4 papers
MDInference: Balancing Inference Accuracy and Latency for Mobile Applications
Samuel S. Ogden, Tian Guo
Deep Neural Networks are allowing mobile devices to incorporate a wide range of features into user applications. However, the computational complexity of these models makes it diff…
Characterizing the Deep Neural Networks Inference Performance of Mobile Applications
Samuel S. Ogden, Tian Guo
Today's mobile applications are increasingly leveraging deep neural networks to provide novel features, such as image and speech recognitions. To use a pre-trained deep neural netw…
ModiPick: SLA-aware Accuracy Optimization For Mobile Deep Inference
Samuel S. Ogden, Tian Guo
Mobile applications are increasingly leveraging complex deep learning models to deliver features, e.g., image recognition, that require high prediction accuracy. Such models can be…
CloudCoaster: Transient-aware Bursty Datacenter Workload Scheduling
Samuel S. Ogden, Tian Guo
Today's clusters often have to divide resources among a diverse set of jobs. These jobs are heterogeneous both in execution time and in their rate of arrival. Execution time hetero…