Compiling And Optimizing Neural Nets


Edge inference engines often run a slimmed-down real-time engine that interprets a neural-network model, invoking kernels as it goes. But higher performance can be achieved by pre-compiling the model and running it directly, with no interpretation — as long as the use case permits it. At compile time, optimizations are possible that wouldn’t be available if interpreting. By quantizing au... » read more

RISC-V’s Expanding Footprint


Zdenek Prikryl, CTO of Codasip, sat down with Semiconductor Engineering to talk about the RISC-V market, where this open instruction set architecture (ISA) is gaining ground, and what are the biggest challenges in working with this technology. SE: Where do you see the value in RISC-V? Is it for off-the-shelf processors or more customized components? Prikryl: A few years ago, RISC-V was us... » read more

What Happened To Execute-in-Place?


Executing code directly from non-volatile memory, where it is stored, greatly simplifies compute architectures — especially for simple embedded devices like microcontrollers (MCUs). However, the divergence of memory and logic processes has made that nearly impossible today. The term “execute-in-place,” or ”XIP,” originated with the embedded NOR memory in MCUs that made XIP viable. ... » read more

RISC-V Gaining Traction


Part 1: Semiconductor Engineering sat down to discuss where and why RISC-V is doing well, with Zdenek Prikryl, CTO of Codasip; Helena Handschuh, a Rambus Security Technologies fellow; Louie De Luna, director of marketing at Aldec; Shubhodeep Roy Choudhury, CEO of Valtrix Systems; and Bipul Talukdar, North America director of applications engineering at SmartDV. What follows are excerpt of that ... » read more

Data Strategy Shifting Again In Cars


Carmakers are modifying their data processing strategies to include more processing at or near the source of data, reducing the amount of data that needs to be moved around within a vehicle to both improve response time and free up compute resources. These moves are a world away from the initial idea that terabytes of streaming data would be processed in the cloud and sent back to the vehicl... » read more

Powering The Edge


On-device machine learning (ML) is a phenomenon that has exploded in popularity. Smart devices that are able to make independent decisions, acting on locally generated data, are hailed as the future of compute for consumer devices: on-device processing slashes latency; increases reliability and safety; boosts privacy and security...all while saving on power and cost. Although ML in edge d... » read more

Making Sense Of PUFs


As security becomes a principal design consideration, physically unclonable functions (PUFs) are seeing renewed interest as new players emerge onto the market. PUFs can play a central role in hardware roots of trust (HRoTs), but the messaging in the market can make it confusing to understand the different types of PUF as well as their pros and cons. PUFs leverage some uncertain aspect of som... » read more

Connectivity Key To Growing MCU Market


“It is a truth universally acknowledged, that an MCU without connectivity, must be in want of a Wi-Fi.” A picture paints a thousand words and for ambitious companies with microcontroller unit (MCU) technology, the picture below is very clear – market growth in IoT-oriented connected devices offers great opportunities. In a slow-growing market, each new design win requires the removal... » read more

IoT Debugging Crosses The Hardware-Software Divide


By Paul Hill and Gordon MacNee Debugging is an important part of embedded design; one that necessarily crosses the hardware/software divide. At a system level, the functionality of an embedded design is increasingly defined by firmware, so avoiding bugs requires engineers with specific disciplines to work closely together during the design phase of a project. It can also mean resisting the u... » read more

Auto Outlook: Down But Not Out


For years, automotive has been an engine of growth in the semiconductor industry, although the market is expected to decline in 2020. Several types of chips are used in automobiles, such as analog, memory, microcontrollers, processors and RF. But the automotive IC business still represents a small percentage of the overall semiconductor market. It pales in comparison to the smartphone chip m... » read more

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