Researchers in the Murmann Mixed Signal Group have developed a pipelined chip architecture with inverted residual and linear bottlenecks-based networks for energy efficient Machine Learning inference on edge devices.
Stanford researchers have developed new Fast Quick Error Detection (Fast QED) tests that are four orders of magnitude faster than standard QED tests while also preserving quick error detection properties.