NVIDIA and Google have long been at the forefront of AI innovation, consistently working together to empower developers globally. This collaboration isn’t just about creating infrastructure; it’s about a deep, engineering-focused partnership aimed at optimizing the computing stack. This detailed article will provide insights into the latest developments from this partnership and what they mean for the future of AI.
Advancements from NVIDIA and Google Collaboration
The collaboration between NVIDIA and Google has led to significant advancements in community software development. Some noteworthy contributions include JAX, OpenXLA, MaxText, and llm-d. These software optimizations play a pivotal role in supporting Google’s advanced models, such as the Gemini models and the Gemma family of open models.
Moreover, NVIDIA has developed performance-optimized AI software that is seamlessly integrated across Google Cloud. This includes NVIDIA NeMo, NVIDIA TensorRT-LLM, NVIDIA Dynamo, and NVIDIA NIM microservices. These software solutions are incorporated into Google Cloud services like Vertex AI, Google Kubernetes Engine (GKE), and Cloud Run. Such integration enhances performance and simplifies AI deployment, making it more accessible for various applications.
NVIDIA Blackwell in Production on Google Cloud
Google Cloud has set a precedent by being the first cloud service provider to offer both NVIDIA HGX B200 and NVIDIA GB200 NVL72 with its A4 and A4X virtual machines (VMs). These VMs are part of Google Cloud’s AI Hypercomputer architecture, which can be accessed through managed services like Vertex AI and GKE. This architecture allows organizations to develop and deploy AI applications at scale effectively.
Google Cloud’s A4 VMs, accelerated by NVIDIA HGX B200, have become generally available. The A4X VMs offer impressive computing capabilities, delivering over one exaflop per rack. This performance is made possible by Google’s Jupiter network fabric and advanced networking with NVIDIA ConnectX-7 NICs. Additionally, Google’s third-generation liquid cooling infrastructure ensures sustained, efficient performance, even for the most demanding AI workloads.
On-Premises Deployment of Google Gemini with NVIDIA Blackwell
The Gemini models, known for their advanced reasoning abilities, are already enhancing cloud-based AI applications. However, sectors like public services, healthcare, and finance, which have stringent data residency and security requirements, have found it challenging to leverage this technology.
With the introduction of NVIDIA Blackwell platforms in Google Distributed Cloud, organizations can now deploy Gemini models securely in their own data centers. Google Distributed Cloud, a fully managed solution for on-premises and air-gapped environments, allows businesses to access advanced AI capabilities while ensuring data privacy and compliance. This development opens doors for these sectors to innovate using agentic AI by maintaining control over their data.
Optimizing AI Inference Performance for Gemini and Gemma Models
The Gemini family of models represents Google’s most advanced AI offerings, excelling in complex reasoning and multimodal understanding. NVIDIA and Google have collaborated to optimize performance for these models to ensure efficient execution of inference workloads on NVIDIA GPUs, specifically within Google Cloud’s Vertex AI platform. This collaboration allows a vast number of user queries for Gemini models to be handled efficiently across NVIDIA-accelerated infrastructure on Vertex AI and Google Distributed Cloud.
Additionally, the Gemma family of lightweight, open models has been optimized using the NVIDIA TensorRT-LLM library. These models are expected to be available as NVIDIA NIM microservices, which facilitate easy deployment. These optimizations are crucial for maximizing performance and making advanced AI more accessible to developers. Developers can now run their workloads across different deployment architectures, from large data centers to local NVIDIA RTX-powered PCs and workstations.
Building a Robust Developer Community and Ecosystem
Beyond technology, NVIDIA and Google Cloud are committed to supporting the developer community. They have optimized open-source frameworks like JAX for enhanced performance on Blackwell GPUs, allowing AI workloads to run efficiently across numerous nodes.
This collaboration extends to building a new joint developer community that combines the expertise of both Google Cloud and NVIDIA. This community aims to foster cross-skilling and innovation among developers, enabling them to build, scale, and deploy the next generation of AI applications more easily.
In conclusion, the partnership between NVIDIA and Google is a testament to how collaborative efforts can drive significant advancements in AI technology. Through engineering excellence, open-source leadership, and a vibrant developer ecosystem, these companies are paving the way for the future of AI applications. For more information, you can visit the NVIDIA website.
This article serves as a comprehensive overview of the ongoing innovations resulting from the partnership between NVIDIA and Google, highlighting the impact on the AI landscape and the exciting future possibilities for developers and industries worldwide.
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