Optimised software enables low-power neural network inferencing

“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.”

“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.”

18-03-2020 | Cadence | Subs & Systems