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Oort: Informed Participant Selection for Scalable Federated Learning
Federated Learning (FL) is an emerging direction in distributed machine ...
10/12/2020 ∙ by Fan Lai, et al. ∙
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BoPF: Mitigating the Burstiness-Fairness Tradeoff in Multi-Resource Clusters
Simultaneously supporting latency- and throughout-sensitive workloads in...
12/07/2019 ∙ by Tan N. Le, et al. ∙
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Effectively Prefetching Remote Memory with Leap
Memory disaggregation over RDMA can improve the performance of memory-co...
11/22/2019 ∙ by Hasan Al Maruf, et al. ∙
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Mitigating the Performance-Efficiency Tradeoff in Resilient Memory Disaggregation
Memory disaggregation has received attention in recent years as a promis...
10/22/2019 ∙ by Youngmoon Lee, et al. ∙
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Near Optimal Coflow Scheduling in Networks
The coflow scheduling problem has emerged as a popular abstraction in th...
06/17/2019 ∙ by Mosharaf Chowdhury, et al. ∙
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RDMA Performance Isolation With Justitia
Despite its increasing popularity, most of RDMA's benefits such as ultra...
05/11/2019 ∙ by Yiwen Zhang, et al. ∙
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Terra: Scalable Cross-Layer GDA Optimizations
Geo-distributed analytics (GDA) frameworks transfer large datasets over ...
04/17/2019 ∙ by Jie You, et al. ∙
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Salus: Fine-Grained GPU Sharing Primitives for Deep Learning Applications
GPU computing is becoming increasingly more popular with the proliferati...
02/12/2019 ∙ by Peifeng Yu, et al. ∙
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