DSP Group Announces Support of TensorFlow Lite for Microcontrollers on its DBMD7 AI/ML SoC
Sdk for dbmd7 Allows Developers to Cost-Effectively Implement High-Performance Machine Learning Applications on Edge Devices to Avoid Latencies and Ensure End-User Privacy
DSP Group, Inc., a leading global provider of wireless and voice-processing chipset solutions for converged communications, announced software development kit (SDK) support for TensorFlow Lite for Microcontrollers for the DBMD7 family of low-cost, high-performance, multi-core AI and DSP processors. The SDK for the DBMD7 allows developers of AI IoT devices to cost-effectively deploy high-performance machine learning (ML) inference at the edge to avoid network latencies, minimize power consumption, ensure end-user privacy, and free up scarce network bandwidth.
“DSP Group offers compelling hardware for many low-power applications, so we’re excited to collaborate to offer machine learning software to help enable developers create products that wouldn’t be possible otherwise,” said Peter Warden, Staff Research Engineer at Google.
TensorFlow Lite for Microcontrollers is an extension of TensorFlow Lite that addresses the need to run ML on memory-constrained devices with only kilobytes of memory. It comes with a specific set of optimized operations to allow the execution of ML models for applications such as wake-word detection, sound detection, and image wake-up. In addition, developers can add their own ML algorithms. To further enhance efficiency, the DBMD7 has a floating point unit (FPU) for each of its high-frequency cores so TFL code can be executed optimally using either floating-point or fixed-point functions.
“By adding TensorFlow Lite for Microcontrollers to our SDK for the DBMD7 family of AI and DSP processors we allow designers to leverage Google’s open framework and tools to execute advanced audio and voice ML inference at the edge without compromising on cost or performance,” said Yosi Brosh, CVP and head of SmartVoice Product Line at DSP Group. “At the same time, they can take advantage of a platform that scales from two to eight microphones for far-field voice user interfaces (VUIs) and voice communications, which are supported by advanced audio processing algorithms based on our 30 years of experience and technical support in this space.”
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