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Oct 19
Nvidia's custom HBM pulls Samsung onto TSMC's 3nm process, report says
Nvidia's custom memory design is shifting control of how high-bandwidth memory (HBM) is built from memory makers to its largest customer, and steering a key part of that work to TSMC. Samsung Electronics, which has made every part of its HBM stacks in-house, has agreed after an internal review to use TSMC's 3nm process for the base die of NVHBM, Nvidia's next-generation custom HBM, the Seoul Economic Daily reported on October 18, citing industry sources. The newspaper said it would be the first time the two companies have worked together at the HBM manufacturing stage.
Generative AI is pushing chip power consumption and heat flux to unprecedented levels, driving AI packaging thermal management requirements from several hundred watts to the kilowatt (kW) scale. Heat sink specialist Jentech Precision points out that package lids are evolving beyond conventional solid-state heat conduction toward phase-change heat spreading and microchannel liquid cooling, with TIM-less architectures representing the next horizon.
Taiwanese electronics makers are deepening their presence in Mexico's Chihuahua state, drawn by surging US demand for AI servers, officials and business leaders told a seminar in Taipei on October 19. The pace of foreign investment is driven by the state's access to the US market, even as Chihuahua seeks to transition from a manufacturing base into a research and design hub.
SK Hynix has presented the Memory-Centric AI Rack System (MARS) at the Open Compute Project (OCP) Global Summit. The architecture separates memory from individual servers and pools it at the rack level over Compute Express Link (CXL) fabrics. The company says this addresses the capacity and cost limits that are constraining the growth of large AI models.
The economics of the foundry business have always carried a particular contradiction: semiconductor manufacturing demands enormous upfront capital and years of sustained investment, yet the companies making those investments are expected to preserve enough strategic independence to respond quickly to technology cycles and customers.
The AI wave is triggering a surge in memory demand that extends from cloud data centers to edge applications. This surge has not only delivered a substantial dividend to relevant supply chains but is also driving a fundamental structural shift across the broader memory ecosystem.
The world's three largest memory manufacturers—Samsung Electronics, SK Hynix, and Micron Technology—along with Taiwan-based Nanya Technology, Winbond Electronics, and Macronix International, face significant obstacles in their transition to renewable energy.
Chenming Hu co-invented the FinFET transistor with colleagues at the University of California, Berkeley, in the 1990s and became TSMC's first chief technology officer in 2001. Decades earlier, as a graduate student, he was invited by Intel co-founder Andy Grove to join Intel, and turned him down.
ACM Research is expanding beyond China as its panel-level packaging equipment advances through customer evaluations in Taiwan, while the US semiconductor equipment maker invests in South Korea and Oregon. The company expects overseas operations to grow faster than its China revenue, although technology adoption, packaging-size standards, and US-China tensions could affect its plans.
The foundations of TSMC's modern-day success can be traced back to a public call from the US Defense Advanced Research Projects Agency (DARPA) for innovative designs that could break through the 25nm physical limit. Among those who answered it was Chenming (Calvin) Hu, then a professor at UC Berkeley, who would go on to become TSMC's first chief technology officer in 2001.
Once a global LCD manufacturing powerhouse, Taiwan's display industry has weathered financial crises, antitrust penalties and fierce competition from state-backed Chinese rivals. Now, after three decades of boom-and-bust cycles, its leading manufacturers are seeking a new future beyond screens, leveraging their expertise in precision manufacturing to enter automotive electronics, advanced semiconductor packaging and AI-related technologies.
IBM and Siemens will collaborate on research to develop IBM's nanostack transistor architecture, aiming to move its design toward manufacturing. The work could influence chip performance, energy efficiency, and artificial-intelligence computing worldwide, as the companies seek to address design, simulation, lithography, and production challenges beyond the 7-angstrom node.