GPU series
Specs and scheduling parameters for one class of GPU (h200 / h100 built-in defaults, overridable viaFORGE_HARDWARE_SERIES JSON):
Profiles
GPU series + default shape + tuning overrides (built-in defaults, overridable viaFORGE_CLUSTER_PROFILES):
name/series/num_nodes/gpus_per_node: the shape is the authoritative topology for quotas and training;env: process environment (NCCL, Ray memory thresholds, PyTorch allocator) — for multi-node, must be identical to what ray start sees;overrides: framework override entries (parallelism, vLLM memory fraction, micro batch). Only put keys shared by all experiments (CLI overrides use struct mode — changing a non-existent key raises an error).
FORGE_HWCONFIG_REFRESH_INTERVAL).
User quotas
FORGE_QUOTA_ENFORCE=0 downgrades the whole system to “record only, don’t block” (for trial periods).
Storage quota
--max-storage-gb caps the total held by all of a user’s run directories
(working copy + checkpoints + logs). It counts runs/<user>/; the caches
(weights, datasets, corpora) are shared platform infrastructure and are not
charged to anyone — the weights one job pulls, every later job uses.
They answer different questions: the quota is “who is holding too much”, the
watermark is “the disk is about to fill”.
Schedule windows
Restrict daily run windows per GPU series (Admin → Platform settings → Schedules):
Jobs paused this way resume training automatically when the window reopens.