There’s an odd duality in modern FPGA design. We want them to do more, compute more, include more features and deliver results faster and more efficiently. Yet at the same time, there are often competing demands for them to have a smaller footprint and use less power.
We see this in a wide range of embedded and edge applications, like CubeSat payload controllers, industrial robots and automotive ADAS modules, where compute needs to be at the sensor not on a distant processing board. In each case, the design needs meaningful processing capability but must fit within tight physical and power constraints, along with challenging thermal limits.
For FPGA engineers, these constraints are only part of the story. We also have to balance limited logic and memory resources, meet tight timing requirements, integrate multiple subsystems, and debug designs with only partial visibility into what’s happening inside the device. All while keeping power under control and ensuring the design behaves reliably in real-world scenarios, with often unpredictable vibrations, temperatures, and sensor behavior.
That’s quite an ask, and I’ve found the best approach is a methodical one. For example, we start by thinking carefully about architecture before touching RTL, so that we understand the data flows, define the interfaces up front, and avoid timing issues and integration conflicts later.
We then partition designs into well defined blocks, giving us clear boundaries, making verification more manageable, and letting us iterate on individual components. We also budget resources early so that we know where the pressure points will be, and can plan around BRAM, DSP and routing limits. And finally, we validate assumptions through simulation, iterating methodically, and being careful to check corner cases, exercise interfaces, and confirm that the design behaves as expected.
Small devices also change the way we approach the design flow itself. When logic, memory and I/O are limited, we can’t rely on brute force architectures or oversized safety margins. We have to be deliberate about data movement, choose the right abstractions, and think carefully about how each block contributes to overall system behavior. Even verification changes, because constrained devices reward designs that are simple, predictable and easy to exercise in simulation. In many ways, the device size forces a more disciplined, more thoughtful engineering process.
It will be interesting to see how vendors are helping us address challenges like this at FPGA Horizons Conference in London. A good example is the session, Leading Low Power, High Speed Small Form Factor System Devices. Harald Werner will look at how Efinix’s latest small form factor and SiP based devices are designed for the kinds of environments we’ve been talking about, where space is tight, power budgets are limited, and integration needs to be straightforward.
Engineers who want to explore these ideas hands on can also join the Efinix workshop, in which participants walk through the full Efinity flow and integrate a RISC V soft processor on an evaluation board. It’s a practical way to apply the same disciplined, resource aware approach to thinking bigger, even with smaller devices.
