No NN-dedicated hardware on Qualcomm IoT processors

April 24, 2018 // By Peter Clarke
Qualcomm has announced two 10nm processors in support of IoT applications computing at the edge of the network, the quad-CPU QCS603 and the octa-CPUQCS605.

The chips are described as being part of the Qualcomm Vision Intelligence Platform although they provide support for both visual and audio processing. The SoCs include advanced camera processing software, machine learning and computer vision software development kits (SDKs), and connectivity and security technologies.

Both processors provide a lot of CPU, GPU, DSP and other processing resources. However, as with Qualcomm's Snapdragon line of processors it appears that while Qualcomm is prepared to support machine learning in software it is yet to provide dedicated hardware to accelerate this function. Both chips claim to support Tensorflow, Caffe and Caffe2 and other machine learning development environments using the Snapdragon Neural Processing Engine.

An engine sounds like hardware, right? Well yes but it this case it is a programming interface. As in the case of Snapdragon back in 2016 for now the neural network software piggybacks on the existing Kryo CPU, Adreno GPU and Hexagon DSP cores inside the SoC. Back then it was the Snapdragon 820 processor (see Qualcomm offers neural network SDK for Snapdragon processor). Now it is the same processing resources inside the QSC603 and QSC605.

It is notable that many IP core providers and fabless chip startup companies are now offering dedicated machine learning hardware. ARM, an IP provider with which Qualcomm has long-standing cooperation, has launched two machine learning  processors for which the IP is due to become available in mid 2018 (see ARM launches two machine learning processors).

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