The Real-World Impact Of Silicon Lifecycle Management On Chip Architectures


Silicon lifecycle management (SLM) is transforming chip architectures, empowering designers to build smarter, more resilient, and secure semiconductor devices by leveraging data from manufacturing to end of life in the field. That data can be used to improve future designs, reduce margin, and continuously optimize performance and power efficiency throughout a chip's lifetime. Moreover, under... » read more

A Golden Source As The Single Source Of Truth In HSI


The hardware/software interface (HSI) is where system-on-chip (SoC) software defines the connections between the software and the underlying hardware. Maintaining a precise, synchronized HSI across all artifacts is challenging, and unmanaged deviations can propagate through the flow and affect integration schedules. Most complex SoCs rely on IP reuse, each with its own naming conventions, ha... » read more

Chip Industry Week in Review


Samsung reportedly is hiking memory chip prices by 30% to 60% due to high demand from AI data centers and constrained supplies. Those shortages are causing ripples elsewhere. SMIC, China's largest foundry, said its customers are holding back orders for other types of semiconductor due to concerns about memory supplies. Meanwhile, interest in photonics and power semiconductors is picking up, ... » read more

Chip Industry Week in Review


SK hynix is ramping HBM manufacturing capacity to meet explosive demand for AI data centers. The company will launch 16-stack HBM4 next year, and up to 12-stack HBM4E. HBM5 and HBM5E will be introduced between 2029 and 2031, reports Business Korea. China will not have access to NVIDIA’s most advanced chips, President Trump told 60 Minutes. The Dutch economy minister said Nexperia's chip... » read more

Small Vs. Large Language Models


The proliferation of edge AI will require fundamental changes in language models and chip architectures to make inferencing and learning outside of AI data centers a viable option. The initial goal for small language models (SLMs) — roughly 10 billion parameters or less, compared to more than a trillion parameters in the biggest LLMs — was to leverage them exclusively for inferencing. In... » read more

Thermal, Mechanical, And Material Stresses Grow With Die Stacking


Managing thermal and mechanical stress in multi-die assemblies will require a detailed knowledge of how and where a device will be used, how it will be packaged, and where stresses could cause problems at any point during its expected lifetime. This includes everything from workload-dependent thermal gradients to mechanical and electrical stress, which may become more pronounced over time wi... » read more

Efficiency Defines The Future Of Data Movement


For decades, chip performance was measured by how much raw compute could be packed onto a die. However, that equation has changed. Moving data across a system-on-chip (SoC) now consumes more energy than the computations it performs. Efficient data movement has become a significant challenge for next-generation SoC designs. AI workloads are multiplying, hyperscale data centers are approaching po... » read more

Even With AI Inroads, Human Chip Designers Still Essential


The proliferation of AI tools seems perfectly matched to fill a talent shortage, but a closer look shows the skills do not entirely overlap. Certain parts of the EDA pipeline require human engineers, and it seems likely to stay that way for the foreseeable future. The dark art of analog design, the final word on safety-critical functional safety, high-level architectural decisions, product i... » read more

Chip Industry Week in Review


Retaliations and countermoves leading up to planned trade talks between the U.S. and China led experts to wonder, 'Who's winning?' New activity on this front: China issued questionnaires to some U.S. semiconductor firms as part of an anti-dumping probe, demanding detailed data on sales, profit margins, logistics costs and Chinese customer names for analog chips. The probe appears aimed at ... » read more

Multiple Challenges Emerge With Physical AI System Design


Physical AI holds the promise of making everything from robots to a slew of mobile edge devices much more interactive and useful, but it will significantly alter how systems are designed, verified, and monitored. Physical AI systems need to work both independently and together. They need the ability to make decisions quickly and locally, typically using much less power than other types of AI... » read more

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