Leveraging Sparsity for Fast Response Times in Edge AI - tinyML Summit 2021

Explore a 23-minute conference talk from the tinyML Summit 2021 Partner Session on Edge Applications, focusing on leveraging sparsity for fast response times in edge computing. Delve into the concept of NeuronFlow, a novel multi-core processor architecture that exploits various forms of sparsity to create a scalable dataflow processing engine for AI applications at the edge. Learn about the significance of low latency in Edge AI applications, metrics for measuring latency, and their correlation to application performance. Discover how NeuronFlow's unique sparsity-exploitation characteristics enable real-time live AI applications where rapid response times are crucial. Gain insights into event-based self-time scheduling, single batch processing, resource allocation, and synchronization in the context of the Neural Flow Architecture. Examine the concept of sparsity through practical examples, comparing frames per second (FPS) to delta frames, and get an overview of the GrayOne chip. This presentation by Orlando Moreira, Fellow and Chief Architect at GrAI Matter Labs, offers valuable knowledge for professionals interested in cutting-edge AI technologies for edge computing.