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EdgeComputer

A computer-like EdgeDevice described by aggregate CPU, RAM, and storage specs. Internally creates standard EdgeCPUComponent, EdgeRAMComponent, and reuses the provided EdgeStorage so loads can be sized against component capacity.

When to use this class

Use EdgeComputer for general-purpose edge compute hardware where CPU, RAM, and storage matter. Use EdgeAppliance for sealed appliance-style hardware described only by total power and embodied carbon. Use EdgeDevice for fully bespoke hardware.

Params

name

A human readable description of the object.

carbon_footprint_fabrication

Embodied carbon emitted to manufacture one computer.

Unit: kilogram.

power

Electrical power drawn at full load.

Unit: watt.

lifespan

Expected time before the computer is replaced. Embodied carbon is amortised over this duration.

Unit: year.

idle_power

Electrical power drawn at zero load.

Unit: watt.

ram

Memory available on one computer.

Unit: gigabyte_ram.

compute

Compute capacity available on one computer, expressed in CPU cores.

Unit: cpu_core.

base_ram_consumption

RAM consumed independently of recurring needs (operating system, baseline processes).

Unit: gigabyte_ram.

base_compute_consumption

Compute consumed independently of recurring needs.

Unit: cpu_core.

storage

EdgeStorage component holding persistent data on the computer.

An instance of EdgeStorage.

Calculated attributes

structure_carbon_footprint_fabrication

Structure fabrication footprint of the computer, copied from the computer's own fabrication footprint since the auto-created sub-components carry no separate fabrication contribution.

Example value: 60 kg

Depends directly on:

through the following calculations:

You can also visit the link to Structure fabrication carbon footprint’s full calculation graph.

lifespan_validation

Validates that the device lifespan is at least as long as every EdgeUsageJourney that uses it; raises otherwise.

Example value: no value

Depends directly on:

through the following calculations:

You can also visit the link to no value’s full calculation graph.

component_needs_edge_device_validation

Validates that every RecurrentEdgeComponentNeed loaded onto this device targets a component that actually belongs to it.

Example value: no value

Depends directly on:

through the following calculations:

You can also visit the link to no value’s full calculation graph.

total_nb_of_units

How many copies of the device are deployed in total once group hierarchies are unrolled. Defaults to 1 if the device is not in any EdgeDeviceGroup.

Example value: 1

Depends directly on:

through the following calculations:

You can also visit the link to no group (default count = 1)’s full calculation graph.

structure_fabrication_footprint_per_usage_pattern

Hourly fabrication-phase emissions of the chassis (excluding components), broken down by usage pattern.

Example value: {
EdgeUsagePattern Default edge usage pattern (7d23cf): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in t:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0.000854, 0.00171, 0.00256],
last 10 vals [0.00428, 0.00427, 0.00427, 0.00428, 0.00428, 0.00342, 0.00256, 0.00171, 0.000853, 0],
}

Depends directly on:

through the following calculations:

You can also visit the link to Hourly structure fabrication footprint for Default edge usage pattern’s full calculation graph.

instances_fabrication_footprint_per_usage_pattern

Hourly fabrication-phase emissions of the whole device (chassis plus all components), broken down by usage pattern.

Example value: {
EdgeUsagePattern Default edge usage pattern (7d23cf): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in t:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0.00163, 0.00326, 0.0049],
last 10 vals [0.00817, 0.00816, 0.00817, 0.00817, 0.00817, 0.00653, 0.0049, 0.00326, 0.00163, 0],
}

Depends directly on:

through the following calculations:

You can also visit the link to Hourly instances fabrication footprint for Default edge usage pattern’s full calculation graph.

instances_energy_per_usage_pattern

Hourly energy consumed by the whole device, broken down by usage pattern. Equal to the sum of component-level energy multiplied by the device count.

Example value: {
EdgeUsagePattern Default edge usage pattern (7d23cf): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in MWh:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0.00843, 0.0169, 0.0253],
last 10 vals [0.0422, 0.0421, 0.0422, 0.0422, 0.0422, 0.0337, 0.0253, 0.0168, 0.00841, 0],
}

Depends directly on:

through the following calculations:

You can also visit the link to Hourly energy consumed by instances for Default edge usage pattern’s full calculation graph.

energy_footprint_per_usage_pattern

Hourly carbon emissions caused by device electricity use, broken down by usage pattern. Equal to component-level energy footprints summed and multiplied by the device count.

Example value: {
EdgeUsagePattern Default edge usage pattern (7d23cf): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in t:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0.000716, 0.00143, 0.00215],
last 10 vals [0.00358, 0.00358, 0.00358, 0.00358, 0.00358, 0.00287, 0.00215, 0.00143, 0.000715, 0],
}

Depends directly on:

through the following calculations:

You can also visit the link to Energy footprint for Default edge usage pattern’s full calculation graph.

instances_fabrication_footprint

Total hourly fabrication-phase carbon footprint, summed across every usage pattern.

Example value: 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in t:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0.00163, 0.00326, 0.0049],
last 10 vals [0.00817, 0.00816, 0.00817, 0.00817, 0.00817, 0.00653, 0.0049, 0.00326, 0.00163, 0]

Depends directly on:

through the following calculations:

You can also visit the link to Total fabrication footprint across usage patterns’s full calculation graph.

fabrication_footprint_breakdown_by_source

Per-component breakdown of the device's fabrication footprint, attributing each component's own embodied carbon plus an even share of the chassis fabrication.

Example value: {
EdgeComputerCPUComponent edge computer CPU (6bc540): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in t:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0.000285, 0.00057, 0.000855],
last 10 vals [0.00143, 0.00142, 0.00142, 0.00143, 0.00143, 0.00114, 0.000855, 0.000569, 0.000284, 0],
EdgeComputerRAMComponent edge computer RAM (491c7e): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in t:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0.000285, 0.00057, 0.000855],
last 10 vals [0.00143, 0.00142, 0.00142, 0.00143, 0.00143, 0.00114, 0.000855, 0.000569, 0.000284, 0],
EdgeStorage edge SSD storage (b018bd): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in t:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0.00106, 0.00213, 0.00319],
last 10 vals [0.00532, 0.00531, 0.00532, 0.00532, 0.00532, 0.00425, 0.00319, 0.00212, 0.00106, 0],
}

Depends directly on:

through the following calculations:

You can also visit the link to Fabrication footprint attributed to edge computer CPU’s full calculation graph.

instances_energy

Total hourly energy consumed by all instances of the device, summed across every usage pattern.

Example value: 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in MWh:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0.00843, 0.0169, 0.0253],
last 10 vals [0.0422, 0.0421, 0.0422, 0.0422, 0.0422, 0.0337, 0.0253, 0.0168, 0.00841, 0]

Depends directly on:

through the following calculations:

You can also visit the link to Total energy consumed across usage patterns’s full calculation graph.

energy_footprint

Total hourly energy-use carbon footprint, summed across every usage pattern.

Example value: 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in t:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0.000716, 0.00143, 0.00215],
last 10 vals [0.00358, 0.00358, 0.00358, 0.00358, 0.00358, 0.00287, 0.00215, 0.00143, 0.000715, 0]

Depends directly on:

through the following calculations:

You can also visit the link to Total energy footprint across usage patterns’s full calculation graph.

fabrication_impact_repartition_weights

Per-RecurrentEdgeComponentNeed weights used to attribute the device's fabrication footprint to the needs that load each component, proportional to each need's share of demand.

Example value: {
RecurrentEdgeProcessRAMNeed edge process RAM need (68d204): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in t:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0.000285, 0.00057, 0.000855],
last 10 vals [0.00143, 0.00142, 0.00142, 0.00143, 0.00143, 0.00114, 0.000855, 0.000569, 0.000284, 0],
RecurrentEdgeProcessCPUNeed edge process CPU need (fe2f3c): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in t:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0.000285, 0.00057, 0.000855],
last 10 vals [0.00143, 0.00142, 0.00142, 0.00143, 0.00143, 0.00114, 0.000855, 0.000569, 0.000284, 0],
RecurrentEdgeProcessStorageNeed edge process storage need (d15383): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in t:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
last 10 vals [0.00532, 0.00531, 0.00532, 0.00532, 0.00532, 0.00425, 0.00319, 0.00212, 0.00106, 0],
}

Depends directly on:

through the following calculations:

You can also visit the link to edge process RAM need fabrication weight in impact repartition’s full calculation graph.

fabrication_impact_repartition_weight_sum

Sum of fabrication impact repartition weights, used as the denominator when normalising into per-container shares.

Example value: 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in t:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0.00057, 0.00114, 0.00171],
last 10 vals [0.00817, 0.00816, 0.00817, 0.00817, 0.00817, 0.00653, 0.0049, 0.00326, 0.00163, 0]

Depends directly on:

through the following calculations:

You can also visit the link to Fabrication impact repartition weights sum’s full calculation graph.

fabrication_impact_repartition

Normalised share of fabrication-phase emissions that this object attributes to each container.

Example value: {
RecurrentEdgeProcessRAMNeed edge process RAM need (68d204): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in :
first 10 vals [1, 1, 1, 1, 1, 1, 1, 0.5, 0.5, 0.5],
last 10 vals [0.174, 0.174, 0.174, 0.174, 0.174, 0.174, 0.174, 0.174, 0.174, 1],
RecurrentEdgeProcessCPUNeed edge process CPU need (fe2f3c): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in :
first 10 vals [1, 1, 1, 1, 1, 1, 1, 0.5, 0.5, 0.5],
last 10 vals [0.174, 0.174, 0.174, 0.174, 0.174, 0.174, 0.174, 0.174, 0.174, 1],
RecurrentEdgeProcessStorageNeed edge process storage need (d15383): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in :
first 10 vals [1, 1, 1, 1, 1, 1, 1, 0, 0, 0],
last 10 vals [0.651, 0.651, 0.651, 0.651, 0.651, 0.651, 0.651, 0.651, 0.651, 1],
}

Depends directly on:

through the following calculations:

You can also visit the link to fabrication impact attribution to edge process RAM need’s full calculation graph.

usage_impact_repartition_weights

Per-RecurrentEdgeComponentNeed weights used to attribute the device's energy-use footprint to the needs that load each component.

Example value: {
RecurrentEdgeProcessRAMNeed edge process RAM need (68d204): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in mg:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
last 10 vals [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
RecurrentEdgeProcessCPUNeed edge process CPU need (fe2f3c): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in t:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0.000716, 0.00143, 0.00215],
last 10 vals [0.00358, 0.00358, 0.00358, 0.00358, 0.00358, 0.00287, 0.00215, 0.00143, 0.000715, 0],
RecurrentEdgeProcessStorageNeed edge process storage need (d15383): no value,
}

Depends directly on:

through the following calculations:

You can also visit the link to edge process RAM need usage weight in impact repartition’s full calculation graph.

usage_impact_repartition_weight_sum

Sum of usage impact repartition weights, used as the denominator when normalising into per-container shares.

Example value: 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in t:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0.000716, 0.00143, 0.00215],
last 10 vals [0.00358, 0.00358, 0.00358, 0.00358, 0.00358, 0.00287, 0.00215, 0.00143, 0.000715, 0]

Depends directly on:

through the following calculations:

You can also visit the link to Usage impact repartition weights sum’s full calculation graph.

usage_impact_repartition

Normalised share of usage-phase emissions that this object attributes to each container.

Example value: {
RecurrentEdgeProcessRAMNeed edge process RAM need (68d204): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in :
first 10 vals [1, 1, 1, 1, 1, 1, 1, 0, 0, 0],
last 10 vals [0, 0, 0, 0, 0, 0, 0, 0, 0, 1],
RecurrentEdgeProcessCPUNeed edge process CPU need (fe2f3c): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in :
first 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
last 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
RecurrentEdgeProcessStorageNeed edge process storage need (d15383): no value,
}

Depends directly on:

through the following calculations:

You can also visit the link to usage impact attribution to edge process RAM need’s full calculation graph.