Performance Analysis of High Performance Computing Applications on the Amazon Web Services Cloud
By K. Jackson, Lavanya Ramakrishnan, K. Muriki, Shane Canon, S. Cholia, John M. Shalf, H. Wasserman, Nicholas J. Wright. 2010 IEEE Second International Conference on Cloud Computing Technology and Science, 2010
643 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Information Systems
View Paper: https://www.semanticscholar.org/paper/0914d1fa86a1a5eeb16dcea904cc226fb010e508
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Nikolay Grozev
- Rajkumar Buyya
- Anton Beloglazov
- Blesson Varghese
- Rodrigo Neves Calheiros
- Jia Yu
- R. Ranjan
- David Abramson
In Information Systems
- Nikolay Grozev
- Rajkumar Buyya
- Anton Beloglazov
- Rodrigo Neves Calheiros
- Blesson Varghese
- R. Ranjan
- Yonggang Wen
- Miyuru Dayarathna
Citations in the corpus
- Edge Computing: Vision and Challenges (2016, neutral): “Latency: Latency is one of the most important metrics to evaluate the performance, especially in interaction applications/services [34], [35].”
- Inter‐Cloud architectures and application brokering: taxonomy and survey (2014, result): “Research community clouds like Australia’s NeCTAR [23] and Canada’s CESWP [24] have made the use of clouds for resource intensive jobs apparent, though there are still concerns about the worse performance of cloud clusters compared to physical ones as reported by Jackson et al. [26].”
- Performance Analysis of Google Colaboratory as a Tool for Accelerating Deep Learning Applications (2018, background): “[13] claim that the underlying network infrastructure of the EC2 cloud platform severely limits performance.”