Data Center Configuration File

This file defines one or more data center entries under the top-level datacenters key. Each entry describes the compute, memory, and geographic characteristics of a single data center. Below is an example structure; see the field descriptions that follow.

datacenters:
  - dc_id: 1
    location: "US-CAL-CISO"
    timezone_shift: -7
    population_weight: 0.18
    total_cores: 50000
    total_gpus: 1000
    total_mem: 80000
    dc_config_file: "configs/dcs/dc_config.json"

  - dc_id: 2
    location: "DE-LU"
    timezone_shift: 1
    population_weight: 0.22
    total_cores: 85000
    total_gpus: 600
    total_mem: 80000
    dc_config_file: "configs/dcs/dc_config.json"

  - dc_id: 3
    location: "CL-SIC"
    timezone_shift: -5
    population_weight: 0.20
    total_cores: 110000
    total_gpus: 300
    total_mem: 60000
    dc_config_file: "configs/dcs/dc_config.json"

  - dc_id: 4
    location: "SG"
    timezone_shift: 8
    population_weight: 0.25
    total_cores: 15000
    total_gpus: 700
    total_mem: 50000
    dc_config_file: "configs/dcs/dc_config.json"

  - dc_id: 5
    location: "AU-NSW"
    timezone_shift: 11
    population_weight: 0.15
    total_cores: 25000
    total_gpus: 300
    total_mem: 60000
    dc_config_file: "configs/dcs/dc_config.json"

Field Reference

datacenters (list) : A sequence of data center definitions.

For each item in the list:

  • dc_id (integer) Unique identifier for the data center.

  • location (string) A short code representing the geographic region (e.g., “US-CAL-CISO”, “DE-LU”, “SG”).

  • timezone_shift (integer) Offset in hours from UTC for local time alignment (e.g., -7 for PDT, +1 for CET).

  • population_weight (float) Relative weight reflecting the fraction of total user population served by this data center.

  • total_cores (integer) Total number of CPU cores available in the data center.

  • total_gpus (integer) Total number of GPU devices available.

  • total_mem (integer) Total memory capacity in GB.

  • dc_config_file (string) Path to an additional JSON file containing advanced or region-specific parameters (e.g., rack layouts, power limits).

Usage

  1. Place your datacenters.yaml in the configs/ directory.

  2. Read this file via the load_yaml loader in train_rl_agent.py.

See also Main Configuration File for how to integrate this configuration into the main environment setup.