PYTORCH_CUDA_ALLOC_CONF 是PyTorch 中的一个环境变量,用于配置 CUDA 内存分配的行为。expandable_segments:true 是这个环境变量的一个选项,用于启用可扩展的内存段分配机制,这有助于减少内存碎片,降低内存峰值。 以下是设置 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:true 的步骤: 1.
PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True 以一个transformer用例(PyTorch显存可视化与Snapshot数据分析 1.2)来对比测试,开启expandable功能前后的显存块申请差异。示例运行后装载数据进行可视化,跳转到"allocator state hisotry" 页面可看到: expandable_segments:False ...
PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True 跟cudaMalloc直接分配Kernel可访问的内存地址不同,该机制操作的是虚拟内存空间(对应的物理内存地址不具备访问权限),可以通过驱动map更多的物理内存在已分配的block的后面,从而使得segments可向上扩展,一定程度上提高了cache match的效率,减少内存碎片。 6. 在适当时机清空...
PYTORCH_CUDA_ALLOC_CONF="expandable_segments:True" 这告诉PyTorch分配器分配可以在将来扩展的块。但是,如果大小变化太大,它仍然可能无法解决问题。 所以我们智能手动来进行优化,那就是是使数据形状一致。这样分配器就更容易找到合适的数据块进行重用。 比如最简单的将数据填充到相同的大小。或者可以通过运行具有最大输...
re-enable PYTORCH_CUDA_ALLOC_CONF expandable_segments f95f4c4 winglian added the ready to merge label Jul 17, 2024 View details winglian merged commit 8731b95 into main Jul 17, 2024 8 checks passed winglian deleted the re-enable-cuda-alloc-conf-optim branch July 17, 2024 19:38 Si...
5. 对于输入数据size频繁变化的场景,使用Expandable Segments PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True 跟cudaMalloc直接分配Kernel可访问的内存地址不同,该机制操作的是虚拟内存空间(对应的物理内存地址不具备访问权限),可以通过驱动map更多的物理内存在已分配的block的后面,从而使得segments可向上扩展,一定程度上...
"PYTORCH_CUDA_ALLOC_CONF" ]="expandable_segments:True,roundup_power2_divisions:16" Copy link Collaborator NanoCode012Dec 13, 2024 I'm just reading about this:roundup_power2_divisionsconfig. Is there a reason we're setting 16? I saw that the default was 512. ...
does not support them, if you need to enable them, please do not use transfer_to_npu. warnings.warn(msg, RuntimeWarning) [W compiler_depend.ts:623] Warning: expandable_segments currently defaults to false. You can enable this feature by `export PYTORCH_NPU_ALLOC_CONF = expandable...
export PYTORCH_CUDA_ALLOC_CONF="expandable_segments:True,max_split_size_mb:32" This results in the very strange error: RuntimeError: !block->expandable_segment_ INTERNAL ASSERT FAILED at "../c10/cuda/CUDACachingAllocator.cpp":2814, please report a bug to PyTorch. ...
# Owner(s): ["module: cuda"] # run time cuda tests, but with the allocator using expandable segments import pathlib import sys from test_cuda import ( # noqa: F401 TestBlockStateAbsorption, TestCuda, TestCudaMallocAsync, ) import torch from torch.testing._internal.c...