Cloud Performance Reports
Cloud computing is getting a great deal of attention these days. Unfortunately, there is very little data available about performance, scalability and usability of the cloud deployment platforms.
I was recently invited to speak at Silicon Valley Cloud User Group where I tried to bring a "practitioner's prospective" and present the results of three different recent performance and scalability benchmarks related to the cloud computing. The first benchmark aims to establish the scalability of EC2 on a perfectly parallel mathematical problem, a Monte Carlo simulation, executed by Grid Gain's popular open source map/reduce platform - and to document lessons learned in making the application scale to 512 nodes.
The second benchmark looks at a scalability of a more complex stateful application, typical to Risk Management, that required both in-memory data grid and compute grid. Both grids were running on EC2 and executed by GigaSpaces' data & compute grid platform.
The third benchmark looks at a prototypical data-intensive Portfolio Analysis application used heavily in the financial services industry, and studies the performance impact of data being located close to computing, or "on the cloud" vs. "off the cloud". This work was done in collaboration with Microsoft on their HPC++ CompFin Lab that integrates Microsoft Windows HPC Server, a central market data database and Microsoft productivity products to provide academic community with an online service to publish, execute and manage computational finance models.
You can find the presentation, with summary of results here. Please, note that these results are very fresh and the benchmarks in two cases are still going on. You can find far more details on the first benchmark in our previous blog post. We will be coming with more detailed blog reports for the second and third benchmarks soon.
I was recently invited to speak at Silicon Valley Cloud User Group where I tried to bring a "practitioner's prospective" and present the results of three different recent performance and scalability benchmarks related to the cloud computing. The first benchmark aims to establish the scalability of EC2 on a perfectly parallel mathematical problem, a Monte Carlo simulation, executed by Grid Gain's popular open source map/reduce platform - and to document lessons learned in making the application scale to 512 nodes.
The second benchmark looks at a scalability of a more complex stateful application, typical to Risk Management, that required both in-memory data grid and compute grid. Both grids were running on EC2 and executed by GigaSpaces' data & compute grid platform.
The third benchmark looks at a prototypical data-intensive Portfolio Analysis application used heavily in the financial services industry, and studies the performance impact of data being located close to computing, or "on the cloud" vs. "off the cloud". This work was done in collaboration with Microsoft on their HPC++ CompFin Lab that integrates Microsoft Windows HPC Server, a central market data database and Microsoft productivity products to provide academic community with an online service to publish, execute and manage computational finance models.
You can find the presentation, with summary of results here. Please, note that these results are very fresh and the benchmarks in two cases are still going on. You can find far more details on the first benchmark in our previous blog post. We will be coming with more detailed blog reports for the second and third benchmarks soon.
1 Comments:
Thanks for sharing, Victoria!
So does cloud computing make the grade? Pass or fail? Or will there be other benchmarks beyond the third one?
Looking forward to reading more about it, soon.
Best.
alain
mor.ph
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