High-Efficiency Edge Vision Processing Based on Dynamically Reconfigurable TPU Technology

To achieve high accuracy, edge computer vision requires teraops of processing to be executed in fractions of a second. Additionally, edge systems are constrained in terms of power and cost. This talk will present and demonstrate the novel dynamic TPU array architecture of Flex Logix’s InferX X1 accelerators and contrast it to current GPU, TPU and other approaches to delivering the teraops computing required by edge vision inferencing. We will compare latency, throughput, memory utilization, power dissipation and overall solution cost. We’ll also show how existing trained models can be easily ported to run on the InferX X1 accelerator.