Get the latest tech news
A practitioner's guide to testing and running GPU clusters
for training generative AI models Training generative AI models require clusters of expensive cutting-edge hardware: H100 GPUs & fast storage wired together in multi-network topologies involving Infiniband links, switches, transceivers and ethernet connections. While an increasing number of HPC and AI cloud services now offer these specialized clusters, they demand substantial capital commitments.
Training generative AI models require clusters of expensive cutting-edge hardware: H100 GPUs & fast storage wired together in multi-network topologies involving Infiniband links, switches, transceivers and ethernet connections. As a result, we've created a systematic approach to acceptance testing, designed to guarantee reliability for our end customers as we expand our globally distributed cloud service. By adopting a comprehensive and structured approach to testing, companies can navigate the complexities of the hardware lottery, ensuring that their infrastructure is stable and reliable, and that it can support the types of workloads they intend to run on the GPUs.
Or read this on Hacker News
