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In his keynote address at the ITF World 2023 semiconductor conference, Jensen Huang, founder and CEO of Nvidia, emphasized the profound impact of accelerated computing and artificial intelligence (AI) in the chip manufacturing industry. In his video presentation, Huang provided a comprehensive overview of the latest computing advancements propelling industries worldwide.
Huang highlighted the potential of Nvidia’s accelerated computing and AI solutions in chipmaking. He emphasized their intersection with semiconductor manufacturing. He also stressed the need for a new approach to meet the rising demand for computing power while addressing concerns regarding net-zero goals.
“We are experiencing two simultaneous platform transitions — accelerated computing and generative AI,” Huang said. “I am thrilled to see Nvidia accelerated computing and AI in service of the world’s chipmaking industry.”
As an example of how AI and accelerated computing are transforming the technology industry, Huang explained that to achieve advanced chip manufacturing, over 1,000 precise steps must be executed to create features the size of a biomolecule, with each step executed perfectly to ensure functional output.
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“Sophisticated computational sciences are performed at every stage to compute the features to be patterned and to do defect detection for in-line process control,” Huang said. “Chip manufacturing is an ideal application for Nvidia accelerated and AI computing.”
Furthermore, Huang recognized that while the exponential performance growth of central processing units (CPUs) had primarily driven the technology industry for almost four decades, CPU design has reached a state of maturity, resulting in a slowdown in the rate at which semiconductors enhance their power and efficiency.
Leveraging accelerated computing to streamline tech development
Huang noted Nvidia’s pioneering efforts in accelerated computing, a groundbreaking approach that combines the parallel processing capabilities of graphics processing units (GPUs) with CPUs. Nvidia, he said, is well suited to tackle today’s computational science challenges, and his company’s accelerated computing is fueling the AI revolution.
He cited several examples of how Nvidia GPUs are increasingly crucial in chip manufacturing. Companies like D2S, IMS Nanofabrication and NuFlare are using Nvidia GPUs to accelerate pattern rendering and mask process correction in the creation of photomasks — stencils used to transfer patterns onto wafers using electron beams.
Meanwhile, semiconductor manufacturers KLA, Applied Materials and Hitachi High-Tech are incorporating Nvidia GPUs into their e-beam and optical wafer inspection and review systems.
“We have already accelerated the processing by 50 times,” Huang said. “Tens of thousands of CPU servers can be replaced by a few hundred Nvidia DGX systems, reducing power and cost by an order of magnitude.”
In March, Nvidia launched cuLitho, a software library that offers optimized tools and algorithms for computational lithography, accelerated by GPUs.
The future of AI and digital innovations
Huang stressed the far-reaching influence of AI and accelerated computing, extending beyond chip manufacturing to permeate the entire technology industry. He acknowledged that the concurrent shifts in accelerated computing and generative AI are shaping the future of the technological landscape.
Looking to the future, Huang referred to the next wave of AI as “embodied AI” — intelligent systems capable of understanding, reasoning and interacting with the physical world. He cited robotics, autonomous vehicles, and chatbots with heightened physical world comprehension as examples of this technology.
To demonstrate advancements in embodied AI, Huang unveiled Nvidia VIMA, a multimodal embodied AI system capable of carrying out intricate tasks guided by visual text prompts. Through acquiring concepts, comprehending boundaries and even emulating physics, VIMA signifies a notable progression in AI capabilities.
Huang also revealed Nvidia’s Earth-2 project, designed to develop a digital replica of the planet. Earth-2 will forecast weather patterns, provide long-range climate predictions and ultimately contribute to the search for affordable and environmentally friendly energy solutions.
This endeavor employs FourCastNet, a physics-AI model that rapidly simulates global weather patterns. These systems hold great potential for addressing pressing issues of our era, including the demand for sustainable energy solutions.
“The reactor plasma physics-AI runs on Nvidia AI, and its digital twin runs in Nvidia Omniverse,” Huang said. “Such systems hold promise for further advancements in the semiconductor industry. I look forward to physics-AI, robotics, and Omniverse-based digital twins helping to advance the future of chip manufacturing.”
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