Comparing SARS-CoV-2 Sequences using a Commercial Cloud with a Spot Instance Based Dynamic Scheduler
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Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9499314/9499345/09499452.pdf?arnumber=9499452
Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Monte Carlo Simulation-Based Robust Workflow Scheduling for Spot Instances in Cloud Environments;Tsinghua Science and Technology;2024-02
2. A Framework for Automated Parallel Execution of Scientific Multi-workflow Applications in the Cloud with Work Stealing;Lecture Notes in Computer Science;2024
3. MScheduler: Leveraging Spot Instances for High-Performance Reservoir Simulation in the Cloud;2023 IEEE International Conference on Cloud Computing Technology and Science (CloudCom);2023-12-04
4. A Preliminary Review of Function as a Service Platform Running with AWS Spot Instances;2023 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW);2023-10-17
5. Towards Optimizing Computational Costs of Federated Learning in Clouds;2021 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW);2021-10
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