Processor companies are packing more neural processing capability into processors for IoT edge devices. Here’s a look back at several of these that we covered in May.
Meta’s Reality Labs discussed a prototype AR processor at the 2024 ISSCC, fabricated using hybrid bonding as 3D packaging. This improved performance for the trial tasks of hand tracking and image processing.
Synaptics’ new Astra platform aims to ease the integration of more AI compute capability in IoT edge devices with Arm-based SoCs featuring AI acceleration engines and an ecosystem of supporting software and development tools.
Arm has updated its neural processing technology, offering its EthosU85 as a follow-on to the prior EthosU65. It positions Arm as having a critical new technology for the edge.
AMD’s latest series of processors for the enterprise market, the Ryzen PRO 8000 series, offers an upgraded AI engine that improves AI acceleration for businesses and professional users.
Arm has bolstered its automotive offering with CPUs, an image-signal processor, and multicore cluster infrastructure blocks. Configuration options enable ASIL B or ASIL D safety.
AMD plans a second generation of Versal AI Edge devices that integrate more CPUs with a more efficient hardware accelerator to bring more AI inference capability to edge applications.
NVIDIA’s Blackwell pods bring exascale compute to a rack while pushing the power envelope to 120 kW. The DGX GB200 NVL72 pod offers up to 1.44 ExaFLOPS of FP4 performance.
Cadence has updated its Vision DSP line to handle radar data types and instructions. It’s also offering an accelerator for high-FFT workloads such as 4D imaging radar.
NXP’s new S32N55, part of a new S32N processor family and the newly announced CoreRide brand, centralizes core driving functions that are currently implemented in localized ECUs.
Ambiq’s Apollo510 microcontroller pairs the company’s subthreshold energy-efficient design technology with vector acceleration performance to bring more AI capability to edge devices.
Renesas is testing demand for RISCV-based microcontrollers, introducing the first of what could be a series of such processors, the R9A02G021, targeting low-cost applications.
The new AI accelerator in Renesas’s RZ/V2H provides a boost in AI performance and efficiency to target high-performance robots that inhabit factory floors and smart homes and buildings.
NVIDIA has announced its Blackwell architecture, although the results are mixed. It is faster, but not as much so as the industry may have been expecting.
Microchip’s PIC16F13145 microcontroller includes a new configurable logic block that raises the amount of peripheral glue logic available by more than eight times compared with its predecessors.
Renesas and TSMC demonstrated two uses of fast MRAM at ISSCC. Renesas targets faster NVM; TSMC targets working memory. Their tradeoffs are very different.
