This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...

The vast proliferation and adoption of AI over the past decade has started to drive a shift in AI compute demand from training to inference. There is an increased push to put to use the large number ...

For a neural network to run at its fastest, the underlying hardware must run efficiently on all layers. Through the inference of any CNN—whether it be based on an architecture such as YOLO, ResNet, or ...