Ziqi Tan +2
Autoscaling GPU inference workloads in Kubernetes remains challenging due to the reactive and threshold-based nature of default mechanisms such as the Horizontal Pod Autoscaler (HP…
AMP4EC: Adaptive Model Partitioning Framework for Efficient Deep Learning Inference in Edge Computing Environments
Guilin Zhang, Wulan Guo, Ziqi Tan +1
Edge computing facilitates deep learning in resource-constrained environments, but challenges such as resource heterogeneity and dynamic constraints persist. This paper introduces…