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Limit amount of pinned memory on windows to prevent issues. #10638

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Merged
comfyanonymous merged 1 commit into from
Nov 4, 2025
Merged

Limit amount of pinned memory on windows to prevent issues. #10638

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32 changes: 28 additions & 4 deletions comfy/model_management.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1082,8 +1082,20 @@ def cast_to_device(tensor, device, dtype, copy=False):
non_blocking = device_supports_non_blocking(device)
return cast_to(tensor, dtype=dtype, device=device, non_blocking=non_blocking, copy=copy)


PINNED_MEMORY = {}
TOTAL_PINNED_MEMORY = 0
if PerformanceFeature.PinnedMem in args.fast:
if WINDOWS:
MAX_PINNED_MEMORY = get_total_memory(torch.device("cpu")) * 0.45 # Windows limit is apparently 50%
else:
MAX_PINNED_MEMORY = get_total_memory(torch.device("cpu")) * 0.95
else:
MAX_PINNED_MEMORY = -1

def pin_memory(tensor):
if PerformanceFeature.PinnedMem not in args.fast:
global TOTAL_PINNED_MEMORY
if MAX_PINNED_MEMORY <= 0:
return False

if not is_nvidia():
Expand All @@ -1092,13 +1104,21 @@ def pin_memory(tensor):
if not is_device_cpu(tensor.device):
return False

if torch.cuda.cudart().cudaHostRegister(tensor.data_ptr(), tensor.numel() * tensor.element_size(), 1) == 0:
size = tensor.numel() * tensor.element_size()
if (TOTAL_PINNED_MEMORY + size) > MAX_PINNED_MEMORY:
return False

ptr = tensor.data_ptr()
if torch.cuda.cudart().cudaHostRegister(ptr, size, 1) == 0:
PINNED_MEMORY[ptr] = size
TOTAL_PINNED_MEMORY += size
return True

return False

def unpin_memory(tensor):
if PerformanceFeature.PinnedMem not in args.fast:
global TOTAL_PINNED_MEMORY
if MAX_PINNED_MEMORY <= 0:
return False

if not is_nvidia():
Expand All @@ -1107,7 +1127,11 @@ def unpin_memory(tensor):
if not is_device_cpu(tensor.device):
return False

if torch.cuda.cudart().cudaHostUnregister(tensor.data_ptr()) == 0:
ptr = tensor.data_ptr()
if torch.cuda.cudart().cudaHostUnregister(ptr) == 0:
TOTAL_PINNED_MEMORY -= PINNED_MEMORY.pop(ptr)
if len(PINNED_MEMORY) == 0:
TOTAL_PINNED_MEMORY = 0
return True

return False
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