Google has this week unveiled its new A3 supercomputers which the company has purposely built specifically for artificial intelligence (AI) applications and machine learning (ML) models both of which require huge amounts of computation. Google Compute Engine A3 supercomputers are built to train and serve the most demanding AI models that power today’s generative AI and large language model innovation says Google. The A3 supercomputer’s scale provides up to 26 exaFlops of AI performance, which considerably improves the time and costs for training large ML models.
AI supercomputers
The new A3 supercomputers are equipped with NVIDIA H100 Tensor Core GPUs and feature Google’s “leading networking advancements” to serve customers of all sizes. “A3 is the first GPU instance to use our custom-designed 200 Gbps IPUs, with GPU-to-GPU data transfers bypassing the CPU host and flowing over separate interfaces from other VM networks and data traffic. This enables up to 10x more network bandwidth compared to our A2 VMs, with low tail latencies and high bandwidth stability.”
“Together with our partners, we offer a wide range of compute options for ML use cases such as large language models (LLMs), generative AI, and diffusion models. Recently, we announced G2 VMs, becoming the first cloud to offer the new NVIDIA L4 Tensor Core GPUs for serving generative AI workloads. Today, we’re expanding that portfolio with the private preview launch of the next-generation A3 GPU supercomputer. Google Cloud now offers a complete range of GPU options for training and inference of ML models.”
NVIDIA L4 Tensor Core GPUs
A3 GPU VMs were purpose-built to deliver the highest-performance training for today’s ML workloads, complete with modern CPU, improved host memory, next-generation NVIDIA GPUs and major network upgrades. Here are the key features of the A3:
- 8 H100 GPUs utilizing NVIDIA’s Hopper architecture, delivering 3x compute throughput
- 3.6 TB/s bisectional bandwidth between A3’s 8 GPUs via NVIDIA NVSwitch and NVLink 4.0
- Next-generation 4th Gen Intel Xeon Scalable processors
- 2 TB of host memory via 4800 MHz DDR5 DIMMs
- 10x greater networking bandwidth powered by our hardware-enabled IPUs, specialized inter-server GPU communication stack and NCCL optimizations
Machine learning
“A3 GPU VMs are a step forward for customers developing the most advanced ML models. By considerably speeding up the training and inference of ML models, A3 VMs enable businesses to train more complex ML models at a fast speed, creating an opportunity for our customer to build large language models (LLMs), generative AI, and diffusion models to help optimize operations and stay ahead of the competition.”
“Google Cloud’s A3 VMs, powered by next-generation NVIDIA H100 GPUs, will accelerate training and serving of generative AI applications,” said Ian Buck, vice president of hyperscale and high performance computing at NVIDIA. “On the heels of Google Cloud’s recently launched G2 instances, we’re proud to continue our work with Google Cloud to help transform enterprises around the world with purpose-built AI infrastructure.
Artificial intelligence supercomputer
For customers looking to develop complex ML models without the maintenance, you can deploy A3 VMs on Vertex AI, an end-to-end platform for building ML models on fully-managed infrastructure that’s purpose-built for low-latency serving and high-performance training. Today, at Google I/O 2023, we’re pleased to build on these offerings by both opening generative AI support in Vertex AI to more customers, and by introducing new features and foundation models.”
For more information on the latest supercomputers built by Google for artificial intelligence (AI) and machine learning (ML) applications jump over to the official Google blog by following the link below.
Source : Google
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