Final answer:
MAC units stand for 'Multiply-Accumulate' units, which are key to embedded ML platforms due to their efficiency in performing calculations essential to machine learning algorithms. They are ideal for embedded systems with limited resources and help facilitate the deployment of ML models in real-world applications.
Step-by-step explanation:
The term MAC units refer to 'Multiply-Accumulate' units, which are specialized hardware components used in embedded Machine Learning (ML) platforms.
The reason why MAC units are considered a key building block in embedded ML platforms is that they are extremely efficient at performing the types of calculations that are fundamental to ML algorithms, particularly neural networks.
Neural networks involve a large number of matrix multiplication and accumulation operations, which the MAC units are specifically designed to handle. Embedded ML platforms often operate under constraints such as limited power and computational resources. Therefore, having a dedicated hardware that can perform these operations quickly and efficiently is crucial for the performance and feasibility of ML applications within these embedded systems.
MAC units help in reducing the computational burden and power consumption, which makes the deployment of ML models in real-world applications, like mobile devices, wearable technology, and IoT devices, more practical and effective.