Boost Embedded Systems: 5 Quick Performance Hacks

Embedded systems are the unsung heroes of modern tech: from smart thermostats to automotive ECUs, they run silently in the background. Yet, when performance dips, the whole product can feel sluggish or even fail to meet safety standards. The good news? You don’t need a PhD in quantum physics to squeeze extra speed out of your microcontroller. Below are five practical, bite‑sized hacks that will give your embedded code a turbo boost without breaking the bank.

1. Cut the C Runtime Footprint with –Os

Most compilers offer a family of optimization flags. The -Os flag tells GCC (or Clang) to “optimize for size” rather than speed. While this sounds counterintuitive, a smaller binary often runs faster because it fits better in cache and reduces instruction fetch stalls.

gcc -Os -mcpu=cortex-m4 -mthumb main.c -o firmware.bin

When you pair -Os with the -flto (link‑time optimization) flag, the compiler can inline across translation units, further trimming code size. Just remember: profile your system first. If a particular function is a hot spot, you might still need -O3 for that one.

2. Turn the Clock Down (and Keep Your Core Intact)

Speed isn’t just about CPU frequency. It’s also about how efficiently you use the clock cycles you have. Here are two tricks:

• Clock Gating: Disable peripheral clocks when idle. For example, if your UART is only used for debug logs, shut its clock off after initialization.
• Dynamic Frequency Scaling (DFS): Many MCUs support runtime frequency changes. Run at a lower clock when the system is idle, then spike up during heavy processing.

Example: On an STM32, you can toggle the PLL and system clock prescaler via the RCC registers. A quick table shows typical energy savings:

Case Study: The “Low‑Power Sensor Hub”

This project reduced its average power draw from 5 mA to 2.5 mA by gating the I²C bus when no sensors were active, without affecting data latency.

3. Inline What Matters, Not Everything

Function calls cost cycles—especially on 8‑bit cores. Inlining small, frequently called functions can eliminate those overheads.

#define MIN(a,b) ((a)<(b)?(a):(b))  // Classic macro

However, macros can be dangerous. Modern compilers let you request inlining with __attribute__((always_inline)). For example:

static inline uint8_t
__attribute__((always_inline)) min_uint8(uint8_t a, uint8_t b)
{
  return (a < b) ? a : b;
}

Benchmarks show up to 15 % speed improvement on tight loops, but always profile first. Over‑inlining can bloat the binary and hurt cache locality.

4. Use Fixed‑Point Arithmetic

Floating‑point units (FPUs) are great, but on many MCUs they’re either absent or slow. Fixed‑point arithmetic gives you deterministic performance and often better precision for embedded signals.

• Choose a scaling factor that covers your range (e.g., 16.16 for numbers between -32768 and +32767).
• Leverage the MULS instruction on ARM Cortex‑M4 for fast 32×32→64 multiplications.
• Wrap your fixed‑point math in a small library to keep the code readable.

Below is a simple fixed‑point multiply function:

int32_t fp_mul(int32_t a, int32_t b)
{
  int64_t temp = (int64_t)a * b;
  return (int32_t)(temp >> 16); // Assuming Q16 format
}

In a motor‑control demo, swapping floating point to fixed‑point cut latency from 120 µs to 70 µs.

5. Prioritize Your Interrupt Service Routines (ISRs)

Interrupt latency is a common bottleneck. A poorly designed ISR can starve your main loop and cause jitter.

• Keep ISRs short: do only what’s necessary and set a flag for the main loop to handle heavy lifting.
• Use __attribute__((interrupt)) to let the compiler know you’re in ISR context.
• Prioritize interrupts by adjusting NVIC_PriorityGroup on ARM Cortex‑M.
• Disable nested interrupts unless you truly need them.

A quick table shows typical ISR latency improvements:

Putting It All Together: A Mini Checklist

1. Profile first: Use gprof, Oprofile, or vendor tools to identify hot spots.
2. Apply -Os and -flto: Shrink the binary.
3. Implement clock gating and DFS: Reduce power and avoid wasted cycles.
4. Inline critical functions wisely: Balance size vs. speed.
5. Switch to fixed‑point where feasible: Faster math on limited cores.
6. Optimize ISRs: Short, prioritized, flag‑driven.

Follow this roadmap and you’ll see tangible gains—often 20–30 % in latency or power consumption—with minimal code churn.

Conclusion

Embedded optimization is less about chasing the highest clock speed and more about smart resource management. By trimming binary size, judiciously managing clocks, inlining selectively, embracing fixed‑point math, and refining interrupt handling, you can unlock significant performance gains. The best part? These hacks are straightforward enough for a weekend tinkerer yet powerful enough to satisfy seasoned firmware engineers.

So next time you’re staring at a sluggish sensor read or a battery that drains too fast, remember these five hacks. With a little profiling and some code tweaking, your embedded system can run faster, leaner, and more reliably—just like the superheroes it was built to be.