Paper

Abstract: Multi-core processors come with several cores integrated on a single die. They often work incessantly under high thermal stress, leading to severe wear-out. Server-class multicores already come with a mechanism to survive a core failure called Core Failure Resilience (CFR).

Abstract: Heterogeneous Multi-Processor System on Chips (HMPSoCs) combines different processors on a single chip. They enable powerful embedded devices, which increasingly perform Machine Learning (ML) inference at the edge. State-of-the-art HMPSoCs can perform on-chip embedded inference using their CPU, GPU, and integrated accelerators.

Abstract: Convolutional Neural Networks (CNNs) are now quintessential kernels within embedded computer vision applications deployed in edge devices. Heterogeneous Multi-Processor Systemon- Chips (HMPSoCs) with Dynamic Voltage and Frequency Scaling (DVFS) capable components (CPUs and GPUs) allow for lowlatency, low-power CNN inference on resource-constrained edge devices when employed efficiently.