High Performance Storage for AI Applications
The recent explosion in AI for everything from large language models to recommender systems is pushing demand for increases in GPU performance in order to maximize the value and efficiency of GPU servers. A complete solution which includes the right combination of CPUs, GPUs, tiered storage and networking will ensure optimal performance to meet users’ specific application requirements.
One of the biggest challenges facing businesses looking to capitalize on the growth of AI, is finding a storage solution that won’t become the bottleneck in their high performance GPU cluster. High hroughput, low latency storage is vital to feed massive amounts of data to train models and perform complex simulations and analysis, reducing AI model training and inference times, as well as TCO.
Red Hat certified hardware is proven to incorporate Red Hat's best practices and provides customers tested interoperability, known life cycle management, and trusted support.
Compare | Product | Level | |
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Red Hat OpenStack Services on OpenShift 18.0 - 18.x Base OS: Red Hat Enterprise Linux 9.0 Architecture: x86_64 | Certified | ||
Red Hat OpenStack Platform 17.0 - 17.x Base OS: Red Hat Enterprise Linux 9.0 Architecture: x86_64 | Certified | ||
Red Hat Enterprise Linux 9.0 - 9.x Architecture: x86_64 | Certified | ||
Red Hat OpenShift Container Platform 4.13 - 4.x Base OS: Red Hat Enterprise Linux 9.0 Architecture: x86_64 | Certified |
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