BARCELONA — GreenWaves Technologies, a startup based in Grenoble, France, launched an apps processor designed to do image, sound and vibration AI analysis on battery-operated sensing devices. The processor, called GAP8, is built on the RISC-V and PULP open-source projects.
Greenwaves’ first sample chip just came back last week from TSMC, which built it using its 55nm low power process. With this brainchild in hand, the company is pitching its GAP8 processor and GAP8 software development kit this week both at Mobile World Congress here and Embedded World in Nürnberg, Germany.
Mike Demler, senior analyst at the Linley Group, told us, “It’s the first time I’ve seen someone add a neural engine to an MCU-class processor.”
The move by the French startup illustrates how the AI frenzy is infecting even the IoT world, where most edge devices are both resource- and power-constrained.
Founded in 2014, Greenwaves didn’t originally aim to design embedded AI processors. The initial goal, to do an innovative orthogonal frequency-division multiplexing (OFDM) algorithm known as GreenOFDM on a processor, however, recently shifted focus. The company reset its sights on machine learning applications, acknowledged Loïc Liétar, co-founder and CEO of GreenWaves. This pivot became inevitable, explained Liétar, when he saw “far more [market] traction” on the processor’s ability to do “content understanding (image, sound, vibration).”
GreenWaves was born when two projects merged into one. Liétar was originally interested in solving the high-power consumption limits of OFDM and was looking for an appropriate processor architecture to map his algorithm. Eric Flamand, Liétar’s long-time friend and now GreenWaves’ CTO, was then developing an ultra-low power processor for content understanding. After the two decided to join forces as a single startup, they leveraged Flamand’s PULP-based architecture to offer both machine learning functions and GreenOFDM.
Asked about whatever happened to GreenOFDM, Liétar noted, “A couple of customers are interested in the SW modem capabilities of GAP8, albeit not for GreenOFDM, which would require the development of a specific power amplifier to deliver on its promise.”
Put simply, GreenWaves’ GAP8 consists of nine RISC-V cores. One serves as a fabric controller managing peripherals and communication with the outside world. The other eight cores are organized in a cluster with shared data and instruction memory. The cluster — consisting of eight RISC-V cores — has an integrated hardware convolution computation engine that accelerates inference calculations for convolutional neural networks (CNNs).
According to Greenwaves, the fabric controller and cluster live in separate voltage and frequency domains, so that each consumes power only when necessary. Greenwaves also used the standard RISC-V ISA extension mechanism to add instructions that boost performance for DSP-centric operations, which are frequently found in the algorithms executed on the cluster.
Liétar explained, “For most developers, GAP8 is programmed just like any MCU.”
When compute-intense tasks need to be launched, they go to the cluster through the APIs of a rich compute library included in the GAP8 SDK. “A tool-driven methodology also allows trained CNNs described with an AI framework to be optimized for and ported onto GAP8,” he added.
Continue to page two on Embedded's sister site, EE Times: “AI comes to sensing devices.”