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Home » News » What is NVIDIA Hopper-based Gen AI with the Power of TensorRT-LLM?

What is NVIDIA Hopper-based Gen AI with the Power of TensorRT-LLM?

In the realm of generative AI, NVIDIA's Hopper architecture, powered by TensorRT-LLM software, with nearly 3x performance gains in MLPerf. H200 and GH200 GPUs redefine AI processing, setting new standards in efficiency and speed.

Ayush-Patel by Ayush Patel
Thursday, 28 March 2024, 2:23 AM
in News
NVIDIA TensorRT LLM

NVIDIA TensorRT LLM

In the realm of generative AI, where breakthroughs are measured in performance and efficiency, NVIDIA’s Hopper architecture has emerged as the indisputable champion in industry-standard tests, showcasing the unrivaled capabilities of TensorRT-LLM software. 

The latest MLPerf benchmarks attest to the remarkable performance enhancement, with NVIDIA Hopper-based systems achieving nearly three times the speed of their previous results, just within six months. Read here for the official release

At the heart of this revolutionary advancement lies TensorRT-LLM, a software solution designed to streamline the intricate process of inference on large language models (LLMs). 

This achievement underscores NVIDIA’s commitment to delivering a comprehensive platform encompassing cutting-edge chips, systems, and software tailored to meet the formidable demands of generative AI.

Also Read: What is NVIDIA Omniverse Cloud APIs for Transforming Industrial Innovations?

At the heart of this breakthrough are the H200 Tensor Core GPUs, equipped with memory-enhanced capabilities that redefine the boundaries of AI processing. 

These GPUs, featuring 141GB of HBM3e memory operating at an astounding 4.8 TB/s, have propelled inference speeds to unprecedented levels, reaching up to 31,000 tokens per second on the monumental Llama 2 benchmark.

But NVIDIA’s relentless pursuit of innovation doesn’t stop there. The GH200 Superchips raise the bar even further, packing up to 624GB of fast memory and incorporating a power-efficient NVIDIA Grace CPU. 

With nearly 5 TB/s of memory bandwidth, these Superchips deliver exceptional performance across a range of memory-intensive AI tasks, including recommender systems.

Also Read: How NVIDIA Blackwell and Automotive Innovations Power the New Era Computing

Moreover, NVIDIA’s commitment to openness and transparency is evident in its participation in the MLPerf benchmarks, where it consistently sweeps every test, reaffirming its position as the trusted source for AI solutions. 

Through a combination of advanced techniques such as structured sparsity, pruning, and DeepCache optimization, NVIDIA continues to redefine the possibilities of inference, paving the way for more cost-effective and efficient AI deployments worldwide.

As the demands of generative AI continue to evolve, NVIDIA remains at the forefront of innovation, poised to deliver the next big breakthrough with the upcoming Blackwell architecture GPUs. With Hopper GPUs and TensorRT-LLM leading the charge, the future of AI inference has never looked more promising.

Also Read: How Siemens and NVIDIA Partnership Will Bring Immersive AI Visualization in Manufacturing

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Ayush-Patel

Ayush Patel

Ayush Patel is a distinguished author and political graduate, renowned for his insightful writings on new-age technology. With a profound understanding of artificial intelligence, machine learning, and the ever-evolving landscape of technological advancements, Ayush has carved a niche for himself in the world of tech journalism. His articles, known for their depth and clarity, aim to inform and report on the latest happenings in the field, making complex topics accessible to a wide audience.

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