Cadence Design Systems has announced that software for Cadence Tensilica HiFi DSPs has been optimised to efficiently execute TensorFlow Lite for Microcontrollers, part of the TensorFlow end-to-end open-source platform for ML from Google. The blend of edge-based ML running on the ultra-low-power cores supports the increasing requirement for pervasive intelligence in advanced audio, voice and sensing applications.

The HiFi DSPs are the first DSPs to support TensorFlow Lite for Microcontrollers. With the extension of optimised software support for TensorFlow Lite operators on the HiFi DSP cores, developers are now able to take full advantage of the platform. This supports rapid development of edge applications that use AI and ML, eliminating the requirement for hand-coding the neural networks and ending in faster time to market and higher performance.

“Voice and audio AI applications are now mainstream, as voice-based user interfaces become more popular with consumers,” said Ian Nappier, product manager at Google. “TensorFlow Lite’s microcontroller software combined with optimised operators for the HiFi DSP makes developing and deploying innovative neural nets on low-power, memory-constrained audio DSPs easier than ever.”

“Our powerful crossover microcontroller, the i.MX RT600, includes a 600MHz Tensilica HiFi 4 DSP that delivers 4.8GMACs of performance,” explained Joe Yu, VP of microcontrollers at NXP Semiconductors. “This new MCU provides the optimal balance in power and performance. The compute power makes the i.MX RT600 ideal for our customers deploying voice, audio, and other neural network-based applications at the edge. Supporting the popular, end-to-end toolchain, TensorFlow, as well as other inferencing technologies, on the HiFi DSP will enable ML developers to take advantage of the compelling combination of compute and memory on this chip.”

“Enabling ML at the edge saves power, protects privacy and greatly reduces latency,” observed Yipeng Liu, director of audio/voice IP at Cadence. “Tensilica HiFi DSPs are the most widely licensed DSPs for audio, voice and AI speech. Support for TensorFlow Lite for Microcontrollers enables our licensees to innovate with ML applications like keyword detection, audio scene detection, noise reduction and voice recognition, with the assurance that they can run in an extremely low-power footprint.”