e2e_inference: update readme with known issue #187
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uMartinXu
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Dec 13, 2023
e2e/inference/README.md
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| @@ -2,6 +2,12 @@ | |||
| Intel AI inference end-to-end solution with RHOCP is based on the Intel® Data Center GPU Flex Series provisioning, Intel® OpenVINO™, and [Red Hat OpenShift Data Science](https://www.redhat.com/en/technologies/cloud-computing/openshift/openshift-data-science) (RHODS) on RHOCP. There are two AI inference modes verified with Intel® Xeon® processors and Intel Data Center GPU Flex Series with RHOCP-4.12. | |||
| * Interactive mode – RHODS provides OpenVINO based Jupyter Notebooks for users to interactively debug the inference applications or [optimize the models](https://docs.openvino.ai/2023.0/openvino_docs_MO_DG_Deep_Learning_Model_Optimizer_DevGuide.html) on RHOCP using data center GPU cards or Intel Xeon processors. | |||
| * Deployment mode – [OpenVINO Model Sever](https://github.com/openvinotoolkit/model_server) (OVMS) can be used to deploy the inference workloads in data center and edge computing environments on RHOCP. | |||
| * | |||
| **NOTE**: Known issue on OCP 4.13 | |||
| * To work around GPU workloads [issue](https://github.com/intel/intel-technology-enabling-for-openshift/issues/107), please run the below command on the GPU node : | |||
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Please change it to
Note: To make sure the AI inference workloads work properly, Please make sure follow the workaround section in the Known SeLinux regression issue
@vbedida79 please work with @mregmi and add the workaround section in the issue description. Thanks!
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updated PR and issue #107
mregmi
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Dec 13, 2023
Signed-off-by: vbedida79 <[email protected]>
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hershpa
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Dec 14, 2023
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LGTM! |
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update about #107
Signed-off-by: vbedida79 [email protected]