There has been tremendous demand to deploy AI models across new and diverse hardware architectures. Many of these architectures include a variety of processing nodes and specialized hardware accelerators. The challenge is to take trained AI models developed in various open-source software frameworks and execute them efficiently on these architecures. Software tools must evolve to provide features such as AI model import, graph analysis, quantization, optimization, and code generation. Creating AI-centric software development tools is a complex undertaking that requires expertise in AI network theory and construction, high-performance computing, compilers, and embedded systems. This talk will share some of our experiences developing Cadence’s NeuroWeave Software Development Kit (SDK). NeuroWeave is a collection of tools and software libraries for optimizing and compiling AI models in order to execute them efficiently on Tensilica DSPs and Neo accelerators.
![](https://kisacoresearch.com/sites/default/files/styles/panopoly_image_square/public/speakers/eric-stotzer-head-shot-2023.jpg?itok=oeAulmLC&c=5068df298875f4c66f8d55d4c516c171)
Eric Stotzer
Eric Stotzer is a Software Engineering Group Director at Cadence Design Systems, where he is responsible for the Neuroweave SDK and Xtensa Neural Network Compiler (XNNC). Eric worked for 30 years at Texas Instruments developing system software tools for DSPs and MCUs. Before coming to Cadence, he was at Mythic working on a neural network compiler for mixed-signal AI accelerators. He is a coauthor of the book Using OpenMP - The Next Step: Affinity, Accelerators, Tasking, and SIMD, (MIT Press 2017). Eric holds a PhD in Computer Science from the University of Houston.
Cadence
Website: https://www.cadence.com/en_US/home.html
Cadence’s goal is to empower engineers at semiconductor and systems companies to create innovative, intelligent, and highly differentiated electronic products that transform the way people live, work, and play. The company’s Intelligent System Design strategy helps customers develop differentiated products—from chips to boards to systems—in AI, IoT, mobile, 5G, consumer, cloud, data center, automotive, aerospace, and other market segments. Cadence offers specialized IP with industry-leading performance, power efficiency, and interconnects, as well as AI-specific verification and implementation solutions. The company also employs machine learning within its tools and solutions to enable the best power, performance, and area (PPA), quality of results (QoR), and time-to-market (TTM) benefits.