Paper-Conference

Interference-aware Multiplexing for Deep Learning in GPU Clusters A Middleware Approach
A common strategy for improving efficiency in training deep learning entails multiplexing tasks on a single GPU. To mitigate the …
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PERT-GNN: Latency Prediction for Microservice-based Cloud-Native Applications via Graph Neural Networks
Cloud-native applications using microservice architectures are rapidly replacing traditional monolithic applications. To meet …
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Understanding and Optimizing Workloads for Unified Resource Management in Large Cloud Platforms
To fully utilize computing resources, cloud providers such as Google and Alibaba choose to co-locate online services with batch …
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Erms: Efficient Resource Management for Shared Microservices with SLA Guarantees
A common approach to improving resource utilization in data centers is to adaptively provision resources based on the actual workload. …
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The Power of Prediction Microservice Auto Scaling via Workload Learning
When deploying microservices in production clusters, it is critical to automatically scale containers to improve cluster utilization …
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Multi Resource Scheduling with Task Cloning in Heterogeneous Clusters
To mitigate the straggler effect, today’s systems and computing frameworks have adopted redundancy to launch extra copies for …
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Characterizing Microservice Dependency and Performance: Alibaba Trace Analysis
Best Paper Award
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