February 28, 2024 By Marissa Treible
Kodie Glosser
Ethan Long
Elvin Galarza
2 min read

With NVIDIA L4 GPUs, industries are achieving 2.5x better performance compared to the previous generation of GPUs for generative AI use cases. Creators are able to optimize graphics performance 4x higher to generate cinematic-quality graphics, scenes for virtual worlds, and cloud gaming. Similarly with AR/VR, live stream use cases have enjoyed a 120x performance boost when compared to CPU-based solutions. As the need for GPUs grow, IBM continues to demonstrably commit to addressing climate change; NVIDIA L4 GPUs consume less energy and significantly lower carbon footprints.

IBM is proud to announce GX3, a suite of NVIDIA L4 Tensor Core GPU flavors, as the newest addition of GPU profiles available with IBM Cloud Kubernetes Service (IKS) and Red Hat OpenShift on IBM Cloud (ROKS) clusters that run on IBM Cloud VPC.

For more information on NVIDIA L4 GPUs and how you can use them to accelerate and optimize your workload performance, see NVIDIA L4 Tensor Core GPU.

Available GX3 (NVIDIA L4 GPU) flavors

The following NVIDIA L4 GPU flavors are available for IBM Cloud VPC clusters that run Kubernetes version 1.28+ or any version of Red Hat OpenShift.

  • gx3.16x80x1L4: 1 GPU, 16 cores, 80 GB memory, 100GB storage, 32 Gbps network speed
  • gx3.32x160x2L4: 2 GPU, 32 cores, 160 GB, memory, 100GB storage, 32 Gbps network speed
  • gx3.64x320x4L4: 4 GPU, 64 cores, 320 GB memory, 100GB storage, 32 Gbps network speed

Getting started with GX3 (NVIDIA L4 GPUs) on IBM Cloud Kubernetes Service

Enjoy a plug-and-play experience with IBM Cloud Kubernetes Service when provisioning a cluster. GPU drivers are automatically installed and you can get started right away by provisioning a new cluster at 1.28 or later with GX3 worker nodes. No additional configuration for setting up the GPU is required. If you already have a 1.28+ cluster, simply add a worker pool that uses the GX3 nodes to your existing cluster. For more information, see Deploying an app on a GPU machine for IBM Cloud Kubernetes Service.

Getting started with GX3 (NVIDIA L4 GPUs) on Red Hat OpenShift on IBM Cloud

With Red Hat OpenShift on IBM Cloud, installing the NVIDIA GPU Operator automates the management of all the necessary NVIDIA software components. Once complete, provision a new cluster or worker pool with the GX3 worker nodes. For more information, see Deploying an app on a GPU machine for Red Hat OpenShift on IBM Cloud.

Furthermore, leverage Red Hat OpenShift AI on GX3 worker nodes to rapidly develop, train, serve, and monitor machine learning models on-premise, in the public cloud, and at the edge. To learn more, see Installing Red Hat OpenShift AI.

Deploying Kubernetes-native apps in clusters Deploying an app on a GPU machine

More from

Merging top-down and bottom-up planning approaches

2 min read - This blog series discusses the complex tasks energy utility companies face as they shift to holistic grid asset management to manage through the energy transition. The first post of this series addressed the challenges of the energy transition with holistic grid asset management. The second post in this series addressed the integrated asset management platform and data exchange that unite business disciplines in different domains in one network. Breaking down traditional silos Many utility asset management organizations work in silos.…

Reflecting on IBM’s legacy of environmental innovation and leadership

4 min read - Upholding a legacy of more than 50 years of environmental responsibility through our company’s actions and commitments, IBM continues to be a leader in driving sustainability for our business, our communities and our clients—including a 34-year history of annual, public environmental reporting, which we continue today. As a hybrid cloud and artificial intelligence (AI) company, we believe that leveraging technology is key to unlocking impact, and it will play a substantial role in how society addresses, adapts to, and overcomes…

Fostering a more ethical future by leveraging technology 

3 min read - The introduction of generative AI (gen AI) has quickly raised new questions and challenges across the global marketplace. At IBM, our principles of trust and transparency serve as a foundation to help our clients address these challenges head-on, and through our work with policymakers, researchers, clients and other stakeholders, we continue to meet these challenges and develop technological and policy safeguards.  We are working hard to set an example of how to implement and maintain responsible technology, as we have…

IBM Newsletters

Get our newsletters and topic updates that deliver the latest thought leadership and insights on emerging trends.
Subscribe now More newsletters