Mystic: Predictive Scheduling for GPU Based Cloud Servers Using Machine Learning

@article{Ukidave2016MysticPS,
  title={Mystic: Predictive Scheduling for GPU Based Cloud Servers Using Machine Learning},
  author={Yash Ukidave and Xiangyu Li and David R. Kaeli},
  journal={2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS)},
  year={2016},
  pages={353-362}
}
GPUs have become the primary choice of accelerators for high-end data centers and cloud servers, which can host thousands of disparate applications. With the growing demands for GPUs on clusters, there arises a need for efficient co-execution of applications on the same accelerator device. However, the resource contention among co-executing applications causes interference which leads to degradation in execution performance, impacts QoS requirements of applications and lowers overall system… CONTINUE READING
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