Google Cloud and NVIDIA announced new AI infrastructure and software for customers to build and deploy massive models for generative AI and speed data science workloads.
In a fireside chat Tuesday at Google Cloud Next, Google Cloud CEO Thomas Kurian and NVIDIA founder and CEO Jensen Huang discussed how the partnership brings end-to-end machine learning services to some of the largest AI customers in the world — including by making it easy to run AI supercomputers with Google Cloud offerings built on NVIDIA technologies.
The new hardware and software integrations use the same NVIDIA technologies employed over the past two years by Google DeepMind and Google research teams.
“We’re at an inflection point where accelerated computing and generative AI have come together to speed innovation at an unprecedented pace,” Huang said. “Our expanded collaboration with Google Cloud will help developers accelerate their work with infrastructure, software and services that supercharge energy efficiency and reduce costs.”
Google’s framework for building massive large language models (LLMs), PaxML, is optimized for NVIDIA accelerated computing.
A GPU-optimized PaxML container is available in the NVIDIA NGC software catalog. In addition, PaxML runs on JAX, which is optimized for GPUs leveraging the OpenXLA compiler.
Google DeepMind and other Google researchers are among the first to use PaxML with NVIDIA GPUs for exploratory research.
The NVIDIA-optimized container for PaxML will be available immediately on the NVIDIA NGC container registry to researchers, startups and enterprises that are building the next generation of AI-powered applications.
Additionally, the companies announced Google’s integration of serverless Spark with NVIDIA GPUs through Google’s Dataproc service. This helps data scientists speed Apache Spark workloads to prepare data for AI development.
The integrations are the latest in NVIDIA and Google’s history of collaboration.
For more information, visit https://nvidianews.nvidia.com/.