{"id":409470,"date":"2021-01-06T08:33:25","date_gmt":"2021-01-06T13:33:25","guid":{"rendered":"http:\/\/www.marketnewsdesk.com\/?p=409470"},"modified":"2021-01-06T08:33:25","modified_gmt":"2021-01-06T13:33:25","slug":"syntiant-introduces-second-generation-ndp120-deep-learning-processor-for-audio-and-sensor-applications-in-battery-powered-devices","status":"publish","type":"post","link":"https:\/\/www.marketnewsdesk.com\/index.php\/syntiant-introduces-second-generation-ndp120-deep-learning-processor-for-audio-and-sensor-applications-in-battery-powered-devices\/","title":{"rendered":"Syntiant Introduces Second Generation NDP120 Deep Learning Processor\u00a0for Audio and Sensor Applications in Battery-powered Devices"},"content":{"rendered":"

\nLow-Power Syntiant Core 2 Delivers 25x Tensor Throughput Without Extensive Post-training Compilation
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IRVINE, Calif., Jan. 06, 2021 (GLOBE NEWSWIRE) — Syntiant Corp.<\/a>, a deep learning chip technology company advancing AI pervasiveness in edge devices, today announced the availability of its Syntiant\u00ae<\/sup> NDP120\u2122 Neural Decision Processor\u2122 (NDP), the latest generation of special purpose chips for audio and sensor processing for always-on applications in battery-powered devices.<\/p>\n

The NDP120 applies neural processing to run multiple applications simultaneously with minimal battery power consumption, including echo-cancellation, beamforming, noise suppression, speech enhancement, speaker identification, keyword spotting, multiple wake words, event detection, and local commands recognition.<\/p>\n

\u201cThe NDP120 is the first of a family of semiconductors using our next generation Syntiant Core 2 tensor processor platform that brings performance levels previously found in plugged-in devices to a power level suitable to run on batteries,\u201d said Kurt Busch, CEO of Syntiant. \u201cWe took years of real world, low-power edge deep learning experience to develop this architecture into a scalable design optimized to bring neural processing to power constrained deployments.\u201d<\/p>\n

\u201cSyntiant’s innovation around powerful, cost-effective, and yet power-efficient embedded silicon systems that bring machine learning capabilities right to the edge has been fascinating,\u201d said Arun Rajasekaran, head of technology strategy, wearables and sensors at Poly, a global communications company. \u201cBy optimizing its silicon for its deep learning models, Syntiant is making neural processing the pervasive technology to interface between people and machines.\u201d<\/p>\n

Syntiant\u2019s NDP120 brings always-on neural processing to all types of consumer products, including mobile phones, earbuds, wearables, smart speakers, laptops, smart home applications and security devices. Ideal for use cases where audio filtering and echo cancelation are required for far-field speech processing, the NDP120 packages the Syntiant Core 2\u2122, a highly flexible, ultra-low-power deep neural network inference engine, with a highly configurable audio front-end interface. The NDP120 also supports multi-modal sensor fusion, including sensors for infrared detection, multi-axis acceleration, tilt, magnetic field, and pressure.<\/p>\n

\u201cBraveHeart stands apart in the world of medical sensor applications because we have included Syntiant\u2019s ultra-low-power chip architecture in our design,\u201d said Stuart MacEachern, co-founder, VP of hardware engineering at BraveHeart Wireless Inc., a leading innovator in clinical-quality biometric wearables. \u201cBraveHeart’s applications and partners benefit from this powerful AI edge computing. We are able to offer greater functionality in our devices and be free from the cloud during processing which improves user privacy and security. The NDP120 delivers powerful processing at under one milliwatt, which translates to little strain on our battery consumption.”<\/p>\n

\n An Easy-to-Use Powerful Neural Network <\/strong>\n <\/p>\n

The Syntiant Core 2 moves larger neural networks into always-on domains with capacity to generate shared embeddings, run ensembles, and other neural architectures concurrently or in cascades. The Syntiant Core 2 is a tensor processing core built from the ground up to support energy efficient inference without compromising ease of programming. This second generation architecture delivers 25x the tensor throughput of the Syntiant Core 1\u2122 found in the Syntiant\u00ae<\/sup> NDP100\u2122 and Syntiant\u00ae<\/sup> NDP101\u2122 devices that are currently shipping in high volumes.<\/p>\n

Graph Native:
The Syntiant Core 2 is built around a highly optimized tensor-based memory and processing system designed to avoid inefficiencies in stored program architectures. Each layer independently controls its parameter, input, and output tensors consistent with graph-based execution, enabling neural designers with full control of multiple concurrent independent networks, or swapping network configurations depending on operating conditions.<\/p>\n

Framework Support:
The Syntiant Core 2 training development kit includes tools for running bit-exact simulations directly within high-level modeling languages, such as Tensorflow and Keras. All major frameworks can port to the Syntiant Core 2 runtime, including native support for multiple types of convolutional kernels, kernel striding, kernel dilation, downsampling layers, fully connected layers, pointwise operations, and a variety of activations.<\/p>\n

Compression When You Want It:
The evolving practice of neural compression is natively supported by the Syntiant Core 2. Network architectures can mix 1-, 2-, 4-, and 8-bit weights and higher precision bias terms. For the most challenging tasks, the Syntiant Core 2 supports high precision modes, including 16-bit inputs and outputs. Quantize inference when wanted, but not just because the edge processor requires it.<\/p>\n

Secret Sauce:
The Syntiant Core 2 supports a variety of task-dependent under the hood optimizations for sparsity and time series that speed up inference and reduce power requirements without extensive post-training network optimization. With design tools supplied by Syntiant, it is possible to explore the complete power, latency, memory, and parameter requirements on the Syntiant Core 2 interactively, and perform large scale hardware-aware hyperparameter searches with the same tools. The Syntiant Core 2 can shorten time-to-product by months or years as compared to more constrained and power-intensive solutions.<\/p>\n

\u201cSyntiant\u2019s highly configurable deep neural network provides enormous flexibility for low-power audio applications and feature extraction,\u201d said Clark Peng, vice president, head of product management at MSI, a world leader in gaming. \u201cThe NDP120\u2019s programmable DSP combined with its highly accurate inference engine are ideal for creating high performance voice command applications that can run across both traditional and machine learning algorithms.\u201d<\/p>\n

\n Special Purpose Silicon Designed to Run Multiple DNNs <\/strong>\n <\/p>\n

The NDP120 is equipped with an Arm Cortex M0 Processor and a HiFi-3 DSP. The NDP120\u2019s embedded Syntiant Core 2 supports more than 7 million parameters and can process multiple concurrent heterogeneous networks.<\/p>\n

Key features of the NDP120:<\/p>\n