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Found 5 papers, 2 papers with code
MOELA: A Multi-Objective Evolutionary/Learning Design Space Exploration Framework for 3D Heterogeneous Manycore Platforms
To enable emerging applications such as deep machine learning and graph processing, 3D network-on-chip (NoC) enabled heterogeneous manycore platforms that can integrate many processing elements (PEs) are needed.
RACE: A Reinforcement Learning Framework for Improved Adaptive Control of NoC Channel Buffers
Network-on-chip (NoC) architectures rely on buffers to store flits to cope with contention for router resources during packet switching.
A Survey of Resource Management for Processing-in-Memory and Near-Memory Processing Architectures
Due to amount of data involved in emerging deep learning and big data applications, operations related to data movement have quickly become the bottleneck.
Hardware Architecture
Learning-based Application-Agnostic 3D NoC Design for Heterogeneous Manycore Systems
Our results show that these generalized 3D NoCs only incur a 1. 8% (36-tile system) and 1. 1% (64-tile system) average performance loss compared to application-specific NoCs.
Machine Learning and Manycore Systems Design: A Serendipitous Symbiosis
Tight collaboration between experts of machine learning and manycore system design is necessary to create a data-driven manycore design framework that integrates both learning and expert knowledge.
