Artificial intelligence technology has become quite a trend in recent years, and NVIDIA is at the forefront with its H100 AI chip. This chip is a common feature in specialized supercomputers used by major corporations worldwide. This unique product has elevated NVIDIA’s value, surpassing even Alphabet (Google’s parent company) and Amazon. But NVIDIA isn’t stopping there. Mr. Jensen Huang, the president of NVIDIA, introduced their latest AI chip, the Blackwell B200 GPU, and the Blackwell GB200 super AI chip, at the GPU Technology Conference 2024.
Source: NVIDIA
Key Features of the Nvidia B200 AI Chip
Performance:
The B200 chip is a powerhouse with 208 billion transistors, delivering up to 20 petaflops of FP4 processing power. It’s incredibly speedy and powerful.
For large language model (LLM) inference tasks, the B200 chip can make a real difference. The GB200 superchip, a combination of two B200 GPUs and a Grace CPU, can boost performance up to 30-fold.
Efficiency:
Nvidia’s B200 chip can cut costs and energy use by as much as 25 times compared to the previous H100 model, making it a more economical and energy-efficient choice.
Training big AI models is more energy-efficient with the B200—it needs fewer GPUs and uses less power, but still delivers standout results.
Architecture:
The B200 chip boasts a second-generation transformer engine that doubles the compute, bandwidth, and model size by using four bits for each neuron instead of eight, contributing to its stellar performance.
It also comes with a next-gen NVLink switch, enabling 576 GPUs to interact, offering high bandwidth and low latency for effective data handling.
Scalability:
Nvidia has crafted the B200 chip with large-scale deployments in mind. For instance, the GB200 NVL72 rack brings together 36 CPUs and 72 GPUs, delivering a total AI training performance of 720 petaflops or 1.4 exaflops of inference.
Source: NVIDIA
Nvidia consistently maintains its strong standing in the era of AI
To sum it up, the Nvidia B200 AI chip is a significant leap forward in AI computing power. It offers impressive performance, efficiency, and scalability for a wide range of AI applications.
Major cloud service providers like Amazon, Google, Microsoft, and Oracle plan to integrate these powerful chips into their services, highlighting their wide-ranging adoption potential.
