The silicon interconnect fabric (Si-IF) as a platform for integration of high performance scaled
out systems including artificial intelligence systems is introduced in this article. The Si-IF is a …

Waferscale processor systems can provide the large number of cores, and memory
bandwidth required by today's highly parallel workloads. One approach to building …

Nowadays, artificial intelligence (AI) technology with large models plays an increasingly
important role in both academia and industry. It also brings a rapidly increasing demand for …

Key challenges of on‐chip integration, including limited scalability, high cost, difficulty to
maintain profitable yield, and increased thermal management complexity, suggest that …

Distributed Deep Neural Network (DNN) training is a technique to reduce the training
overhead by distributing the training tasks into multiple accelerators, according to a …

Silicon interconnect fabric (Si-IF) technology is a PCB replacement, fine pitch
heterogeneous integration platform that enables high package density by supporting dielet …

Silicon interconnect fabric (Si-IF) is a wafer-scale heterogeneous integration platform. This
platform promotes a paradigm shift in system integration and packaging methods, providing …

High-density placement of dies on the Silicon Interconnect Fabric (Si-IF) demands high
power delivery (1 W/mm 2) which in turn generates intense heat (~ 0.5-0.7 W/mm 2). To …

In recent years, with the rise of artificial intelligence and big data, there is an even greater
demand for scaling out computing and memory capacity. Silicon interconnect fabric (Si-IF), a …

Demand for large amounts of parallelism is growing rapidly for today's computing systems.
This is due to the proliferation of applications such as graph processing, data analytics …