Difference between revisions of "CyberShake Computational Estimates"
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The UCERF 3 estimates assume that the number of ruptures increases from 15,000 to 350,000, but the number of rupture variations per rupture on average remains the same. | The UCERF 3 estimates assume that the number of ruptures increases from 15,000 to 350,000, but the number of rupture variations per rupture on average remains the same. | ||
| − | == | + | == 1.0 Hz == |
| − | + | SGTs: At 0.5 Hz, it requires 35 GPU node-hrs per component. | |
| + | (35 GPU node-hrs per component) x (3 components) x (8 times the gridpoints) x (2 times the timesteps) = 1680 node-hrs per site. | ||
| − | + | PP: At 0.5 Hz, it requires 30 CPU node-hrs per component. | |
| − | + | (30 CPU node-hrs per components) x (3 components) x (25 times the rupture points) x (2 times the timesteps) = 4500 node-hrs per site. | |
| − | |||
| − | + | '''6180''' node-hours per 3-component site (200k core-hours) | |
| − | + | '''1.77M''' node-hours for standard 3-component So Cal 286-site map (56.6M core-hours) | |
| − | + | '''5.55M''' node-hours for increased density 3-component So Cal 898-site map (178M core-hours) | |
| − | + | '''8.65M''' node-hours for statewide adaptive 3-component California 1400-site map (277M core-hours) | |
| − | + | == 2.0 Hz == | |
| − | + | SGTs: At 1.0 Hz, it requires 560 GPU node-hrs per component. | |
| + | (560 GPU node-hrs per component) x (3 components) x (8 times the gridpoints) x (2 times the timesteps) = 27k node-hrs per site. | ||
| − | PP | + | PP: At 1.0 Hz, it requires 1500 CPU node-hrs per component. |
| + | (1500 CPU node-hrs per components) x (3 components) x (2 times the timesteps) = 9k node-hrs per site. | ||
| − | + | '''36k''' node-hours per 3-component site (1.1M core-hours) | |
| − | + | '''10.3M''' node-hours for standard 3-component So Cal 286-site map (328M core-hours) | |
| − | + | '''127M''' node-hours for increased density 3-component So Cal 3545-site map (4.1B core-hours) | |
| − | + | '''50.2M''' node-hours for statewide adaptive 3-component California 1400-site map (1.6B core-hours) | |
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Revision as of 20:26, 5 March 2014
We will describe or current best estimates for the CyberShake computational and data requirements as we progress in our simulation planning and testing. These estimates will help us identify which aspects of the CyberShake computational system needs to be optimized to work within our time and resource constraints.
The UCERF 3 estimates assume that the number of ruptures increases from 15,000 to 350,000, but the number of rupture variations per rupture on average remains the same.
1.0 Hz
SGTs: At 0.5 Hz, it requires 35 GPU node-hrs per component.
(35 GPU node-hrs per component) x (3 components) x (8 times the gridpoints) x (2 times the timesteps) = 1680 node-hrs per site.
PP: At 0.5 Hz, it requires 30 CPU node-hrs per component.
(30 CPU node-hrs per components) x (3 components) x (25 times the rupture points) x (2 times the timesteps) = 4500 node-hrs per site.
6180 node-hours per 3-component site (200k core-hours)
1.77M node-hours for standard 3-component So Cal 286-site map (56.6M core-hours)
5.55M node-hours for increased density 3-component So Cal 898-site map (178M core-hours)
8.65M node-hours for statewide adaptive 3-component California 1400-site map (277M core-hours)
2.0 Hz
SGTs: At 1.0 Hz, it requires 560 GPU node-hrs per component.
(560 GPU node-hrs per component) x (3 components) x (8 times the gridpoints) x (2 times the timesteps) = 27k node-hrs per site.
PP: At 1.0 Hz, it requires 1500 CPU node-hrs per component.
(1500 CPU node-hrs per components) x (3 components) x (2 times the timesteps) = 9k node-hrs per site.
36k node-hours per 3-component site (1.1M core-hours)
10.3M node-hours for standard 3-component So Cal 286-site map (328M core-hours)
127M node-hours for increased density 3-component So Cal 3545-site map (4.1B core-hours)
50.2M node-hours for statewide adaptive 3-component California 1400-site map (1.6B core-hours)
