Imagination NN cores implement variable data resolution

June 08, 2018 //By Peter Clarke
Imagination NN cores implement variable data resolution
IP licensor Imagination Technologies has announced two neural network accelerator cores; the first devices within the PowerVR Series2NX family that the company first disclosed in September 2017.

The AX2185 and AX2145 offer inferencing capability on mobile applications and support a high degree of flexibility in terms of data resolution across neural networks, one of the more notable features of the architecture.

The PowerVR 2NX  has been designed as a core for inferencing on a mobile SoC from the ground up. It is a scalable architecture that comes with up to 8 neural network compute engines. Each engine is capable of up to 128 16bit multiply accumulates per clock (MACs/clk) and 256 8bit MACs/clk, giving at the high end 1024 16bit and 2048 8bit MACs/clk.

The AX2185 targets the high-end smartphone, smart surveillance, and automotive markets. It features eight full-width compute engines and provides 2,048 MACs/clock (4.1 Tera Operations Per Second).

The AX2145 targets mid-range smartphone, digital TV and set-top box, smart cameras and consumer security markets. The PowerVR AX2145, which offers up to 1.0TOPS has a streamlined architecture intended to deliver neural network inferencing for ultra-low bandwidth systems. Imagination declined to provide TOPS-per-watt figures for the two cores.

Imagination has taken a broad view of its approach to neural networking acceleration with series of drivers and low-level APIs, SDKs and high-level APIs, compilers, debuggers and analytical tools  that interface between the hardware and open-source and third-party neural network framework tools.

In addition these software tools can direct neural networking to a variety or resources including general purpose processors, GPUs such as Imagination's own PowerVR range as well as the Series 2NX accelerators. Both cores support the Android Neural Networks API (NNAPI), used by developers to bring neural network capabilities to Android-based mobile devices.

Next: Vary the data resolution

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