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In his keynote address to ITF World Cup 2023 semiconductor conference, Jensen Huang, founder and CEO of Nvidia, highlighted the profound impact of accelerated computing and artificial intelligence (AI) on the chip manufacturing industry. In his video presentation, Huang gave a comprehensive overview of the latest information technology advances industries around the world.
Huang highlighted the potential of Nvidia’s accelerated computing and AI solutions in chip manufacturing. He pointed out their intersection with semiconductor manufacturing. He also stressed the need for a new approach to meet growing demand for computing power while addressing concerns about net-zero goals.
“We are experiencing two simultaneous platform transitions: accelerated computing and generative AI,” said Huang. “I am excited to see Nvidia accelerating compute and AI to serve the global chip manufacturing industry.”
As an example of how artificial intelligence and accelerated computing are transforming the technology sector, Huang explained that to achieve advanced chip manufacturing, more than 1,000 precise steps need to be performed to create biomolecule-sized features, with each step performed perfectly to ensure a functional output.
“Sophisticated computational sciences are performed at each stage to calculate the features to be modeled and to perform defect detection for online process control,” said Huang. “Chip manufacturing is an ideal application for Nvidia’s acceleration and AI.”
Furthermore, Huang acknowledged that while the exponential growth in central processing unit (CPU) performance has mainly driven the technology industry for nearly four decades, CPU design has reached a state of maturity, resulting in a slowdown in the speed at which semiconductors increase their power and efficiency.
Leverage accelerated computing to streamline technology development
Huang noted Nvidia’s pioneering efforts in accelerated computing, a revolutionary approach that combines the parallel processing capabilities of graphics processing units (GPUs) with CPUs. Nvidia, he said, is well suited to meet the challenges of today’s computational science, 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 use Nvidia GPUs to accelerate pattern rendering and masking process correction in the creation of photomasks, stencils used to transfer patterns onto wafers using electron beams.
“We’ve already accelerated processing 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 tools and algorithms optimized for GPU-accelerated, computational lithography.
The future of artificial intelligence and digital innovations
Huang emphasized the far-reaching influence of artificial intelligence and accelerated computing, extending beyond chip manufacturing to permeate the entire technology sector. He acknowledged that the simultaneous changes in accelerated computing and generative AI are shaping the future of the technology landscape.
Looking to the future, Huang called the next wave of artificial intelligence “embedded AI”, intelligent systems that can understand, reason and interact with the physical world. He cited robotics, autonomous vehicles and chatbots with greater understanding of the physical world as examples of this technology.
To demonstrate advances in embodied AI, Huang unveiled Nvidia VIMA, a multimodal embodied AI system capable of performing complex tasks guided by visual text prompts. Through capturing concepts, understanding boundaries, and even emulating physics, VIMA represents a remarkable progression in AI capabilities.
Huang also revealed Nvidia’s Earth-2 project, designed to develop a digital replica of the planet. Earth-2 will predict weather patterns, provide long-term climate forecasts and ultimately contribute to the search for environmentally friendly and cost-effective energy solutions.
This effort uses FourCastNet, an AI-physics model that rapidly simulates global weather patterns. These systems have great potential to address the pressing problems of our age, including the demand for sustainable energy solutions.
“The reactor plasma’s physical AI runs on Nvidia AI and its digital twin runs on Nvidia Omniverse,” said Huang. “Such systems hold promise for further advances in the semiconductor industry. I look forward to digital twins powered by AI, robotics and Omniverse to help advance the future of chip manufacturing.
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