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Enable pinned memory by default on Nvidia. (#10656)

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Removed the --fast pinned_memory flag.

You can use --disable-pinned-memory to disable it. Please report if it
causes any issues.
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comfyanonymous 2025-11-05 15:08:13 -08:00 committed by GitHub
parent 97f198e421
commit 1d69245981
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2 changed files with 11 additions and 14 deletions
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3
comfy/cli_args.py
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@ -145,10 +145,11 @@ class PerformanceFeature(enum.Enum):
Fp8MatrixMultiplication = "fp8_matrix_mult" Fp8MatrixMultiplication = "fp8_matrix_mult"
CublasOps = "cublas_ops" CublasOps = "cublas_ops"
AutoTune = "autotune" AutoTune = "autotune"
PinnedMem = "pinned_memory"
parser.add_argument("--fast", nargs="*", type=PerformanceFeature, help="Enable some untested and potentially quality deteriorating optimizations. This is used to test new features so using it might crash your comfyui. --fast with no arguments enables everything. You can pass a list specific optimizations if you only want to enable specific ones. Current valid optimizations: {}".format(" ".join(map(lambda c: c.value, PerformanceFeature)))) parser.add_argument("--fast", nargs="*", type=PerformanceFeature, help="Enable some untested and potentially quality deteriorating optimizations. This is used to test new features so using it might crash your comfyui. --fast with no arguments enables everything. You can pass a list specific optimizations if you only want to enable specific ones. Current valid optimizations: {}".format(" ".join(map(lambda c: c.value, PerformanceFeature))))
parser.add_argument("--disable-pinned-memory", action="store_true", help="Disable pinned memory use.")
parser.add_argument("--mmap-torch-files", action="store_true", help="Use mmap when loading ckpt/pt files.") parser.add_argument("--mmap-torch-files", action="store_true", help="Use mmap when loading ckpt/pt files.")
parser.add_argument("--disable-mmap", action="store_true", help="Don't use mmap when loading safetensors.") parser.add_argument("--disable-mmap", action="store_true", help="Don't use mmap when loading safetensors.")

14
comfy/model_management.py
View File

@ -1085,22 +1085,21 @@ def cast_to_device(tensor, device, dtype, copy=False):
PINNED_MEMORY = {} PINNED_MEMORY = {}
TOTAL_PINNED_MEMORY = 0 TOTAL_PINNED_MEMORY = 0
if PerformanceFeature.PinnedMem in args.fast: MAX_PINNED_MEMORY = -1
if not args.disable_pinned_memory:
if is_nvidia():
if WINDOWS: if WINDOWS:
MAX_PINNED_MEMORY = get_total_memory(torch.device("cpu")) * 0.45 # Windows limit is apparently 50% MAX_PINNED_MEMORY = get_total_memory(torch.device("cpu")) * 0.45 # Windows limit is apparently 50%
else: else:
MAX_PINNED_MEMORY = get_total_memory(torch.device("cpu")) * 0.95 MAX_PINNED_MEMORY = get_total_memory(torch.device("cpu")) * 0.95
else: logging.info("Enabled pinned memory {}".format(MAX_PINNED_MEMORY // (1024 * 1024)))
MAX_PINNED_MEMORY = -1
def pin_memory(tensor): def pin_memory(tensor):
global TOTAL_PINNED_MEMORY global TOTAL_PINNED_MEMORY
if MAX_PINNED_MEMORY <= 0: if MAX_PINNED_MEMORY <= 0:
return False return False
if not is_nvidia():
return False
if not is_device_cpu(tensor.device): if not is_device_cpu(tensor.device):
return False return False
@ -1121,9 +1120,6 @@ def unpin_memory(tensor):
if MAX_PINNED_MEMORY <= 0: if MAX_PINNED_MEMORY <= 0:
return False return False
if not is_nvidia():
return False
if not is_device_cpu(tensor.device): if not is_device_cpu(tensor.device):
return False return False