DProbe: Profiling and Predicting Multi-tenant Deep Learning Workloads for GPU Resource Scaling

Author:

Zhou ZechunORCID,Sun JingweiORCID,Mei Hengquan,Sun Peng,Sun GuangzhongORCID

Publisher

Springer Nature Switzerland

Reference32 articles.

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2. Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. In: International Conference on Learning Representations (ICLR) (2015)

3. Cho, K., van Merrienboer, B., Gulcehre, C., Bougares, F., Schwenk, H., Bengio, Y.: Learning phrase representations using RNN encoder-decoder for statistical machine translation. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP) (2014)

4. Dosovitskiy, A., et al.: An image is worth 16x16 words: transformers for image recognition at scale. In: International Conference on Learning Representations (ICLR) (2021)

5. Fujimoto, S., Hoof, H., Meger, D.: Addressing function approximation error in actor-critic methods. In: International Conference on Machine Learning (ICML), pp. 1587–1596 (2018)

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