When Software Beats Hardware#

Not every problem needs a hardware solution, and recognizing when software is the better tool is one of the more valuable skills in electronics design. It’s tempting — especially when learning electronics — to default to hardware for everything. But the economics, flexibility, and development speed of software solutions often dominate, and ignoring that reality leads to over-designed, over-constrained systems.

The Default Bias Toward Hardware#

Electronics designers tend to solve problems in hardware because that’s the domain they know and enjoy. A signal needs filtering? Build a filter. A voltage needs to be precisely trimmed? Add a precision resistor network. A timing sequence needs to be controlled? Design a state machine in logic gates.

Each of these has a software alternative that may be simpler, cheaper, and more flexible. The question isn’t “can I do this in hardware?” — it almost always can be — but “should I?”

Signal Processing: Analog Filters vs Digital Filters#

One of the clearest examples of software replacing hardware is signal filtering. Consider a low-pass filter at 100 Hz to remove power-line noise from a sensor signal.

Hardware approach: Design a second-order active filter using an op-amp, two resistors, and two capacitors. The cutoff frequency is set by component values, so it shifts with component tolerances (typically 5-10% for standard capacitors) and temperature. Changing the cutoff frequency requires changing components.

Software approach: Sample the signal with an ADC at a sufficient rate (say, 1 kHz), and apply a digital filter in firmware. The cutoff frequency is set by coefficients that can be changed without hardware modifications. The filter response is perfectly repeatable and immune to component drift.

Neither approach is universally better. But if the system already has an MCU and ADC — and many modern designs do — the marginal cost of a software filter is essentially zero, while the hardware filter adds components, board area, and tolerance concerns.

Calibration: Firmware vs Precision Components#

A common need in sensor systems is correcting for offset and gain errors. There are two approaches:

Hardware precision: Use 0.1% resistors, precision voltage references, and low-drift op-amps to minimize errors at the circuit level. This can work, but the BOM cost is high and the design is still subject to temperature drift, aging, and production variation.

Software calibration: Use reasonable components (1% resistors, standard op-amps) and calibrate out the errors in firmware. Measure a known reference during production, store correction coefficients in non-volatile memory, and apply them to every reading.

Software calibration is standard practice in commercial instruments. A $200 multimeter doesn’t use $200 worth of precision components — it uses $20 worth of adequate components and calibrates them in software. The calibration can even be updated in the field.

This approach transforms a precision analog design problem into a data management problem, which is often much easier to solve.

Software-Configurable Behavior vs Hardware Variants#

Imagine a product that needs to be configured for different regions — one version for 120V mains, another for 240V. Or a sensor interface that needs to support multiple sensor types with different signal conditioning.

Hardware variants: Design separate boards or use jumpers and switches to configure the hardware. Each variant needs its own BOM, assembly instructions, and testing procedure. Inventory management becomes a headache.

Software configuration: Design the hardware to accommodate the full range, and select behavior through firmware configuration. A single hardware platform serves multiple applications, reducing inventory complexity and manufacturing overhead.

This pattern shows up everywhere in modern electronics. Programmable gain amplifiers, software-selectable input ranges, firmware-defined communication protocols — these all replace hardware variants with software flexibility.

The Cost Tradeoff: NRE vs Marginal Cost#

Software and hardware have fundamentally different cost structures:

• Software: High NRE (non-recurring engineering) cost to develop and debug, but zero marginal cost per unit. Once the firmware works, every unit benefits at no additional cost.
• Hardware: Lower NRE (a circuit is often faster to design than software), but every added component increases the marginal cost per unit.

At low volumes (prototypes, hobby projects, small-run products), software solutions are almost always cheaper because the NRE cost is spread across few units and the marginal cost savings from removing components are small.

At high volumes, the calculus can shift. If a $0.02 passive component eliminates the need for a firmware feature that took 40 hours to develop, the hardware solution might be economical at large volumes. But the flexibility advantage of software usually tips the balance back.

When Hardware Is the Right Answer#

Software can’t do everything. There are situations where hardware is the only viable approach or is clearly superior:

• Latency-critical paths. An analog comparator responds in nanoseconds. Software processing a digitized signal takes at least one ADC sample period — microseconds to milliseconds. For protection circuits, power supply control loops, and fast signal detection, hardware is necessary.
• Power-critical applications. Software requires an MCU to be awake and clocked. A hardware solution (a comparator, a voltage divider, a passive filter) draws microwatts or less. In ultra-low-power applications where the MCU sleeps most of the time, hardware handles the always-on functions.
• Physics constraints. Impedance matching, RF matching networks, EMI filtering — these are fundamentally physical problems. Software can optimize parameters, but the actual matching network is copper and components.
• Safety-critical functions. Overcurrent protection, overvoltage clamping, thermal shutdown — these must work even if the software has crashed. Hardware protection operates independently of software state.
• Analog signal integrity. Anti-aliasing filters must exist in hardware before the ADC. There’s no software workaround for aliased signals — once the information is folded, it can’t be unfolded.

Hybrid Approaches#

The most practical designs combine hardware and software, using each where it’s strongest:

• Hardware for the hard parts. Analog front-end with appropriate filtering and signal conditioning to get the signal into a usable range for the ADC.
• Software for the flexible parts. Digital filtering, calibration, communication protocols, user interface, data logging — everything that benefits from configurability and doesn’t require real-time analog performance.

A well-designed sensor interface, for example, might use a hardware instrumentation amplifier for its high common-mode rejection (a physics problem), followed by a hardware anti-aliasing filter (a Nyquist requirement), feeding an ADC whose output is digitally filtered, calibrated, linearized, and formatted in software. The hardware does what only hardware can do; the software does everything else.

This division isn’t always obvious. It evolves with experience and with the capabilities of available MCUs. As microcontrollers get faster and ADCs get better, the boundary shifts — more processing moves to software, and the analog front-end gets simpler.

Tips#

• If the system already has an MCU and ADC, consider moving filtering and calibration into firmware — the marginal cost is essentially zero compared to adding analog components
• Use software calibration with reasonable components (1% resistors, standard op-amps) instead of chasing precision hardware; store correction coefficients in non-volatile memory
• Design hybrid systems that use hardware for what only hardware can do (anti-aliasing, protection, impedance matching) and software for everything that benefits from flexibility
• Before adding a hardware variant for a configuration option, check whether firmware-selectable behavior can serve the same need with a single hardware platform

Caveats#

• Anti-aliasing is always a hardware problem. No amount of software filtering can recover from an undersampled signal — when digitizing analog signals, the anti-aliasing filter must exist in hardware before the ADC input
• Firmware bugs can be harder to find than hardware bugs. A wrong resistor value shows up on a multimeter, but a firmware timing bug might only appear under specific conditions after hours of operation — software flexibility comes with debugging complexity
• Software adds latency. Every firmware processing step takes time — ADC conversion, filter computation, communication — if the application is time-critical, measure the software latency budget before assuming the MCU can handle it
• Software requires a working MCU. If the MCU hasn’t booted yet (during power-up sequencing), or has crashed, or is in a brown-out state, all software functions are offline — critical functions that must work regardless of MCU state must be in hardware
• “We’ll fix it in firmware” is a dangerous phrase. It’s valid when the firmware fix is straightforward and the hardware is adequate, but dangerous when it becomes an excuse for not fixing a hardware design problem that should be fixed at the source
• Don’t forget the development tools. A software solution requires a development environment, a debugger, and someone who can write and maintain the code — if the project doesn’t already include firmware development, adding it solely to replace a simple hardware function may not save effort