GPUJob
Params
name
A human readable description of the object.
server
An instance of GPUServer.
data_transferred
Sum of all data uploads and downloads for request manually defined gpu job in kilobyte.
data_stored
Data stored by request manually defined gpu job in kilobyte.
request_duration
Request duration of manually defined gpu job in second.
compute_needed
Gpus needed on server on premise gpu server to process manually defined gpu job in gpu.
ram_needed
Ram needed on server on premise gpu server to process manually defined gpu job in megabyte_ram.
Backwards links
Calculated attributes
hourly_occurrences_per_usage_pattern
Dictionary with UsagePattern as keys and Hourly manually defined gpu job occurrences in usagepattern usage pattern as values, in occurrence.
Example value: {
c374c9: 26298 values from 2024-12-31 23:00:00+00:00 to 2028-01-01 17:00:00+00:00 in occurrence:
first 10 vals [2.0, 4.0, 4.0, 8.0, 4.0, 2.0, 3.0, 6.0, 2.0, 6.0],
last 10 vals [4.0, 3.0, 7.0, 6.0, 3.0, 5.0, 6.0, 4.0, 5.0, 4.0],
}
Depends directly on:
through the following calculations:
You can also visit the link to Hourly Manually defined GPU job occurrences in UsagePattern usage pattern’s full calculation graph.
hourly_avg_occurrences_per_usage_pattern
Dictionary with UsagePattern as keys and Average hourly manually defined gpu job occurrences in usage pattern as values, in concurrent.
Example value: {
c374c9: 26298 values from 2024-12-31 23:00:00+00:00 to 2028-01-01 17:00:00+00:00 in concurrent:
first 10 vals [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
last 10 vals [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
}
Depends directly on:
- Hourly Manually defined GPU job occurrences in UsagePattern usage pattern
- Request duration of Manually defined GPU job from e-footprint hypothesis
through the following calculations:
You can also visit the link to Average hourly Manually defined GPU job occurrences in usage pattern’s full calculation graph.
hourly_data_transferred_per_usage_pattern
Dictionary with UsagePattern as keys and Hourly data transferred for manually defined gpu job in usage pattern as values, in megabyte.
Example value: {
c374c9: 26298 values from 2024-12-31 23:00:00+00:00 to 2028-01-01 17:00:00+00:00 in MB:
first 10 vals [0.3, 0.6, 0.6, 1.2, 0.6, 0.3, 0.45, 0.9, 0.3, 0.9],
last 10 vals [0.6, 0.45, 1.05, 0.9, 0.45, 0.75, 0.9, 0.6, 0.75, 0.6],
}
Depends directly on:
- Average hourly Manually defined GPU job occurrences in usage pattern
- Sum of all data uploads and downloads for request Manually defined GPU job from e-footprint hypothesis
- Request duration of Manually defined GPU job from e-footprint hypothesis
through the following calculations:
You can also visit the link to Hourly data transferred for Manually defined GPU job in usage pattern’s full calculation graph.
hourly_data_stored_per_usage_pattern
Dictionary with UsagePattern as keys and Hourly data stored for manually defined gpu job in usage pattern as values, in megabyte.
Example value: {
c374c9: 26298 values from 2024-12-31 23:00:00+00:00 to 2028-01-01 17:00:00+00:00 in MB:
first 10 vals [0.2, 0.4, 0.4, 0.8, 0.4, 0.2, 0.3, 0.6, 0.2, 0.6],
last 10 vals [0.4, 0.3, 0.7, 0.6, 0.3, 0.5, 0.6, 0.4, 0.5, 0.4],
}
Depends directly on:
- Average hourly Manually defined GPU job occurrences in usage pattern
- Data stored by request Manually defined GPU job from e-footprint hypothesis
- Request duration of Manually defined GPU job from e-footprint hypothesis
through the following calculations:
You can also visit the link to Hourly data stored for Manually defined GPU job in usage pattern’s full calculation graph.
hourly_avg_occurrences_across_usage_patterns
Hourly manually defined gpu job average occurrences across usage patterns in concurrent.
Example value: 26298 values from 2024-12-31 23:00:00+00:00 to 2028-01-01 17:00:00+00:00 in concurrent:
first 10 vals [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
last 10 vals [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
Depends directly on:
through the following calculations:
You can also visit the link to Hourly Manually defined GPU job average occurrences across usage patterns’s full calculation graph.
hourly_data_transferred_across_usage_patterns
Hourly manually defined gpu job data transferred across usage patterns in megabyte.
Example value: 26298 values from 2024-12-31 23:00:00+00:00 to 2028-01-01 17:00:00+00:00 in MB:
first 10 vals [0.3, 0.6, 0.6, 1.2, 0.6, 0.3, 0.45, 0.9, 0.3, 0.9],
last 10 vals [0.6, 0.45, 1.05, 0.9, 0.45, 0.75, 0.9, 0.6, 0.75, 0.6]
Depends directly on:
through the following calculations:
You can also visit the link to Hourly Manually defined GPU job data transferred across usage patterns’s full calculation graph.
hourly_data_stored_across_usage_patterns
Hourly manually defined gpu job data stored across usage patterns in megabyte.
Example value: 26298 values from 2024-12-31 23:00:00+00:00 to 2028-01-01 17:00:00+00:00 in MB:
first 10 vals [0.2, 0.4, 0.4, 0.8, 0.4, 0.2, 0.3, 0.6, 0.2, 0.6],
last 10 vals [0.4, 0.3, 0.7, 0.6, 0.3, 0.5, 0.6, 0.4, 0.5, 0.4]
Depends directly on:
through the following calculations:
You can also visit the link to Hourly Manually defined GPU job data stored across usage patterns’s full calculation graph.