Swapping Out Chiplets: I/Os Vs. Compute


Key Takeaways: Companies can save time and money by swapping out a compute, memory, or I/O chiplet to gain technology improvements, while keeping the other dies stable. Chip architects may choose to keep their I/Os stable and swap out compute to move from a 5nm process node to 3nm to achieve performance and power improvements, or swap out memory from LPDDR5X to LPDDR6. Swapping out... » read more

AI Starting To Simplify Design Of Programmable Logic


Key Takeaways AI/ML and agentic tools are getting better at helping design and compile FPGAs, but downstream programming is slower to benefit. FPGAs historically have been designed using Verilog or VHDL, but higher-level languages could push more intelligence into compilers. ML tools can also help with mixed-signal co-design by automatically tuning DSP algorithms based on analog simu... » read more

Annual Global IC Fabs And Facilities Report


Semiconductor companies announced a significant number of facilities in 2025 as global onshoring efforts continued across manufacturing, materials, packaging, design, and R&D. Investments came from both industry and government sources. Organizations worked together to solve current technology challenges, including soaring demand for AI chips and advanced memory, as well as complex applic... » read more

Programmable Chips Evolve For Shifting Needs


ICs and SoCs are utilizing a range of processing elements that allow them to optimize current workloads while hedging their bets for the future. What used to be a simple choice between an ASIC, FPGA, or DSP, has evolved into a mix of processor types and architectures, including varying levels of programmability and customization. Speed is essential, but technology is evolving so quickly that... » read more

FPGAs Find New Workloads In The High-Speed AI Era


FPGAs are finding new applications in the age of artificial intelligence, high-speed wireless communications, medical and life science technology, and in complex chip architectures where they can improve the flow of data. Field-programmable gate arrays (FPGAs) enable designers to reprogram or reconfigure digital logic after the chips have been deployed, which is essential in the AI world, wher... » read more

Chip Industry Week In Review


China's Hefei Lumiverse Technology reportedly has developed a desktop-sized High Harmonic Generation light source that generates wavelengths as small as 1nm. One customer already has used it to produce 14nm chips, which was the original target node for EUV, according to one report. As a point of comparison, TSMC and Samsung didn't start using EUV until the 7nm node, relying instead on immersion... » 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

Chip Industry Technical Paper Roundup: Oct. 7


New technical papers recently added to Semiconductor Engineering’s library: [table id=480 /] Find more semiconductor research papers here » read more

Double Duty Logic Block Architecture Enabling Concurrent LUT and Adder Chain Usage (Nanyang Technological Univ. et al)


A new technical paper titled "Double Duty: FPGA Architecture to Enable Concurrent LUT and Adder Chain Usage" was published by researchers at Nanyang Technological University, Cornell University, Altera, University of Waterloo and University of Toronto. Abstract "Flexibility and customization are key strengths of Field-Programmable Gate Arrays (FPGAs) when compared to other computing devices... » read more

Chip Industry Week in Review


Amkor, TSMC, and Cadence partnered with Tesoro VC, which will serve as the lead operator of a new Global AI + Semiconductor Startup Hub and a Global Design Center in Phoenix, Arizona, aimed at chip innovation, startup growth, and advanced manufacturing. Nvidia will invest $5 billion in Intel common stock at a purchase price of $23.28 per share and the companies will collaborate on AI infrastru... » read more

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