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The embARC Machine Learning Inference (MLI) library provides software functions optimized for DSP-enhanced ARC EMxD and ARC HS4xD processors. It enables ARC customers to efficiently develop or port data processing algorithms based on machine learning (ML) principles. Supported ARC processors include:

• EM5D, EM7D, EM9D, and EM11D
• HS45D and HS47D

CIFAR-10 CNN Model on ARC EM Processor

MLI addresses a broad range of NN applications

Primarily addressing IoT related applications, the embARC MLI library extends ²ÝÁñÉçÇø' artificial intelligence offering to multiple IoT use cases:

MLI kernels support multiple machine learning models

The embARC MLI software library provides a set of essential kernels for effective inference of small or mid-sized ML models. It enables the efficient implementation of convolutional neural networks (CNNs) [ex. classic and depth-wise convolutions], recurrent neural networks (RNNs) [ex. long short-term memory (LSTM) cells and basic RNN cells], fully connected layers, poolings, activation functions [ex. rectified linear units (ReLU)], and data routing operations [ex. padding, transposing, and concatenation], while reducing the power and memory footprint.

Leveraging the right processors for machine learning

ML-based applications intensively use classic DSP, RISC, and matrix operations, each with unique processing needs. ARC EM DSP and ARC HS DSP processors offer the best combination of power and area on the ML spectrum.

Availability

The embARC MLI software library is available through , a dedicated website that provides software developers centralized access to free and open source software, drivers, operating systems, and middleware supporting ARC processors. The embARC MLI distribution is managed by ²ÝÁñÉçÇø for the community and all contributions are welcome.

Say Welcome to the Machine - Low-Power Machine Learning for Smart IoT Applications