Erwan Gallen
Erwan Gallen's contributions
Article
Running AI inference on Rebellions ATOM NPU with Red Hat AI
Erwan Gallen
+2
Learn how to deploy and serve large language models (LLM) on Rebellions ATOM NPUs using Red Hat OpenShift AI and a certified vLLM container image on the Red Hat AI Inference Server. This post walks through the steps to set up the joint solution between Red Hat and Rebellions, including installing the Node Feature Discovery operator, the Rebellions NPU operator, creating the ATOM hardware profile in OpenShift AI, and creating the vLLM RBLN ServingRuntime.
Article
Configure NVIDIA Blackwell GPUs for Red Hat AI workloads
Erwan Gallen
+4
Learn how to enable the NVIDIA RTX PRO 4500 Blackwell Server Edition on Red Hat AI for compact, power-efficient AI deployments. This hardware offers inference performance without adding unnecessary operational complexity for Red Hat AI users.
Article
Serve and benchmark Prithvi models with vLLM on OpenShift
Michele Gazzetti
+3
Learn how to deploy and test an Earth and space model inference service on Red Hat AI Inference Server and Red Hat OpenShift AI. This article includes two self-contained activities, one deploying Prithvi using a traditional Deployment object and another serving the model using KServe and observing Knative scaling.
Article
Run cost-effective AI workloads on OpenShift with AWS Neuron Operator
Erwan Gallen
+3
Learn how to optimize AI inference costs with AWS Inferentia and Trainium chips on Red Hat OpenShift using the AWS Neuron Operator.
Article
Accelerate model training on OpenShift AI with NVIDIA GPUDirect RDMA
Antonin Stefanutti
+2
Learn how NVIDIA GPUDirect RDMA over Ethernet enhances distributed model training performance and reduces communication bottlenecks in Red Hat OpenShift AI.
Article
Orchestrate offloaded network functions on DPUs with Red Hat OpenShift
Erwan Gallen
Explore the benefits of offloading OVN/OVS networking functions using NVIDIA BlueField-2 data processing units with Red Hat OpenShift.
Running AI inference on Rebellions ATOM NPU with Red Hat AI
Learn how to deploy and serve large language models (LLM) on Rebellions ATOM NPUs using Red Hat OpenShift AI and a certified vLLM container image on the Red Hat AI Inference Server. This post walks through the steps to set up the joint solution between Red Hat and Rebellions, including installing the Node Feature Discovery operator, the Rebellions NPU operator, creating the ATOM hardware profile in OpenShift AI, and creating the vLLM RBLN ServingRuntime.
Configure NVIDIA Blackwell GPUs for Red Hat AI workloads
Learn how to enable the NVIDIA RTX PRO 4500 Blackwell Server Edition on Red Hat AI for compact, power-efficient AI deployments. This hardware offers inference performance without adding unnecessary operational complexity for Red Hat AI users.
Serve and benchmark Prithvi models with vLLM on OpenShift
Learn how to deploy and test an Earth and space model inference service on Red Hat AI Inference Server and Red Hat OpenShift AI. This article includes two self-contained activities, one deploying Prithvi using a traditional Deployment object and another serving the model using KServe and observing Knative scaling.
Run cost-effective AI workloads on OpenShift with AWS Neuron Operator
Learn how to optimize AI inference costs with AWS Inferentia and Trainium chips on Red Hat OpenShift using the AWS Neuron Operator.
Accelerate model training on OpenShift AI with NVIDIA GPUDirect RDMA
Learn how NVIDIA GPUDirect RDMA over Ethernet enhances distributed model training performance and reduces communication bottlenecks in Red Hat OpenShift AI.
Orchestrate offloaded network functions on DPUs with Red Hat OpenShift
Explore the benefits of offloading OVN/OVS networking functions using NVIDIA BlueField-2 data processing units with Red Hat OpenShift.