Built on

Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell, “Caffe: Convolutional architecture for fast feature embedding,” in Proceedings of the 22nd ACM international conference on Multimedia . ACM, 2014, pp. 675–678
2014
Earlier work this paper cites.
D. Crankshaw, P. Bailis, J. E. Gonzalez, H. Li, Z. Zhang, M. J. Franklin, A. Ghodsi, and M. I. Jordan, “The missing piece in complex analytics: Low latency, scalable model management and serving with velox,” arXiv preprint arXiv:1409.3809 , 2014
Original
2014
Earlier work this paper cites.
T. Chen, M. Li, Y. Li, M. Lin, N. Wang, M. Wang, T. Xiao, B. Xu, C. Zhang, and Z. Zhang, “Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems,” arXiv preprint arXiv:1512.01274 , 2015
Original
2015
Earlier work this paper cites.
Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature , vol. 521, no. 7553, pp. 436–444, 2015
2015
Earlier work this paper cites.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” CoRR , vol. abs/1512.03385, 2015. [Online]. Available: http://arxiv.org/abs/1512.03385
Original
2015
Earlier work this paper cites.
M. Yan, P. Castro, P. Cheng, and V. Ishakian, “Building a chatbot with serverless computing,” in Proceedings of the 1st International Workshop on Mashups of Things and APIs . ACM, 2016, p. 5
2016
Earlier work this paper cites.
I. Baldini, P. Castro, P. Cheng, S. Fink, V. Ishakian, N. Mitchell, V. Muthusamy, R. Rabbah, and P. Suter, “Cloud-native, event-based programming for mobile applications,” in Proceedings of the International Workshop on Mobile Software Engineering and Systems . ACM, 2016, pp. 287–288
2016
Earlier work this paper cites.
M. Abadi, A. Agarwal, P. Barham, E. Brevdo, Z. Chen, C. Citro, G. S. Corrado, A. Davis, J. Dean, M. Devin et al. , “Tensorflow: Large-scale machine learning on heterogeneous distributed systems,” arXiv preprint arXiv:1603.04467 , 2016
Original
2016
Earlier work this paper cites.
F. N. Iandola, S. Han, M. W. Moskewicz, K. Ashraf, W. J. Dally, and K. Keutzer, “Squeezenet: Alexnet-level accuracy with 50x fewer parameters and < < 0.5mb model size,” arXiv:1602.07360 , 2016
Original
2016
Earlier work this paper cites.

Similar

G. C. Fox, V. Ishakian, V. Muthusamy, and A. Slominski, “Status of serverless computing and function-as-a-service (faas) in industry and research,” arXiv preprint arXiv:1708.08028 , 2017
Original
2017
Cited alongside, same era.
I. Baldini, P. Castro, K. Chang, P. Cheng, S. Fink, V. Ishakian, N. Mitchell, V. Muthusamy, R. Rabbah, A. Slominski et al. , “Serverless computing: Current trends and open problems,” arXiv preprint arXiv:1706.03178 , 2017
Original
2017
Cited alongside, same era.
R. Chard, K. Chard, J. Alt, D. Y. Parkinson, S. Tuecke, and I. Foster, “Ripple: Home automation for research data management,” in 2017 IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW) , June 2017, pp. 389–394
2017
Cited alongside, same era.
N. Bila, P. Dettori, A. Kanso, Y. Watanabe, and A. Youssef, “Leveraging the serverless architecture for securing linux containers,” in Distributed Computing Systems Workshops (ICDCSW), 2017 IEEE 37th International Conference on . IEEE, 2017, pp. 401–404

Then

S. T. for Improving MXNet Performance, “https://mxnet.incubator.apache.org/how_to/perf.html,” 2017
2017
Closest in time.
Y. Al-Dhuraibi, F. Paraiso, N. Djarallah, and P. Merle, “Autonomic vertical elasticity of docker containers with elasticdocker,” in 10th IEEE International Conference on Cloud Computing, IEEE CLOUD , 2017
2017
Closest in time.
S. Mallya, “Seamlessly scale predictions with aws lambda and mxnet,” 2017, https://aws.amazon.com/blogs/compute/seamlessly-scale-predictions-with-aws-lambda-and-mxnet/
2017
Closest in time.
S. T. predictions with Python and A. Lambda, “https://medium.com/tooso/serving-tensorflow-predictions-with-python-and-aws-lambda-facb4ab87ddd,” 2017
2017
Closest in time.
D. Crankshaw, X. Wang, G. Zhou, M. J. Franklin, J. E. Gonzalez, and I. Stoica, “Clipper: A low-latency online prediction serving system.” in NSDI , 2017, pp. 613–627

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2017

Serving deep learning models in a serverless platform

Ishakian, Vatche, Muthusamy, Vinod, Slominski, Aleksander

Understand

Serverless computing has emerged as a compelling paradigm for the development and deployment of a wide range of event based cloud applications.

At the same time, cloud providers and enterprise companies are heavily adopting machine learning and Artificial Intelligence to either differentiate themselves, or provide their customers with value added services.
In this work we evaluate the suitability of a serverless computing environment for the inferencing of large neural network models.
Our experimental evaluations are executed on the AWS Lambda environment using the MxNet deep learning framework.

Built on

Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell, “Caffe: Convolutional architecture for fast feature embedding,” in Proceedings of the 22nd ACM international conference on Multimedia . ACM, 2014, pp. 675–678
2014
Earlier work this paper cites.
D. Crankshaw, P. Bailis, J. E. Gonzalez, H. Li, Z. Zhang, M. J. Franklin, A. Ghodsi, and M. I. Jordan, “The missing piece in complex analytics: Low latency, scalable model management and serving with velox,” arXiv preprint arXiv:1409.3809 , 2014
Original
2014
Earlier work this paper cites.
T. Chen, M. Li, Y. Li, M. Lin, N. Wang, M. Wang, T. Xiao, B. Xu, C. Zhang, and Z. Zhang, “Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems,” arXiv preprint arXiv:1512.01274 , 2015
Original
2015
Earlier work this paper cites.
Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature , vol. 521, no. 7553, pp. 436–444, 2015
2015
Earlier work this paper cites.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” CoRR , vol. abs/1512.03385, 2015. [Online]. Available: http://arxiv.org/abs/1512.03385
Original
2015
Earlier work this paper cites.
M. Yan, P. Castro, P. Cheng, and V. Ishakian, “Building a chatbot with serverless computing,” in Proceedings of the 1st International Workshop on Mashups of Things and APIs . ACM, 2016, p. 5
2016
Earlier work this paper cites.
I. Baldini, P. Castro, P. Cheng, S. Fink, V. Ishakian, N. Mitchell, V. Muthusamy, R. Rabbah, and P. Suter, “Cloud-native, event-based programming for mobile applications,” in Proceedings of the International Workshop on Mobile Software Engineering and Systems . ACM, 2016, pp. 287–288
2016
Earlier work this paper cites.
M. Abadi, A. Agarwal, P. Barham, E. Brevdo, Z. Chen, C. Citro, G. S. Corrado, A. Davis, J. Dean, M. Devin et al. , “Tensorflow: Large-scale machine learning on heterogeneous distributed systems,” arXiv preprint arXiv:1603.04467 , 2016
Original
2016
Earlier work this paper cites.
F. N. Iandola, S. Han, M. W. Moskewicz, K. Ashraf, W. J. Dally, and K. Keutzer, “Squeezenet: Alexnet-level accuracy with 50x fewer parameters and < < 0.5mb model size,” arXiv:1602.07360 , 2016
Original
2016
Earlier work this paper cites.

Similar

G. C. Fox, V. Ishakian, V. Muthusamy, and A. Slominski, “Status of serverless computing and function-as-a-service (faas) in industry and research,” arXiv preprint arXiv:1708.08028 , 2017
Original
2017
Cited alongside, same era.
I. Baldini, P. Castro, K. Chang, P. Cheng, S. Fink, V. Ishakian, N. Mitchell, V. Muthusamy, R. Rabbah, A. Slominski et al. , “Serverless computing: Current trends and open problems,” arXiv preprint arXiv:1706.03178 , 2017
Original
2017
Cited alongside, same era.
R. Chard, K. Chard, J. Alt, D. Y. Parkinson, S. Tuecke, and I. Foster, “Ripple: Home automation for research data management,” in 2017 IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW) , June 2017, pp. 389–394
2017
Cited alongside, same era.
N. Bila, P. Dettori, A. Kanso, Y. Watanabe, and A. Youssef, “Leveraging the serverless architecture for securing linux containers,” in Distributed Computing Systems Workshops (ICDCSW), 2017 IEEE 37th International Conference on . IEEE, 2017, pp. 401–404

Then

S. T. for Improving MXNet Performance, “https://mxnet.incubator.apache.org/how_to/perf.html,” 2017
2017
Closest in time.
Y. Al-Dhuraibi, F. Paraiso, N. Djarallah, and P. Merle, “Autonomic vertical elasticity of docker containers with elasticdocker,” in 10th IEEE International Conference on Cloud Computing, IEEE CLOUD , 2017
2017
Closest in time.
S. Mallya, “Seamlessly scale predictions with aws lambda and mxnet,” 2017, https://aws.amazon.com/blogs/compute/seamlessly-scale-predictions-with-aws-lambda-and-mxnet/
2017
Closest in time.
S. T. predictions with Python and A. Lambda, “https://medium.com/tooso/serving-tensorflow-predictions-with-python-and-aws-lambda-facb4ab87ddd,” 2017
2017
Closest in time.
D. Crankshaw, X. Wang, G. Zhou, M. J. Franklin, J. E. Gonzalez, and I. Stoica, “Clipper: A low-latency online prediction serving system.” in NSDI , 2017, pp. 613–627

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

alphaXiv is searching for related work…

2017

Cited alongside, same era.

A. OpenWhisk, “https://openwhisk.incubator.apache.org/,” 2017

2017

Cited alongside, same era.

A. L. H. I. Works, “http://docs.aws.amazon.com/lambda/latest/dg/lambda-introduction.html,” 2017

2017

Cited alongside, same era.

2017, https://aws.amazon.com/api-gateway/

2017

Cited alongside, same era.

2017, https://aws.amazon.com/lambda/faqs/

2017

Cited alongside, same era.

2017, http://jmeter.apache.org/

2017

Cited alongside, same era.

S. Xie, R. Girshick, P. Dollár, Z. Tu, and K. He, “Aggregated residual transformations for deep neural networks,” arXiv:1611.05431

Original

Cited in the paper.

S. Mallya, “Mxnet package for aws lambda,” https://github.com/awslabs/mxnet-lambda

Cited in the paper.

R. P. with Intel Movidius NCS, “https://developer.movidius.com/start.”

Original

Cited in the paper.

2017

Closest in time.

T. Serving, “https://tensorflow.github.io/serving,” 2017

2017

Closest in time.

G. McGrath and P. R. Brenner, “Serverless computing: Design, implementation, and performance,” in Distributed Computing Systems Workshops (ICDCSW), 2017 IEEE 37th International Conference on . IEEE, 2017, pp. 405–410

2017

Closest in time.

A. A. B. chip, “https://en.wikipedia.org/wiki/apple_a11,” 2017

2017

Closest in time.