Date: Wednesday, May 18 (Main Conference Day 2)
Start Time: 4:50 pm
End Time: 5:20 pm
As edge and embedded vision applications increasingly incorporate neural networks, developers are looking to add neural network accelerator functionality to their systems. There is just one problem: we need more than just neural networks in real application pipelines. For most real-world applications, robust algorithm pipelines combine classical image processing and computer vision algorithms for pre-processing (for example, image resizing) and post-processing (such as non-maximal suppression) along with DNNs. These classical algorithms cannot leverage neural network accelerators, and can quickly become performance bottlenecks. In this talk, we introduce the quadric q16 processor, which was designed from the ground up to accelerate a wide variety of image, vision and machine learning algorithms. We’ll highlight the distinctive features of the q16, the architecture behind it, and the associated software development tools. Bringing these all together, we will explore use cases illustrating how they solve performance bottlenecks that neural network accelerators do not address.