Chip Industry Week in Review
EDA export controls; Synopsys-Ansys divest requirements; SIA Factbook; McKinsey effects of tariffs; ASE's fan-out bridge; earnings; TSMC's design center; China's legacy chips play; AMD's optical acquisition.
RISC-V’s Increasing Influence
Does the world need another CPU architecture when that no longer reflects the typical workload? Perhaps not, but it may need a bridge to get to where it needs to be.
Chip Industry Week in Review
IC, AI global ranking; China's fully automated IC design system; Micron goes bigger; PCIe 7.0 spec; TSMC-Tokyo joint lab; panel-level packaging win; first neuromorphic compute system; GAA forksheets; AMD's new GPUs.
Co-Packaged Optics Reaches Power Efficiency Tipping Point
But blazing fast data speeds come with significant manufacturing challenges.
Chip Industry Week in Review
Qualcomm to buy Alphawave; reworking chip grants; global semi, equipment sales up; GF's $16B expansion; Arm's AI-defined vehicles platform; Mexico's push; DRAM/DDR4; AI-powered RF design; MLPerf results; rare earths/magnets slow automakers; BEOL thermal resistance in BPD and chiplets.
RISC-V’s Increasing Influence
Does the world need another CPU architecture when that no longer reflects the typical workload? Perhaps not, but it may need a bridge to get to where it needs to be.
3D-IC For The Masses
Advanced assemblies have enabled an unprecedented rate of advancement in the data center, especially for neural processing, but can it expand beyond that?
Chiplets Add New Power Issues
Well-understood challenges become much more complicated when SoCs are disaggregated.
Development Flows For Chiplets
A chiplet economy requires standards, organization, and tools — and that's a problem.
Chiplet Tradeoffs And Limitations
Multi-die assemblies offer more flexibility, but figuring out the right amount of customization can have a big impact on power, performance, and cost.
New Data Center Protocols Tackle AI
UALink scales up, while Ultra Ethernet scales out.
Implementing AI Activation Functions
Why flexibility, area, and performance are traded off in AI inferencing designs.
Future-proofing AI Models
The rate of change in AI algorithms complicates the decision-making process about what to put in software, and how flexible the hardware needs to be.
