As artificially intelligence creeps its way into our smartphone experience, SoC vendors have been racing to improve neural network and machine learning performance in their chips. Everyone has a different take on how to power these emerging use cases, but the general trend has been to include some sort of dedicated hardware to accelerate common machine learning tasks like image recognition.

However, the hardware differences mean that chips offer varying levels of performance. Last year it emerged that HiSilicon’s Kirin 970 bested Qualcomm’s Snapdragon 835 in a number of image recognition benchmarks.

Honor recently published its own tests revealing claiming the chip performs better than the newer Snapdragon 845 as well. We’re a little skeptical of the results when a company tests its own chips, but the benchmarks Honor used (Resnet and VGG) are commonly used pre-trained image recognition neural network algorithms, so a performance advantage isn’t to be sniffed at.

The company claims up to a twelve-fold boost using its HiAI SDK versus the Snapdragon NPE. Two of the more popular results show between a 20 and 33 percent boost.

The big difference between Kirin 970 vs Snapdragon 845 is HiSilicon’s option implements a Neural Processing Unit designed specifically for quickly processing certain machine learning tasks. Meanwhile, Qualcomm repurposed its existing Hexagon DSP design to crunch numbers for machine learning tasks, rather than adding in extra silicon specifically for these tasks. Read more from androidauthority.com…

thumbnail courtesy of androidauthority.com