MCU-based implementation of Glow neural network compiler: Page 2 of 2

July 29, 2020 //By Ally Winning
NXP has introduced its eIQ Machine Learning (ML) software support for the Glow neural network (NN) compiler.
NXP has introduced its eIQ Machine Learning (ML) software support for the Glow neural network (NN) compiler.
to measure performance. MCU benchmarks include standard NN models, such as CIFAR-10. Using a CIFAR-10 model as an example, the benchmark data acquired by NXP shows how to leverage the performance advantage of the i.MX RT1060 device (with 600MHz Arm Cortex-M7), i.MX RT1170 device (with 1GHz Arm Cortex-M7), and i.MX RT685 device (with 600 MHz Cadence Tensilica HiFi 4 DSP).

NXP’s enablement for Glow is tightly coupled with the Neural Network Library (NNLib) that Cadence provides for its Tensilica HiFi 4 DSP delivering 4.8GMACs of performance. In the same CIFAR-10 example, NXP implementation of Glow achieves a 25x performance advantage by using this DSP to accelerate the NN operations.

NXP’s eIQ for Glow NN compiler is available now, delivered via MCUXpresso SDK for i.MX RT600 Crossover MCUs, as well as i.MX RT1050 and i.MX RT1060 crossover MCUs. eIQ for Glow NN compiler will be available for other NXP MCUs in the future.

More information

www.nxp.com/eiq

www.nxp.com/eiq/glow

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