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Running FlexFlow on Stanford's Marlowe, which is a DGX H100 machine. It completes the entire training run and hangs on Legion shutdown for rank 16.
Here's my srun: srun --output ${LOGS}/run_%t.log --ntasks-per-node=8 select_gpu_device.sh ./build-default/flexflow_python examples/python/native/mnist_mlp.py -ll:py 1 -ll:gpu 1 -ll:fsize 70000 -ll:zsize 10000 -lg:inorder -ll:force_kthreads
srun --output ${LOGS}/run_%t.log --ntasks-per-node=8 select_gpu_device.sh ./build-default/flexflow_python examples/python/native/mnist_mlp.py -ll:py 1 -ll:gpu 1 -ll:fsize 70000 -ll:zsize 10000 -lg:inorder -ll:force_kthreads
Attached backtrace and logs for 2 node * 8 procs/node: N2n16_flexflow.tgz
Let me know what else you need to debug this.
The text was updated successfully, but these errors were encountered:
Report the output of -level shutdown=2.
-level shutdown=2
Sorry, something went wrong.
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Running FlexFlow on Stanford's Marlowe, which is a DGX H100 machine. It completes the entire training run and hangs on Legion shutdown for rank 16.
Here's my srun:
srun --output ${LOGS}/run_%t.log --ntasks-per-node=8 select_gpu_device.sh ./build-default/flexflow_python examples/python/native/mnist_mlp.py -ll:py 1 -ll:gpu 1 -ll:fsize 70000 -ll:zsize 10000 -lg:inorder -ll:force_kthreads
Attached backtrace and logs for 2 node * 8 procs/node:
N2n16_flexflow.tgz
Let me know what else you need to debug this.
The text was updated successfully, but these errors were encountered: