In the golden era of electrical engineering, when yours truly was a budding designer, we worked with a processor, like an 8051 or an 8085, and we wrote some code to go with it. Programmable log? It existed, but those things were too darn expensive for what we called mainstream or mid-range applications. 

Fast forward to today, and you’d be hard pressed to come up with application that doesn’t make use of programmable logic.

In this episode of DevTalk with Rich and Vin, we look at today’s landscape of FPGAs, particularly those that are, in theory, aimed at the mid-range of the market. And we bring in a special guest, Gordon Hands, a Senior Director with Lattice Semiconductor.

We talked about this a little while ago, but it bears mentioning again, especially as a new entrant is being announced. There isn’t much development for FPGAs in the middle of the market. Products aimed at high end, with lots of compute performance are readily available. The same goes for the lower performance, yet much power-reduced, offerings.

Mid-range, general-purpose FPGAs are often chosen over other FPGAs, depending on application-specific requirements, for their versatility, cost-effectiveness, and balanced feature set that allows then to perform efficiently in a wide range of applications.

On this episode of Embedded Insiders, we’re discussing cyber resiliency with Eric Sivertson, VP of Security at Lattice Semiconductor, specifically highlighting how organizations can benefit from implementing a personalized data security plan, and how FPGAs can help. 

Embedded vision and processing applications benefit from hardware that is highly configurable with versatile integrated circuits that aid in the customization of a wide range of applications. Embedded vision, sensor fusion, industrial automation, medical imaging, IoT devices, and AI and machine learning are applications and technologies that are capable of processing data and accelerating applications with the help of an FPGA.

The automotive industry is in the midst of a technological transformation and, in particular, a shift to software-defined vehicles.

Automotive system designs and applications rely on modular hardware and software solutions that can keep up with the high-processing, low-power demands of in-vehicle display connectivity and data processing, ADAS sensor bridging and processing, and zonal bridging applications, which enable bridging and processing throughout the vehicle.