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Describe the bug
I am training an LLM using DeepSpeed and 12 nodes a 8 V100s per node. My training is generally working well (thanks DeepSpeed), but when I run multiple training runs in parallel, I run into trouble.
I am getting these kinds of errors
Traceback (most recent call last):
File "/gpfs/u/scratch/ANFM/ANFMbchl/DeepSpeed/deepspeed/ops/transformer/inference/triton/matmul_ext.py", line 473, in matmul_ext_update_autotune_table
fp16_matmul._update_autotune_table()
fp16_matmul._update_autotune_table()
File "/gpfs/u/scratch/ANFM/ANFMbchl/DeepSpeed/deepspeed/ops/transformer/inference/triton/matmul_ext.py", line 450, in _update_autotune_table
File "/gpfs/u/scratch/ANFM/ANFMbchl/DeepSpeed/deepspeed/ops/transformer/inference/triton/matmul_ext.py", line 450, in _update_autotune_table
TritonMatmul._update_autotune_table(__class__.__name__ + "_2d_kernel", __class__._2d_kernel)
File "/gpfs/u/scratch/ANFM/ANFMbchl/DeepSpeed/deepspeed/ops/transformer/inference/triton/matmul_ext.py", line 179, in _update_autotune_table
TritonMatmul._update_autotune_table(__class__.__name__ + "_2d_kernel", __class__._2d_kernel)
File "/gpfs/u/scratch/ANFM/ANFMbchl/DeepSpeed/deepspeed/ops/transformer/inference/triton/matmul_ext.py", line 179, in _update_autotune_table
cache_manager.put(autotune_table)
File "/gpfs/u/scratch/ANFM/ANFMbchl/DeepSpeed/deepspeed/ops/transformer/inference/triton/matmul_ext.py", line 98, in put
cache_manager.put(autotune_table)
os.rename(self.file_path + ".tmp", self.file_path)
FileNotFoundError: [Errno 2] No such file or directory: '/gpfs/u/home/ANFM/ANFMbchl/scratch/1167439/.cache/Fp16Matmul_2d_kernel.pickle.tmp' -> '/gpfs/u/home/ANFM/ANFMbchl/scratch/1167439/.cache/Fp16Matmul_2d_kernel.pickle'
File "/gpfs/u/scratch/ANFM/ANFMbchl/DeepSpeed/deepspeed/ops/transformer/inference/triton/matmul_ext.py", line 98, in put
os.rename(self.file_path + ".tmp", self.file_path)
FileNotFoundError: [Errno 2] No such file or directory: '/gpfs/u/home/ANFM/ANFMbchl/scratch/.cache/Fp16Matmul_2d_kernel.pickle.tmp' -> '/gpfs/u/home/ANFM/ANFMbchl/scratch/.cache/Fp16Matmul_2d_kernel.pickle'
I thought that this is because maybe the directories are shared between the multiple runs, which can create race conditions.
My TMPDIR, TRITON_CACHE_DIR, and TORCH_EXTENSIONS_DIR are set as follows
but that also didn't work. Now I am getting this error
Traceback (most recent call last):
File "/gpfs/u/scratch/ANFM/ANFMbchl/DeepSpeed/deepspeed/ops/transformer/inference/triton/matmul_ext.py", line 473, in matmul_ext_update_autotune_table
fp16_matmul._update_autotune_table()
fp16_matmul._update_autotune_table()
File "/gpfs/u/scratch/ANFM/ANFMbchl/DeepSpeed/deepspeed/ops/transformer/inference/triton/matmul_ext.py", line 450, in _update_autotune_table
File "/gpfs/u/scratch/ANFM/ANFMbchl/DeepSpeed/deepspeed/ops/transformer/inference/triton/matmul_ext.py", line 450, in _update_autotune_table
TritonMatmul._update_autotune_table(__class__.__name__ + "_2d_kernel", __class__._2d_kernel)
File "/gpfs/u/scratch/ANFM/ANFMbchl/DeepSpeed/deepspeed/ops/transformer/inference/triton/matmul_ext.py", line 179, in _update_autotune_table
TritonMatmul._update_autotune_table(__class__.__name__ + "_2d_kernel", __class__._2d_kernel)
File "/gpfs/u/scratch/ANFM/ANFMbchl/DeepSpeed/deepspeed/ops/transformer/inference/triton/matmul_ext.py", line 179, in _update_autotune_table
cache_manager.put(autotune_table)
File "/gpfs/u/scratch/ANFM/ANFMbchl/DeepSpeed/deepspeed/ops/transformer/inference/triton/matmul_ext.py", line 98, in put
cache_manager.put(autotune_table)
os.rename(self.file_path + ".tmp", self.file_path)
FileNotFoundError: [Errno 2] No such file or directory: '/gpfs/u/home/ANFM/ANFMbchl/scratch/1167439/.cache/Fp16Matmul_2d_kernel.pickle.tmp' -> '/gpfs/u/home/ANFM/ANFMbchl/scratch/1167439/.cache/Fp16Matmul_2d_kernel.pickle'
File "/gpfs/u/scratch/ANFM/ANFMbchl/DeepSpeed/deepspeed/ops/transformer/inference/triton/matmul_ext.py", line 98, in put
os.rename(self.file_path + ".tmp", self.file_path)
FileNotFoundError: [Errno 2] No such file or directory: '/gpfs/u/home/ANFM/ANFMbchl/scratch/1167439/.cache/Fp16Matmul_2d_kernel.pickle.tmp' -> '/gpfs/u/home/ANFM/ANFMbchl/scratch/1167439/.cache/Fp16Matmul_2d_kernel.pickle'
ds_report output
[2024-06-12 03:08:15,154] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-06-12 03:08:15,765] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[WARNING] async_io requires the dev libaio .so object and headers but these were not found.
[WARNING] async_io: please install the libaio-devel package with yum
[WARNING] If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found.
[WARNING] Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH
No ROCm runtime is found, using ROCM_HOME='/opt/rocm-4.3.0'
[WARNING] NVIDIA Inference is only supported on Ampere and newer architectures
[WARNING] sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3
[WARNING] using untested triton version (2.3.0), only 1.0.0 is known to be compatible
--------------------------------------------------
DeepSpeed C++/CUDA extension op report
--------------------------------------------------
NOTE: Ops not installed will be just-in-time (JIT) compiled at
runtime if needed. Op compatibility means that your system
meet the required dependencies to JIT install the op.
--------------------------------------------------
JIT compiled ops requires ninja
ninja .................. [OKAY]
--------------------------------------------------
op name ................ installed .. compatible
--------------------------------------------------
[WARNING] async_io requires the dev libaio .so object and headers but these were not found.
[WARNING] async_io: please install the libaio-devel package with yum
[WARNING] If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found.
async_io ............... [NO] ....... [NO]
fused_adam ............. [NO] ....... [OKAY]
cpu_adam ............... [NO] ....... [OKAY]
cpu_adagrad ............ [NO] ....... [OKAY]
cpu_lion ............... [NO] ....... [OKAY]
[WARNING] Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH
evoformer_attn ......... [NO] ....... [NO]
[WARNING] NVIDIA Inference is only supported on Ampere and newer architectures
fp_quantizer ........... [NO] ....... [NO]
fused_lamb ............. [NO] ....... [OKAY]
fused_lion ............. [NO] ....... [OKAY]
inference_core_ops ..... [NO] ....... [OKAY]
cutlass_ops ............ [NO] ....... [OKAY]
transformer_inference .. [NO] ....... [OKAY]
quantizer .............. [NO] ....... [OKAY]
ragged_device_ops ...... [NO] ....... [OKAY]
ragged_ops ............. [NO] ....... [OKAY]
random_ltd ............. [NO] ....... [OKAY]
[WARNING] sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3
[WARNING] using untested triton version (2.3.0), only 1.0.0 is known to be compatible
sparse_attn ............ [NO] ....... [NO]
spatial_inference ...... [NO] ....... [OKAY]
transformer ............ [NO] ....... [OKAY]
stochastic_transformer . [NO] ....... [OKAY]
--------------------------------------------------
DeepSpeed general environment info:
torch install path ............... ['/gpfs/u/home/ANFM/ANFMbchl/scratch/miniconda3/envs/torch-nightly/lib/python3.10/site-packages/torch']
torch version .................... 2.3.0+cu121
deepspeed install path ........... ['/gpfs/u/scratch/ANFM/ANFMbchl/DeepSpeed/deepspeed']
deepspeed info ................... 0.14.3+488a823, 488a823, master
torch cuda version ............... 12.1
torch hip version ................ None
nvcc version ..................... 12.1
deepspeed wheel compiled w. ...... torch 2.4, cuda 12.1
shared memory (/dev/shm) size .... 377.69 GB
The text was updated successfully, but these errors were encountered:
Describe the bug
I am training an LLM using DeepSpeed and 12 nodes a 8 V100s per node. My training is generally working well (thanks DeepSpeed), but when I run multiple training runs in parallel, I run into trouble.
I am getting these kinds of errors
I thought that this is because maybe the directories are shared between the multiple runs, which can create race conditions.
My
TMPDIR
,TRITON_CACHE_DIR
, andTORCH_EXTENSIONS_DIR
are set as followsTo fix this, I tried to allocate one cache folder per run like so
but that also didn't work. Now I am getting this error
ds_report output
The text was updated successfully, but these errors were encountered: