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add gpu-level load balance for global policy

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close #14
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Shaoyuan CHEN 2025-03-21 17:11:10 +08:00
parent 3079d71e1f
commit e1100fefe7
1 changed files with 1 additions and 2 deletions
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eplb.py
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@ -15,7 +15,6 @@ def balanced_packing(weight: torch.Tensor, num_packs: int) -> Tuple[torch.Tensor
pack_index: [X, n], the pack index of each item pack_index: [X, n], the pack index of each item
rank_in_pack: [X, n], the rank of the item in the pack rank_in_pack: [X, n], the rank of the item in the pack
""" """
num_layers, num_groups = weight.shape num_layers, num_groups = weight.shape
assert num_groups % num_packs == 0 assert num_groups % num_packs == 0
groups_per_pack = num_groups // num_packs groups_per_pack = num_groups // num_packs
@ -153,7 +152,7 @@ def rebalance_experts(weight: torch.Tensor, num_replicas: int, num_groups: int,
num_groups, num_nodes, num_gpus) num_groups, num_nodes, num_gpus)
else: else:
# use global load-balance policy # use global load-balance policy
phy2log, phyrank, logcnt = replicate_experts(weight, num_replicas) phy2log, phyrank, logcnt = rebalance_experts_hierarchical(weight, num_replicas, 1, 1, num_gpus)
maxlogcnt = logcnt.max().item() maxlogcnt = logcnt.max().item()
log2phy: torch.Tensor = torch.full((num_layers, num_logical_experts, maxlogcnt), log2phy: torch.Tensor = torch.full((num_layers, num_logical_experts, maxlogcnt),
-1, dtype=torch.int64, device=logcnt.device) -1, dtype=torch.int64, device=logcnt.device)