Safe-NEureka: a Hybrid Modular Redundant DNN Accelerator for On-board Satellite AI Processing

TL;DR

Safe-NEureka is a hybrid DNN accelerator designed for satellite AI, combining redundancy and performance modes to ensure safety and efficiency in radiation-prone space environments.

Contribution

It introduces a modular redundant DNN accelerator with dual operation modes, enhancing fault tolerance and throughput for space-based AI processing.

Findings

96 reduction in faulty executions with redundancy mode

15% area overhead for fault protection features

Near-baseline speeds in performance mode for dense convolutions

Abstract

Low Earth Orbit (LEO) constellations are revolutionizing the space sector, with on-board Artificial Intelligence (AI) becoming pivotal for next-generation satellites. AI acceleration is essential for safety-critical functions such as autonomous Guidance, Navigation, and Control (GNC), where errors cannot be tolerated, and performance-critical processing of high-bandwidth sensor data, where occasional errors are tolerable. Consequently, AI accelerators for satellites must combine robust protection against radiation-induced faults with high throughput. This paper presents Safe-NEureka, a Hybrid Modular Redundant Deep Neural Network (DNN) accelerator for heterogeneous RISC-V systems. It operates in two modes: a redundancy mode utilizing Dual Modular Redundancy (DMR) with hardware-based recovery, and a performance mode repurposing redundant datapaths to maximize parallel throughput. Furthermore, its memory interface is protected by Error Correction Codes (ECCs), and the controller by Triple Modular Redundancy (TMR). Implementation in GlobalFoundries 12nm technology shows a 96 reduction in faulty executions in redundancy mode, with a manageable 15 area overhead. In performance mode, the architecture achieves near-baseline speeds on 3x3 dense convolutions with a 5 throughput and 11 efficiency reduction, compared to 48 and 53 in redundancy mode. This flexibility ensures high overheads are limited to critical tasks, establishing Safe-NEureka as a versatile solution for space applications.