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 ==
+
The 0.5 Hz numbers are taken from Study 14.2.
  
SGTs: At 0.5 Hz, it requires 35 GPU node-hrs per component.
+
== 1.0 Hz, 3 component ==
  (35 GPU node-hrs per component) x (3 components) x (8 times the gridpoints) x (2 times the timesteps) x (20% more efficient due to more work per GPU) = 1350 node-hrs per site.
 
  
PP: At 0.5 Hz, it requires 30 CPU node-hrs per component.
+
SGTs: At 0.5 Hz, it requires 38 GPU 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.
+
   (38 GPU node-hrs per component) x (3 components) x (8 times the gridpoints) x (2 times the timesteps) x (20% more efficient due to more work per GPU) = 1460 node-hrs per site.
  
'''5850''' node-hours per 3-component site (187k core-hours)
+
23% of node hours to SGTs.
  
'''1.67M''' node-hours for standard 3-component So Cal 286-site map (53.5M core-hours)
+
PP: At 0.5 Hz, it requires 41 CPU node-hrs per component.
 +
  (41 CPU node-hrs per components) x (3 components) x (25 times the rupture points) x (2 times the timesteps) x (20% more efficient due to rupture generator improvements) = 4920 node-hrs per site.
  
'''5.25M''' node-hours for increased density 3-component So Cal 898-site map (168M core-hours)
+
77% of node hours to PP.
  
'''8.18M''' node-hours for statewide adaptive 3-component California 1400-site map (262M core-hours)
+
'''6380''' node-hours per 3-component site (181k core-hours)
 +
 
 +
'''1.82M''' node-hours for standard 3-component So Cal 286-site map (51.7M core-hours)
 +
 
 +
'''5.73M''' node-hours for increased density 3-component So Cal 898-site map (162M core-hours)
 +
 
 +
'''8.93M''' node-hours for statewide adaptive 3-component California 1400-site map (253M core-hours)
  
 
== 2.0 Hz ==
 
== 2.0 Hz ==
  
SGTs: At 1.0 Hz, it requires 450 GPU node-hrs per component.
+
SGTs: At 1.0 Hz, it requires 485 GPU node-hrs per component.
   (450 GPU node-hrs per component) x (3 components) x (8 times the gridpoints) x (2 times the timesteps) = 22k node-hrs per site.
+
   (485 GPU node-hrs per component) x (3 components) x (8 times the gridpoints) x (2 times the timesteps) = 23.3k node-hrs per site.
  
PP: At 1.0 Hz, it requires 1500 CPU node-hrs per component.
+
PP: At 1.0 Hz, it requires 1640 CPU node-hrs per component.
   (1500 CPU node-hrs per components) x (3 components) x (2 times the timesteps) = 9k node-hrs per site.
+
   (1640 CPU node-hrs per components) x (3 components) x (2 times the timesteps) = 9.8k node-hrs per site.
  
'''31k''' node-hours per 3-component site (976k core-hours)
+
'''33.1k''' node-hours per 3-component site (686k core-hours)
  
'''8.72M''' node-hours for standard 3-component So Cal 286-site map (279M core-hours)
+
'''9.47M''' node-hours for standard 3-component So Cal 286-site map (196M core-hours)
  
'''108M''' node-hours for increased density 3-component So Cal 3545-site map (3.5B core-hours)
+
'''117M''' node-hours for increased density 3-component So Cal 3545-site map (2.4B core-hours)
  
'''35M''' node-hours for statewide adaptive 3-component California 1400-site map (1.1B core-hours)
+
'''46.3M''' node-hours for statewide adaptive 3-component California 1400-site map (960M core-hours)

Revision as of 19:54, 13 May 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.

The 0.5 Hz numbers are taken from Study 14.2.

1.0 Hz, 3 component

SGTs: At 0.5 Hz, it requires 38 GPU node-hrs per component.

 (38 GPU node-hrs per component) x (3 components) x (8 times the gridpoints) x (2 times the timesteps) x (20% more efficient due to more work per GPU) = 1460 node-hrs per site.

23% of node hours to SGTs.

PP: At 0.5 Hz, it requires 41 CPU node-hrs per component.

 (41 CPU node-hrs per components) x (3 components) x (25 times the rupture points) x (2 times the timesteps) x (20% more efficient due to rupture generator improvements) = 4920 node-hrs per site.

77% of node hours to PP.

6380 node-hours per 3-component site (181k core-hours)

1.82M node-hours for standard 3-component So Cal 286-site map (51.7M core-hours)

5.73M node-hours for increased density 3-component So Cal 898-site map (162M core-hours)

8.93M node-hours for statewide adaptive 3-component California 1400-site map (253M core-hours)

2.0 Hz

SGTs: At 1.0 Hz, it requires 485 GPU node-hrs per component.

 (485 GPU node-hrs per component) x (3 components) x (8 times the gridpoints) x (2 times the timesteps) = 23.3k node-hrs per site.

PP: At 1.0 Hz, it requires 1640 CPU node-hrs per component.

 (1640 CPU node-hrs per components) x (3 components) x (2 times the timesteps) = 9.8k node-hrs per site.

33.1k node-hours per 3-component site (686k core-hours)

9.47M node-hours for standard 3-component So Cal 286-site map (196M core-hours)

117M node-hours for increased density 3-component So Cal 3545-site map (2.4B core-hours)

46.3M node-hours for statewide adaptive 3-component California 1400-site map (960M core-hours)