Abstract
In this chapter, we plan to provide an overview of cloud accelerators available on different cloud providers. We plan to introduce, show how to program, instantiate and discuss a deployment workflow. The goal is to provide an overview, but each step’s details shall be discussed in the following sections.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aljamal, R., El-Mousa, A., Jubair, F.: A comparative review of high-performance computing major cloud service providers. In: 2018 9th International Conference on Information and Communication Systems (ICICS). pp. 181–186. IEEE (2018)
Dutta, P., Dutta, P.: Comparative study of cloud services offered by amazon, microsoft & google. International Journal of Trend in Scientific Research and Development 3(3), 981–985 (2019)
Gangwar, A.K., Ravi, V.: Diabetic retinopathy detection using transfer learning and deep learning. In: Evolution in Computational Intelligence, pp. 679–689. Springer (2021)
Google: Cloud tpu system architecture (2022), https://cloud.google.com/tpu/docs/system-architecture-tpu-vm
Kotas, C., Naughton, T., Imam, N.: A comparison of amazon web services and microsoft azure cloud platforms for high performance computing. In: 2018 IEEE International Conference on Consumer Electronics (ICCE). pp. 1–4. IEEE (2018)
Künas, C.A., Serpa, M.S., Bez, J.L., Padoin, E.L., Navaux, P.O.: Offloading the training of an i/o access pattern detector to the cloud. In: 2021 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW). pp. 15–19. IEEE (2021)
LeCun, Y.: The mnist database of handwritten digits. http://yann.lecun.com/exdb/mnist/ (1998)
Lin, L., Pan, L., Liu, S.: Methods for improving the availability of spot instances: A survey. Computers in Industry 141, 103718 (2022)
Maliszewski, A.M., Roloff, E., Carreño, E.D., Griebler, D., Gaspary, L.P., Navaux, P.O.: Performance and cost-aware hpc in clouds: A network interconnection assessment. In: 2020 IEEE Symposium on Computers and Communications (ISCC). pp. 1–6. IEEE (2020)
Roloff, E., Diener, M., Gaspary, L.P., Navaux, P.O.: Hpc application performance and cost efficiency in the cloud. In: 2017 25th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP). pp. 473–477. IEEE (2017)
Serpa, M.S., Cruz, E.H., Diener, M., Krause, A.M., Navaux, P.O., Panetta, J., Farrés, A., Rosas, C., Hanzich, M.: Optimization strategies for geophysics models on manycore systems. The International Journal of High Performance Computing Applications 33(3), 473–486 (2019)
Singh, H.: Aws pricing and cost management. In: Practical Machine Learning with AWS, pp. 29–44. Springer (2021)
Vogel, A., Griebler, D., Maron, C.A., Schepke, C., Fernandes, L.G.: Private iaas clouds: a comparative analysis of opennebula, cloudstack and openstack. In: 2016 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP). pp. 672–679. IEEE (2016)
Wang, D., Chen, D., Song, B., Guizani, N., Yu, X., Du, X.: From iot to 5g i-iot: The next generation iot-based intelligent algorithms and 5g technologies. IEEE Communications Magazine 56(10), 114–120 (2018)
Wang, Y.E., Wei, G.Y., Brooks, D.: Benchmarking tpu, gpu, and cpu platforms for deep learning. ar**v preprint ar**v:1907.10701 (2019)
Wiley, C.: Google cloud unveils vertex ai, one platform, every ml tool you need (2021), https://cloud.google.com/blog/products/ai-machine-learning/google-cloud-launches-vertex-ai-unified-platform-for-mlops
Ying, C., Kumar, S., Chen, D., Wang, T., Cheng, Y.: Image classification at supercomputer scale. ar**v preprint ar**v:1811.06992 (2018)
You, Y., Zhang, Z., Hsieh, C.J., Demmel, J., Keutzer, K.: Fast deep neural network training on distributed systems and cloud tpus. IEEE Transactions on Parallel and Distributed Systems 30(11), 2449–2462 (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Künas, C.A., Serpa, M.S., Navaux, P.O.A. (2023). Exploiting Hardware Accelerators in Clouds. In: Borin, E., Drummond, L.M.A., Gaudiot, JL., Melo, A., Melo Alves, M., Navaux, P.O.A. (eds) High Performance Computing in Clouds . Springer, Cham. https://doi.org/10.1007/978-3-031-29769-4_7
Download citation
DOI: https://doi.org/10.1007/978-3-031-29769-4_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-29768-7
Online ISBN: 978-3-031-29769-4
eBook Packages: Computer ScienceComputer Science (R0)