Semiconductor Engineering: SoC Integration And Data Transport Architecture Requirements Surge In 2023
, 2023年11月30日
Trends shaping chip design and what might be ahead in the next year.
As the holiday season is in full swing, it’s retrospection and prediction time! Let’s look at what I thought 2023 would look like, review how it turned out, and take a first stab at 2024 predictions. As a spoiler, my biggest surprise was the intensity with which artificial intelligence and machine learning (AI/ML) accelerated since Generative AI was put on the mainstream adoption map last year, making 2023 a pivotal year for AI/ML and generating even more advanced requirements for optimized on-chip and chip-to-chip/die-to-day transport architectures.
Looking back – What I thought 2023 would be …
When preparing predictions for 2023 last year, I suggested we would witness a significant shift in computing, emphasizing high-performance, power-efficient technologies, evident across data centers, networks, and devices, driving advancements in semiconductor materials, designs, and manufacturing. Specifically, we would see the emergence of complex, integrated device architectures for the high-end computing realm, blending various components into systems of chiplets and systems on chips. The rise of AI and machine learning technologies would spur even more specialized, workload-optimized semiconductor devices. In automotive design, 2023 would bring innovations in electrification, autonomy, and personalization, with sustainability playing a crucial role. Specifically, networks-on-chips would face heightened scrutiny to meet low-power demands, putting additional pressure on optimizing the power contribution of network-on-chips (NoCs) by reducing elements like wires, registers, and base components such as switches.
To read the full article on Semiconductor Engineering, click here.