Nikoleta Iliakopoulou, Jovan Stojkovic, et al.
MICRO 2025
This brief presents an overview of recent tools and research efforts aimed at enhancing the programmability and reliability of In-Memory Computing (IMC)-based systems. We discuss hardware-aware training techniques that improve model resilience to analog device imperfections, and explore mapping strategies that balance accuracy and performance for heterogeneous IMC-based accelerators. Additionally, we examine a compiler framework that abstracts hardware complexities and enables seamless integration of these accelerators into existing deployment pipelines. By combining these approaches with advanced simulation tools, we propose an end-to-end workflow that facilitates the practical deployment and optimization of IMC technologies across diverse memory types and architectural designs.
Nikoleta Iliakopoulou, Jovan Stojkovic, et al.
MICRO 2025
Ilias Iliadis
International Journal On Advances In Networks And Services
Alessandro Pomponio
Kubecon + CloudNativeCon NA 2025
Haoran Qiu, Weichao Mao, et al.
ASPLOS 2024