Evaluating high-performance computing on google app engine

IEEE Software

Volumn 29, Issue 2, 2012, Pages 52-58

  Prodan, Radu ^a   Sperk, Michael ^a   Ostermann, Simon ^a  

^a UNIVERSITY OF INNSBRUCK   (Austria)

Author keywords

Amazon EC2; Amazon Elastic Compute Cloud; cloud computing; GAE; Google App Engine; high performance computing; performance analysis; software engineering

Indexed keywords

AMAZON EC2; EXPERIMENTAL APPROACHES; FAST PROTOTYPING; GAE; HIGH-PERFORMANCE COMPUTING; MASTER-SLAVE; MONTE CARLO SIMULATION; PERFORMANCE ANALYSIS;

CLOUD COMPUTING; COMPUTER SOFTWARE SELECTION AND EVALUATION; MIDDLEWARE; MONTE CARLO METHODS; PARALLEL ARCHITECTURES; SOFTWARE ENGINEERING;

INTERNET;

EID: 84857575482     PISSN: 07407459     EISSN: None     Source Type: Journal    
DOI: 10.1109/MS.2011.131     Document Type: Article

References (4)

1. D. Sanderson, Programming Google App Engine, O'Reilly Media, 2009.
2. A. Iosup et al., "Performance Analysis of Cloud Computing Services for Many-Tasks Scientifi c Computing," IEEE Trans. Parallel and Distributed Systems, vol. 22, no. 6, 2011, pp. 931-945.
3. M. Sperk, "Scientifi c Computing in the Cloud with Google App Engine," master's thesis, Faculty of Mathematics, Computer Science, and Physics, Univ. of Innsbruck, 2011; http:// dps.uibk.ac.at/-radu/sperk.pdf.
4. J.L. Gustafson, "Reevaluating Amdahl's Law," Comm. ACM, vol. 31, no. 5, 1988, pp. 532-533