SpotVista recommends multi-node spot instance configurations achieving 81.28% higher availability than SpotVerse and 21.6% higher stability than AWS SpotFleet while also delivering cost savings, based on collected availability data and real-world experiments.
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KubePACS formulates spot instance selection as a multi-objective ILP problem solved with GSS, integrated with Karpenter, and reports 55% average higher performance per dollar than prior tools.
COMPASS formalizes HPC configuration questions as ML tasks on traces, quantifies recommendation trustworthiness, and delivers 65.93% lower average job turnaround time plus 80.93% lower node usage versus prior methods in simulator tests.
citing papers explorer
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SpotVista: Availability-Aware Recommendation System for Reliable and Cost-Efficient Multi-Node Spot Instances
SpotVista recommends multi-node spot instance configurations achieving 81.28% higher availability than SpotVerse and 21.6% higher stability than AWS SpotFleet while also delivering cost savings, based on collected availability data and real-world experiments.
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KubePACS: Kubernetes Cluster Using Performant, Highly Available, and Cost Efficient Spot Instances
KubePACS formulates spot instance selection as a multi-objective ILP problem solved with GSS, integrated with Karpenter, and reports 55% average higher performance per dollar than prior tools.
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COMPASS: A Unified Decision-Intelligence System for Navigating Performance Trade-off in HPC
COMPASS formalizes HPC configuration questions as ML tasks on traces, quantifies recommendation trustworthiness, and delivers 65.93% lower average job turnaround time plus 80.93% lower node usage versus prior methods in simulator tests.