Google Cloud adds more infrastructure support for AI workloads

It was in May 2023 that Google first launched the A3 series of supercomputer VMs in its cloud, aimed at rapidly training large AI models.

The new A3 Mega VM, which will be generally available next month, offers double the GPU-to-GPU networking bandwidth of the original A3, the company said, adding that it was planning to add Confidential Computing capabilities to the A3 VM family in preview later this year. The feature is intended to protect the privacy and integrity of data being used in AI workloads.

Storage optimization for AI and ML workloads

To improve performance on AI training, fine-tuning, and inference, Google Cloud has made enhancements to its storage products, including caching, which keeps the data closer to compute instances and enables a faster training cycle.

The enhancements are targeted at maximizing GPU and TPU utilization, leading to higher energy efficiency and cost optimization, the company said.

One of these enhancements is including caching in Parallelstore, a managed parallel file service that offers high performance. While this enhancement is still in preview, it can offer up to 3.9 times faster training times and up to 3.7 times higher training throughput compared to native ML framework data loaders, the company said.

Another enhancement is the introduction of a preview of Hyperdisk ML, a block storage service optimized for AI inferencing workloads.