Machine Learning Techniques for Understanding and Predicting Memory Interference in CPU-GPU Embedded Systems
Alessio Masola,
Nicola Capodieci,
Benjamin Rouxel
et al.
Abstract:Nowadays, heterogeneous embedded platforms are extensively used in various low-latency applications, including the automotive industry, real-time IoT systems, and automated factories. These platforms utilize specific components, such as CPUs, GPUs, and neural network accelerators for efficient task processing and to solve specific problems with a lower power consumption compared to more traditional systems. However, since these accelerators share resources such as the global memory, it is crucial to understand… Show more
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