Maxim Launches Edge AI MAX78000 SoC with Neural Network Accelerator, RISC-V Coprocessor

Launched with the claim of performing edge AI tasks in one percent of the power envelope required by rivals, the MAX78000 impresses.

Maxim Integrated has announced the launch of a new chip for the IoT, the MAX78000, claiming to accelerate edge AI tasks for a hundredth of the power required by rival platforms.

"We've cut the power cord for AI at the edge," says Kris Ardis, executive director for the Micros, Security, and Software business unit at Maxim Integrated, of the MAX78000's launch. "Battery-powered IoT devices can now do much more than just simple keyword spotting. We've changed the game in the typical power, latency and cost trade-off, and we're excited to see a new universe of applications that this innovative technology enables."

The MAX78000 system-on-chip (SoC) is built around a dual-core Arm Cortex-M4 processor, with floating-point unit, running at up to 100MHz, with 512kB of flash memory and 128kB of static RAM (SRAM) plus a performance-boosting 16kB instruction cache. It also includes a low-power 60MHz coprocessor based on the free and open source RISC-V instruction set architecture - the same approach as taken by rival Espressif for its recently-launched ESP32-S2.

It's the neural network accelerator which Maxim is looking to push, though. Optimised for deep convolutional neural networks, the accelerator boasts a weight storage memory of 442kB, data memory of 512kB of SRAM, and supports 1-, 2-, 4-, and 8-bit weights for networks of up to 3.5 million weights in size. Networks are trained off-device using existing toolsets, including PyTorch and Tensorflow, then converted using Maxim-supplied tools for execution on the CNN accelerator.

Maxim claims the part is ideally suited for a range of edge AI tasks, including object detection and classification, audio processing with multi-keyword recognition, sound classification, and noise cancellation, facial recognition, and time-series data processing for heart rate and other health signal analyses, signal analysis, multi-sensor analysis, and predictive maintenance applications.

Full details on the part are available on the Maxim website, though pricing is only "on request;" an evaluation kit is also available, priced at $168.

Gareth Halfacree
Freelance journalist, technical author, hacker, tinkerer, erstwhile sysadmin. For hire: freelance@halfacree.co.uk.
Related articles
Sponsored articles
Related articles