Published On: July 5, 2025

4o AI Workloads Redefine Chip Architecture AI workloads are fundamentally different from traditional computing tasks. Where classic CPUs focused on serial instruction execution, AI models and intense neural networks demand massive parallelism and high data throughput. This has driven a shift toward specialized compute architectures, such as GPUs, tensor processors, and custom AI ASICs. These designs move away from pure von Neumann principles, emphasizing data locality and minimizing costly data movement. At the heart of this shift is the need to process billions of operations efficiently, for which the traditional architectures struggle to meet AI’s bandwidth and memory requirements, leading designers to adopt local SRAM buffers, near-memory compute, and advanced interconnects. However, these improvements come at the cost of larger die areas, power density challenges, and significant […]