A new technical paper titled “Performance, efficiency, and cost analysis of wafer-scale AI accelerators vs. single-chip GPUs” was published by researchers at UC Riverside.
“This review compares wafer-scale AI accelerators and single-chip GPUs, examining performance, energy efficiency, and cost in high-performance AI applications. It highlights enabling technologies like TSMC’s chip-on-wafer-on-substrate (CoWoS), which enhances computational density up to 40×. Addressing challenges such as fault tolerance, software optimization, and cost efficiency, this review offers insights into trade-offs and synergies between architectures, inspiring innovation in scalable, energy-efficient hardware for next-generation AI,” the paper states.
Find the technical paper here. June 2025. The university’s news summary can be found here.
Ozkan et al., Performance, efficiency, and cost analysis of wafer-scale AI accelerators vs. single-chip GPUs, Device
(2025), https://doi.org/10.1016/j.device.2025.100834
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