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When looking at Inference/Edge/Open Division results, e.g.
https://mlperf.org/inference-results-0-7/
It seems unlikely that accuracy was maintained across the different line items (e.g. going fro…
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Have references to Python2 and python2.7 which runs into multiple issues.
Once I resolve that, I ran into famous issue of cannot find cublas_v2.h file although the file exists in 4 different loca…
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In the MLPerf Inference v2.1 round, Qualcomm and their partners submitted a number of RetinaNet results, which the Review Committee eventually accepted to the Open division under the Preview category.…
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For reproducibility we would request NVIDIA to switch the `BASE_IMAGE` repo links from internal Gitlab links to publicly available repo links. In the `Makefile.docker`, the `BASE_IMAGE` URL is from an…
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Hi there,
I have ran retinanet on **jetson Orin** and found the latency is greater than the official one.
My result is **118112979.00** ns which is 0.16 of the official results **19378310.00** ns.…
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Hi, the rules show that min duration is 600 for all workloads (I was looking at datacenter) while it shall be 60 for most of them.
https://github.com/mlcommons/inference_policies/blob/master/inferenc…
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Hello, I hope you are doing well.
I intend to run resnet50 in the server scenario (datacenter) using the script in the docs:
```
cm run script --tags=run-mlperf,inference,_r4.1-dev \
--mode…
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During the MLPerf Inference v1.0 round, I noticed that the power workflow when used with CPU inference _occasionally_ seemed to incur a rather high overhead (~10%), for example:
- Xavier with power m…
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Please see below for the detailed output. The run is done on Nvidia RTX 4090 GPU.
```
CMD: /home/arjun/cm/bin/python3 main.py --scenario SingleStream --profile stable-diffusion-xl-pytorch --datas…