Plus, Google unveils Axion, its custom Arm-based chip for data centers, at Google Cloud Next 2024.
Alphabet’s Google Cloud unveiled a slew of new products and services at the Google Cloud Next 2024 conference in Las Vegas, among them a program to help startups and small businesses build generative AI applications and services.
The initiative brings together the Nvidia Inception program for startups and the Google for Startups Cloud Program – and expands the benefits to include cloud credits, go-to-market support, and technical expertise to help startups with their AI initiatives.
Inception is a global program that supports more than 18,000 startups, and Nvidia is looking to entice more by offering an accelerated path to using Google Cloud infrastructure with access to Google Cloud credits, offering up to $350,000 for firms focused on AI.
In return, Google for Startups Cloud Program members can join Nvidia Inception and gain access to technical expertise, Nvidia Deep Learning Institute course credits, Nvidia hardware and software, and more. Inception also offers a platform called Capital Connect, which gives startups exposure to venture capital firms interested in the space.
Google launches Axion custom Arm processor
Google also announced a new line of Arm processors for its cloud services offerings, called Axion, making it the latest tech giant to do its own custom Arm-based chips. Amazon Web Services has offered Graviton processors since 2018, and Microsoft launched its own Arm chip, called Cobalt 100, last fall.
This isn’t Google’s first foray into custom silicon. It has had the tensor processing units (TPU) for acceleration of its own workloads going back to 2015, and in 2018, it launched a video coding unit (VCU) for video transcoding. But this will be its first customer-facing custom silicon.
Axion is based on Arm’s Neoverse V2 design, a data-center-oriented chip built on the ARMv9 architecture. Arm doesn’t make chips; it makes designs, and then licensees take those design and do their own customizations by adding to the basic configuration they get from Arm. Some make smart phones (Apple, Qualcomm), and others make server chips (Ampere).
Google declined to comment on speeds, fees, and cores, but it did claim that Axion processors would deliver instances with up to 30% better performance than the fastest general-purpose Arm-based instances available in the cloud today, up to 50% better performance, and up to 60% better energy-efficiency than comparable current-generation x86-based instances.
Axion is built on Titanium, a system of Google’s own purpose-built custom silicon microcontrollers and tiered scale-out offloads. It offloads operations like networking and security, so Axion processors can focus on computation of the workload, much like the SuperNIC offloads networking traffic from the CPU.
Virtual machines based on Axion processors will be available in preview in the coming months, according to Google.
AI software services updated
In February, Google introduced Gemma, a suite of open models using the same research and technology used to create Google’s Gemini generative AI service. Now, teams from Google and Nvidia have worked together to accelerate the performance of Gemma with Nvidia’s TensorRT-LLM, an open-source library for optimizing LLM inference.
Google Cloud also has made it easier to deploy Nvidia’s NeMo framework for building custom generative AI applications across its platform via its GKE Kubernetes engine and Google Cloud HPC Toolkit. This enables developers to jumpstart the development of generative AI models, allowing for the rapid deployment of turnkey AI products.
