Accelerating Multi-Model Inference by Merging DNNs of Different Weights

Joo Seong Jeong
Joo Seong Jeong
Gyeong-In Yu
Gyeong-In Yu
Cited by: 0|Views9

Abstract:

Standardized DNN models that have been proved to perform well on machine learning tasks are widely used and often adopted as-is to solve downstream tasks, forming the transfer learning paradigm. However, when serving multiple instances of such DNN models from a cluster of GPU servers, existing techniques to improve GPU utilization such ...More

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