mlcommons / mlcommons/inference
[v4.1 inference] Detected system did not match any known systems.
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Description
Hi,
I'm facing some issues when i tried running the benchmark for 3d-unet.
When i ran
make run RUN_ARGS="--benchmarks=3d-unet --scenarios=offline,server""
Got the errors, which is also the system i'm working on
Detected system did not match any known systems. Exiting. SystemConfiguration(host_cpu_conf=CPUConfiguration(layout={CPU(name='AMD EPYC 9554 64-Core Processor', architecture=<CPUArchitecture.x86_64: AliasedName(name='x86_64', aliases=(), patterns=())>, core_count=56, threads_per_core=2): 2}), host_mem_conf=MemoryConfiguration(host_memory_capacity=Memory(quantity=1.5849542239999999, byte_suffix=<ByteSuffix.TB: (1000, 4)>, _num_bytes=1584954224000), comparison_tolerance=0.05), accelerator_conf=AcceleratorConfiguration(layout=defaultdict(<class 'int'>, {GPU(name='NVIDIA H100 PCIe', accelerator_type=<AcceleratorType.Discrete: AliasedName(name='Discrete', aliases=(), patterns=())>, vram=Memory(quantity=79.6474609375, byte_suffix=<ByteSuffix.GiB: (1024, 3)>, _num_bytes=85520809984), max_power_limit=350.0, pci_id='0x233110DE', compute_sm=90): 8})), numa_conf=NUMAConfiguration(numa_nodes={}, num_numa_nodes=16), system_id=None)
Driver Version: 550.90.07 CUDA Version: 12.4
I didn't manually add any system configuration under /work/code/common/system since i didn't saw 4.1 inference result submitter who submit on H100 Pcie 80GB customized that.
any suggestion could help me to pass the error?
thanks a lot!
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the reported make run command for the 3d-unet offline and server scenarios, then inspect the system configuration under /work/code/common/system. Compare the detected CPU, H100 PCIe GPU, memory, NUMA, driver, and CUDA details with the repository's known configurations; done means the benchmark recognizes this system without the reported error.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning, performance
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100