Higher Density, More Data Create New Bottlenecks In AI Chips


Data movement is becoming a bigger problem at advanced nodes and in advanced packaging due to denser circuitry, more physical effects that can affect the integrity of signals or the devices themselves, and a significant increase in data from AI and machine learning. Just shrinking features in a design is no longer sufficient, given the scaling mismatch between SRAM-based L1 cache and digital... » read more

New AI Processors Architectures Balance Speed With Efficiency


Leading AI systems designs are migrating away from building the fastest AI processor possible, adopting a more balanced approach that involves highly specialized, heterogeneous compute elements, faster data movement, and significantly lower power. Part of this shift revolves around the adoption of chiplets in 2.5D/3.5D packages, which enable greater customization for different workloads and ... » read more

3.5D: The Great Compromise


The semiconductor industry is converging on 3.5D as the next best option in advanced packaging, a hybrid approach that includes stacking logic chiplets and bonding them separately to a substrate shared by other components. This assembly model satisfies the need for big increases in performance while sidestepping some of the thorniest issues in heterogeneous integration. It establishes a midd... » read more

Intel Vs. Samsung Vs. TSMC


The three leading-edge foundries — Intel, Samsung, and TSMC — have started filling in some key pieces in their roadmaps, adding aggressive delivery dates for future generations of chip technology and setting the stage for significant improvements in performance with faster delivery time for custom designs. Unlike in the past, when a single industry roadmap dictated how to get to the next... » read more