Difference between revisions of "Cloud Telecons 10/24/2016"
From Earth Science Information Partners (ESIP)
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# Access Code: 445-841-573 | # Access Code: 445-841-573 | ||
| − | === | + | === October 24, 2016 ESIP cloud computing cluster telecon recap=== |
'''Participants:'''Joseph C Jacob, Pham Long, Stephan Klene, Frank Greguska, Thomas Huang, Fei Hu, Phil Yang,(this list might miss somebody else. If there is anyone else, please help add them here. Thanks!)<br> | '''Participants:'''Joseph C Jacob, Pham Long, Stephan Klene, Frank Greguska, Thomas Huang, Fei Hu, Phil Yang,(this list might miss somebody else. If there is anyone else, please help add them here. Thanks!)<br> | ||
| − | Discussion notes: | + | '''Discussion notes''': |
:*How did NASA use commercial cloud, such as Amazon? What kind of projects need to set up its own cloud in an affordable manner. One of Amazon advantages is to scale up resources. The private could need consider the largest resource for the worst case. On Amazon, you just need pay as you go . | :*How did NASA use commercial cloud, such as Amazon? What kind of projects need to set up its own cloud in an affordable manner. One of Amazon advantages is to scale up resources. The private could need consider the largest resource for the worst case. On Amazon, you just need pay as you go . | ||
:*When to make sense on cloud or hardware. Looking into the provision service, such as mapreduce, nosql, to accelerate their system | :*When to make sense on cloud or hardware. Looking into the provision service, such as mapreduce, nosql, to accelerate their system | ||
:*Technical session: how do people apply cloud computing on their scientific researches. | :*Technical session: how do people apply cloud computing on their scientific researches. | ||
| − | :*The comparison between Google computing engine, Microsoft Azure, Amazon, Redhat, etc. Look into their features, differences, and potential cost. The cost estimator from GMU for different cloud can be useful, but the information need be updated. Two keys for cloud service users: 1) how much is the cost overtime? 2)how to grow the system overtime? | + | :*The comparison between Google computing engine, Microsoft Azure, Amazon, Redhat, etc. Look into their features, differences, and potential cost. The cost estimator from GMU for different cloud platforms can be useful, but the information need be updated. Two keys for cloud service users: 1) how much is the cost overtime? 2)how to grow the system overtime? |
:*GPU to accelerate the analysis/software on Cloud; how much the cost of GPU on Amazon? Several issues with GPU may need to be solved: data into GPU/ data movement/ IO bottleneck. | :*GPU to accelerate the analysis/software on Cloud; how much the cost of GPU on Amazon? Several issues with GPU may need to be solved: data into GPU/ data movement/ IO bottleneck. | ||
| − | Summary for session proposal: | + | '''Summary for session proposal''': |
:*comparing of using public cloud and private cloud. | :*comparing of using public cloud and private cloud. | ||
:*comparison between different venders: google redhat etc. | :*comparison between different venders: google redhat etc. | ||
| Line 22: | Line 22: | ||
:*application of cloud (including big data) to solve their projects or missions | :*application of cloud (including big data) to solve their projects or missions | ||
| − | Reminder: | + | '''Reminder''': |
:*send the session proposal by this week | :*send the session proposal by this week | ||
Latest revision as of 13:43, October 24, 2016
Telecon Info
To start the online portion of the Personal Conference meeting
- Go to https://global.gotomeeting.com/join/445841573
- You can also dial in using your phone: United States +1 (571) 317-3112
- Access Code: 445-841-573
October 24, 2016 ESIP cloud computing cluster telecon recap
Participants:Joseph C Jacob, Pham Long, Stephan Klene, Frank Greguska, Thomas Huang, Fei Hu, Phil Yang,(this list might miss somebody else. If there is anyone else, please help add them here. Thanks!)
Discussion notes:
- How did NASA use commercial cloud, such as Amazon? What kind of projects need to set up its own cloud in an affordable manner. One of Amazon advantages is to scale up resources. The private could need consider the largest resource for the worst case. On Amazon, you just need pay as you go .
- When to make sense on cloud or hardware. Looking into the provision service, such as mapreduce, nosql, to accelerate their system
- Technical session: how do people apply cloud computing on their scientific researches.
- The comparison between Google computing engine, Microsoft Azure, Amazon, Redhat, etc. Look into their features, differences, and potential cost. The cost estimator from GMU for different cloud platforms can be useful, but the information need be updated. Two keys for cloud service users: 1) how much is the cost overtime? 2)how to grow the system overtime?
- GPU to accelerate the analysis/software on Cloud; how much the cost of GPU on Amazon? Several issues with GPU may need to be solved: data into GPU/ data movement/ IO bottleneck.
Summary for session proposal:
- comparing of using public cloud and private cloud.
- comparison between different venders: google redhat etc.
- some researches that move to cloud and truly leverage the provision service
- application of cloud (including big data) to solve their projects or missions
Reminder:
- send the session proposal by this week
