Selecting the right processing hardware is critical when developing embedded systems. Microcontrollers (MCUs), Digital Signal Processors (DSPs), and Field Programmable Gate Arrays (FPGAs) each serve different purposes, offering trade-offs in latency, power efficiency, parallelism, and computational complexity.
In this article, we explore when to use an MCU, DSP, or FPGA based on real-time processing requirements, computational demands, and system constraints.
1. Microcontrollers (MCUs): Low-Power, General-Purpose Processing
Overview
A microcontroller (MCU) is a compact, integrated processor that includes a CPU, memory (RAM, Flash), and peripherals (UART, SPI, I2C, ADC, timers). MCUs are designed for low-power, event-driven, real-time applications that require a balance between cost and performance.
Working Principle
- Executes sequential code using general-purpose instruction sets.
- Ideal for task scheduling, I/O control, and moderate real-time constraints.
- Often operates on low power, making it suitable for battery-powered devices.
When to Use an MCU
✔ Low-power embedded systems: Ideal for IoT sensors, medical devices, and smart home products.
✔ Control systems: Used in motor controllers, industrial automation, and automotive ECUs.
✔ Cost-sensitive applications: MCUs are inexpensive and require minimal external components.
✔ Peripheral-heavy systems: Best for applications requiring UART, SPI, ADC, PWM, and GPIO interactions.
Limitations
❌ Limited computational power: Not ideal for high-speed signal processing.
❌ Not optimized for parallel processing: Runs instructions sequentially, limiting performance in real-time, high-speed applications.
2. Digital Signal Processors (DSPs): Optimized for Real-Time Signal Processing
Overview
A DSP is a specialized processor designed for high-speed mathematical operations, particularly in real-time signal processing applications such as audio, video, and communications. DSPs optimize execution of Fourier Transforms (FFT), filtering, and convolution operations through hardware-accelerated Multiply-Accumulate (MAC) units and parallel execution.
Working Principle
- Executes parallel arithmetic operations efficiently.
- Supports hardware-accelerated mathematical functions such as FFT, FIR/IIR filtering, and vector multiplication.
- Works with fixed-point or floating-point number representation depending on precision requirements.
When to Use a DSP
✔ Audio and speech processing: Used in digital hearing aids, voice recognition, and noise cancellation.
✔ Wireless communication systems: Essential for modulation, demodulation, and filtering in 5G, Wi-Fi, and radar applications.
✔ Medical imaging and bio-signal processing: Ideal for ECG, EEG, ultrasound, and MRI signal filtering.
✔ High-speed control loops: Used in servo motor control, power inverters, and automotive radar.
Limitations
❌ Not highly flexible: DSPs are optimized for signal processing and may not be suitable for general-purpose control applications.
❌ Less customizable than FPGAs: Cannot implement hardware-specific optimizations like an FPGA.
3. Field Programmable Gate Arrays (FPGAs): Parallel and Reconfigurable Processing
Overview
An FPGA is a hardware-reconfigurable semiconductor device that uses programmable logic blocks to implement custom digital circuits. Unlike MCUs and DSPs, FPGAs execute tasks in true parallel processing, making them ideal for high-speed, low-latency, and real-time deterministic applications.
Working Principle
- Uses hardware logic gates and lookup tables (LUTs) to perform computations.
- Supports true parallel execution, enabling multiple operations simultaneously.
- Can be dynamically reprogrammed to implement different functionalities.
When to Use an FPGA
✔ Ultra-low-latency real-time processing: Essential for high-frequency trading, avionics, and military radar.
✔ Massively parallel computations: Ideal for AI inference, image processing, and deep learning acceleration.
✔ Custom hardware accelerators: Used in high-performance computing (HPC) and cryptographic applications.
✔ Industrial automation & robotics: Ideal for real-time vision systems, motor control, and sensor fusion.
Limitations
❌ Higher cost: FPGAs are expensive compared to MCUs and DSPs.
❌ Complex development: Requires expertise in VHDL/Verilog and FPGA toolchains.
❌ Higher power consumption: Not ideal for ultra-low-power embedded applications.
Comparison: MCU vs. DSP vs. FPGA
| Feature | Microcontroller (MCU) | Digital Signal Processor (DSP) | Field Programmable Gate Array (FPGA) |
| Processing Type | Sequential | Optimized for signal processing | True parallel execution |
| Power Consumption | Low | Medium | High |
| Complexity | Easy to program | Moderate | High (Requires FPGA programming) |
| Latency | Medium | Low | Ultra-low |
| Parallelism | Limited | Some SIMD support | High |
| Customization | Fixed instruction set | Some programmability | Fully customizable hardware |
| Cost | Low | Medium | High |
| Best Use Cases | General control tasks, IoT, sensors | Real-time signal processing | AI, image processing, high-speed computation |
Choosing the Right Processor for Your Application
| Application | Recommended Processing Unit |
| Battery-powered IoT sensors | Microcontroller (MCU) |
| Motor control & industrial automation | MCU or DSP |
| Audio & voice recognition | DSP |
| Wireless communication (5G, Wi-Fi, Radar) | DSP |
| AI & Machine Learning acceleration | FPGA |
| Real-time vision processing | FPGA |
| High-frequency trading | FPGA |
Final Thoughts
Selecting between an MCU, DSP, and FPGA depends on computational complexity, real-time constraints, power efficiency, and cost considerations.
✔ For general-purpose control & low-power applications, use an MCU.
✔ For high-speed signal processing, use a DSP.
✔ For ultra-fast, parallel processing & hardware customization, use an FPGA.
At Embedded RT, we specialize in hardware design, firmware development, and real-time processing solutions. Whether you’re building IoT sensors, DSP-based signal processors, or FPGA-accelerated AI systems, we can help!
📩 Need help selecting the right processor?
Contact us at info@embeddedrt.com or “Request a call back”
