NVIDIA Accelerates Inference on Meta Llama 3: A Breakthrough in AI Technology
NVIDIA, a global leader in semiconductor design, has made a significant stride in accelerating inference on Meta Llama 3, the latest large language model (LLM) generation. This optimization across all NVIDIA platforms is set to revolutionize the way developers, researchers, and businesses leverage AI technologies responsibly across various applications.
Trained on NVIDIA AI
Engineers at Meta trained the Llama 3 model on computer clusters powered by 24,576 NVIDIA H100 Tensor Core GPUs, interconnected with cutting-edge NVIDIA Quantum-2 InfiniBand networks. Meta plans to scale its infrastructure to a staggering 350,000 H100 GPUs in a bid to further push the boundaries of generative AI.
Putting Llama 3 to Work
Accelerated versions of Llama 3, tailored for NVIDIA GPUs, are now accessible for deployment in the cloud, data centers, edge computing, and PC environments. Developers can test drive Llama 3 at ai.nvidia.com through the NVIDIA NIM microservice, equipped with a versatile API for deployment across multiple platforms. Businesses can fine-tune Llama 3 using NVIDIA NeMo and optimize custom models for inference with NVIDIA TensorRT-LLM, deployable via the NVIDIA Triton Inference Server.
Taking Llama 3 to Devices and PCs
NVIDIA Jetson Orin is now capable of running Llama 3 for edge computing applications, facilitating the creation of interactive agents like those featured in the Jetson AI Lab. Additionally, Llama 3 is compatible with NVIDIA RTX and GeForce RTX GPUs, enhancing inference speed on workstations and PCs, hence providing developers with a vast user base of over 100 million NVIDIA-accelerated systems worldwide.
Get Optimal Performance with Llama 3
Deploying an LLM for chatbots demands a delicate balance of low latency, high reading speed, and optimal GPU utilization to minimize costs. Following best practices, a single NVIDIA H200 Tensor Core GPU can churn out 3,000 tokens/second, sufficient to serve around 300 users simultaneously. Leveraging an NVIDIA HGX server with eight H200 GPUs can deliver 24,000 tokens/second, thereby supporting over 2,400 users concurrently.
Advancing Community Models
NVIDIA, with its commitment to being an active open-source contributor, prioritizes optimizing community software to aid users in overcoming their most pressing challenges. Open-source models not only foster AI transparency but also empower users to share advancements in AI safety and resilience widely.
In conclusion, NVIDIA’s continued dedication to innovation and optimization in AI technology, exemplified by the accelerated inference on Meta Llama 3, paves the way for enhanced AI applications across various domains.
FAQ:
1. What is Meta Llama 3?
Meta Llama 3 is the latest generation of large language models (LLMs) developed by Meta. It is optimized for various applications and is now accelerated on NVIDIA platforms for enhanced performance.
2. How can developers access Llama 3?
Developers can access Llama 3 on ai.nvidia.com as a NVIDIA NIM microservice, providing a standard API for deployment in different environments like cloud, data centers, edge computing, and PCs.
3. How does NVIDIA optimize Llama 3 for inference?
NVIDIA utilizes technologies like NVIDIA TensorRT-LLM and Triton Inference Server to optimize custom models of Llama 3 for efficient inference on NVIDIA GPUs, ensuring optimal performance and cost-effectiveness.
