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Copy file name to clipboardExpand all lines: content/patterns/medical-diagnosis-amx/_index.adoc
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@@ -3,15 +3,16 @@ title: Intel AMX accelerated Medical Diagnosis
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date: 2023-10-10
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validated: false
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summary: This pattern is based on a demo implementation of an automated data pipeline for chest X-ray analysis previously developed by Red Hat. The pattern is modified to utilize Intel AMX feature.
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products:
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rh_products:
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- Red Hat OpenShift Container Platform
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- Red Hat OpenShift Serverless
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- Red Hat OpenShift Data Foundation
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- Red Hat OpenShift Node Feature Discovery
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- 4th Gen Intel Xeon Scalable processors with Intel Advanced Matrix Extensions (Intel AMX)
Copy file name to clipboardExpand all lines: content/patterns/multicloud-gitops-amx-rhoai/_index.adoc
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@@ -3,15 +3,16 @@ title: Intel AMX accelerated Multicloud GitOps with Openshift AI
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date: 2024-02-27
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validated: false
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summary: This is extension of Multicloud GitOps pattern with Red Hat Openshift AI component to show the value of using Intel AMX.
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products:
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rh_products:
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- Red Hat OpenShift Container Platform
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- Red Hat Advanced Cluster Management
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- Red Hat Openshift AI
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- OpenVINO Toolkit Operator
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- 5th Gen Intel Xeon Scalable processors with Intel Advanced Matrix Extensions (Intel AMX)
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partners:
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- Intel
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industries:
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- General
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aliases: /multicloud-gitops-amx-rhoai/
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variant_of: multicloud-gitops
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# uncomment once this exists
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# pattern_logo: multicloud-gitops.png
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pattern_logo: amx-intel-ai.png
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// RHODS pattern description
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The basic {mcg-pattern} has been extended to highlight the *{intel-5th-gen-xeon-processors}* capabilities, offering developers a streamlined pathway to accelerate their workloads through the integration of cutting-edge *{intel-amx}*, providing efficiency and performance optimization in AI workloads.
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The basic pattern has been extended with two components: Openshift AI and OpenVINO Toolkit Operator.
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The basic pattern has been extended with two components: Openshift AI and OpenVINO Toolkit Operator.
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* Openshift AI, serves as a robust AI/ML platform for the creation of AI-driven applications and provides a collaborative environment for data scientists and developers that helps to move easily from experiment to production. It offers Jupyter application with selection of notebook servers, equipped with pre-configured environments and necessary support and optimizations (such as CUDA, PyTorch, Tensorflow, HabanaAI, etc.).
summary: This is an extension of Multicloud GitOps pattern with additional application using Intel SGX.
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products:
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rh_products:
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- Red Hat OpenShift Container Platform
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- Red Hat Advanced Cluster Management
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- Red Hat Node Feature Discovery
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- Intel Device Plugins Operator
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- 5th Gen Intel Xeon Scalable processors with Intel Software Guard Extensions (Intel SGX)
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partners:
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- Intel
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industries:
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- General
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aliases: /multicloud-gitops-sgx-hello-world/
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variant_of: multicloud-gitops
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# uncomment once this exists
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# pattern_logo: multicloud-gitops.png
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pattern_logo: sgx-intel-ai.png
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Background::
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Organizations are aiming to develop, deploy, and operate applications on an open hybrid cloud in a stable, simple, and secure way. This hybrid strategy includes multi-cloud deployments where workloads might be running on multiple clusters and on multiple clouds, private or public.
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This strategy requires an infrastructure-as-code approach: GitOps. GitOps uses Git repositories as a single source of truth to deliver infrastructure-as-code. Submitted code checks the continuous integration (CI) process, while the continuous delivery (CD) process checks and applies requirements for things like security, infrastructure-as-code, or any other boundaries set for the application framework. All changes to code are tracked, making updates easy while also providing version control should a rollback be needed.
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Moreover, organizations are looking for solutions that are secure for AI, ML, data processing etc. It is the case especially for cloud computing, which uses heavily multi-tenancy and multiple processes runs on single bare-metal machine and they do not know who might be their neighbors and what are their intentions.
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Moreover, organizations are looking for solutions that are secure for AI, ML, data processing etc. It is the case especially for cloud computing, which uses heavily multi-tenancy and multiple processes runs on single bare-metal machine and they do not know who might be their neighbors and what are their intentions.
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Memory encryption technologies can protect well the data and separate application from other ones run on the same machine - it is possible using *{intel-5th-gen-xeon-processors}* with *Intel Software Guard Extensions*.
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[id="about-solution"]
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In the logs of `hello-world-sgx` pod, there is an information that "Gramine is starting" and it executes the application by printing "HelloWorld!".
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This pattern demonstrates basic capabilities of running docker applications inside SGX enclaves. Based on this pattern other applications can be secured with {intel-sgx} and Gramine Shielded Containers in a similar way as presented here.
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This pattern demonstrates basic capabilities of running docker applications inside SGX enclaves. Based on this pattern other applications can be secured with {intel-sgx} and Gramine Shielded Containers in a similar way as presented here.
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