Leveraging Cloud Computing and High Performance Computing (HPC) Advances for Next Generation Projects and Technologies

Authors

  • Praveen Kumar Donepudi UST-Global, Inc.

DOI:

https://doi.org/10.18034/ajtp.v7i3.499

Keywords:

Leveraging Cloud Computing, HPC, Next-Generation Technology, Cloud Computing Technology

Abstract

The scene of cloud computing has essentially changed throughout the most recent decade. Not just have more providers and administration contributions have barged in the space, yet additionally, cloud foundation that was generally restricted to single providers data centers is currently advancing. In this paper, we initially talk about the changing cloud foundation and consider the utilization of framework from numerous providers and the advantage of decentralizing computing ceaselessly from data centers. These patterns have brought about the requirement for a variety of new computing architectures that will be offered by future cloud framework. These models are predicted to affect certain areas, for example, connecting individuals and devices, data-intensive computing, the service space, and self-learning frameworks. At long last, we spread out a guide of difficulties that should be tended to for understanding the capability of cutting edge cloud frameworks. Architectural and metropolitan design ventures are continually breaking barriers of scale and unpredictability and consistently look for improved proficiency, maintainability, building energy performance, and cost-efficiency. Simulation and largescale information processing are presently the basic components of this cycle. Ongoing advances in calculations and computational force offer a way to address the complicated elements of a coordinated entire structure framework. Nonetheless, adaptability is a critical boundary to the acknowledgment of entire structure frameworks devices for configuration, control, and improvement. This position paper presents a bunch of strategies, for example, quick plan boundary space exploration, large-scope high accuracy simulation, and integrated multi-disciplinary improvement for semi-or completely automated projects. These procedures are very computing escalated, and have customarily just been accessible to the examination network. Be that as it may, once empowered by advances in cloud computing and high-performance computing, these procedures can encourage the intelligent plan measure bringing about improved results and decreased advancement process durations.

 

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Author Biography

Praveen Kumar Donepudi, UST-Global, Inc.

Enterprise Architect, Information Technology, UST-Global, Inc., Ohio, USA

References

Ahmed, A. A. A. (2020). Corporate Attributes and Disclosure of Accounting Information: Evidence from the Big Five Banks of China. Journal of Public Affairs. e2244. https://doi.org/10.1002/pa.2244 DOI: https://doi.org/10.1002/pa.2244

Ahmed, A. A. A., Asadullah, A. B. M., & Rahman, M. M. (2016). NGO’s Financial Reporting and Human Capital Development. American Journal of Trade and Policy, 3(2), 53-60. https://doi.org/10.18034/ajtp.v3i2.401 DOI: https://doi.org/10.18034/ajtp.v3i2.401

Donepudi , P. K. (2019). Automation and Machine Learning in Transforming the Financial Industry. Asian Business Review, 9(3), 129-138. https://doi.org/10.18034/abr.v9i3.494 DOI: https://doi.org/10.18034/abr.v9i3.494

Donepudi, P. K. (2015). Crossing Point of Artificial Intelligence in Cybersecurity. American Journal of Trade and Policy, 2(3), 121-128. https://doi.org/10.18034/ajtp.v2i3.493 DOI: https://doi.org/10.18034/ajtp.v2i3.493

Donepudi, P. K. (2020). Crowdsourced Software Testing: A Timely Opportunity. Engineering International, 8(1), 25-30. https://doi.org/10.18034/ei.v8i1.491 DOI: https://doi.org/10.18034/ei.v8i1.491

Gai, K., Qiu, M., Zhao, H., Tao, L., Zong, Z. (2016). Dynamic energy-aware cloudlet-based mobile cloud computing model for green computing. Journal of Network and Computer Applications, 59, 46-54, https://doi.org/10.1016/j.jnca.2015.05.016 DOI: https://doi.org/10.1016/j.jnca.2015.05.016

Grozev, N., & Buyya, R. (2014). Inter-Cloud Architectures, and Application Brokering: Taxonomy and Survey. Software: Practice and Experience, 44(3), 369–390. https://doi.org/10.1002/spe.2168 DOI: https://doi.org/10.1002/spe.2168

Petcu, D., Macariu, G., Panica, S., Crăciun, C. (2013) Portable Cloud applications-From theory to practice. Future Generation Computer Systems, 29(6), 1417-1430. https://doi.org/10.1016/j.future.2012.01.009. DOI: https://doi.org/10.1016/j.future.2012.01.009

Rahman, M. M., Chowdhury, M. R. H. K., Islam, M. A., Tohfa, M. U., Kader, M. A. L., Ahmed, A. A. A., & Donepudi, P. K. (2020). Relationship between Socio-Demographic Characteristics and Job Satisfaction: Evidence from Private Bank Employees. American Journal of Trade and Policy, 7(2), 65-72. https://doi.org/10.18034/ajtp.v7i2.492 DOI: https://doi.org/10.18034/ajtp.v7i2.492

Varghese, B., Wang, N., Barbhuiya, S., Kilpatrick, P., Nikolopoulos, D. S. (2016). Challenges and Opportunities in Edge Computing, in: IEEE International Conference on Smart Cloud, 20–26. https://doi.org/10.1109/SmartCloud.2016.18 DOI: https://doi.org/10.1109/SmartCloud.2016.18

Villari, M., Fazio, M., Dustdar, S., Rana, O., Ranjan, R. (2016). Osmotic Computing: A New Paradigm for Edge/Cloud Integration, IEEE Cloud Computing, 3 (6), 76–83. https://doi.org/10.1109/MCC.2016.124 DOI: https://doi.org/10.1109/MCC.2016.124

Wu, Z., & Madhyastha, H. V. (2013). Understanding the Latency Benefits of Multi-cloud Webservice Deployments, SIGCOMM Computer Communications Review, 43 (2), 13–20. https://doi.org/10.1145/2479957.2479960 DOI: https://doi.org/10.1145/2479957.2479960

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Published

2020-12-01

How to Cite

Donepudi, P. K. . (2020). Leveraging Cloud Computing and High Performance Computing (HPC) Advances for Next Generation Projects and Technologies. American Journal of Trade and Policy, 7(3), 73–78. https://doi.org/10.18034/ajtp.v7i3.499