Floating point cost on embedded systems in Embedded C

Introduction

Floating point operations use more time and power on small devices. Knowing this helps write faster and efficient code.

When programming small devices like microcontrollers with limited power.

When you want your device to run longer on battery.

When you need your program to respond quickly without delays.

When you want to save memory and processing power.

When you decide between using whole numbers or decimals in calculations.

Syntax

Embedded C

float myNumber = 3.14f;
double myDouble = 3.14159;

Floating point numbers store decimal values like 3.14 or 2.718.

Using float uses less memory than double, but is less precise.

Examples

Use float for decimal numbers when less precision is okay.

Embedded C

float temperature = 36.5f;
// stores temperature with decimals

Use int for whole numbers to save time and power.

Embedded C

int count = 10;
// whole number, faster and cheaper to use

double gives more decimal places but costs more resources.

Embedded C

double preciseValue = 3.1415926535;
// more precise but slower on small devices

Sample Program

This program measures how long it takes to add numbers using floats versus ints. It shows floats usually take more time on embedded systems.

Embedded C

#include <stdio.h>
#include <time.h>

int main() {
    clock_t start, end;
    volatile float f = 0.0f;
    volatile int i = 0;
    int loops = 1000000;

    // Measure time for float addition
    start = clock();
    for (int j = 0; j < loops; j++) {
        f += 0.1f;
    }
    end = clock();
    double float_time = (double)(end - start) / CLOCKS_PER_SEC;

    // Measure time for int addition
    start = clock();
    for (int j = 0; j < loops; j++) {
        i += 1;
    }
    end = clock();
    double int_time = (double)(end - start) / CLOCKS_PER_SEC;

    printf("Float addition time: %f seconds\n", float_time);
    printf("Int addition time: %f seconds\n", int_time);

    return 0;
}

Important Notes

Floating point math can be much slower than integer math on small chips without special hardware.

Using integers or fixed-point math can save power and speed up your program.

Always test your program's speed if you use floating point on embedded devices.

Summary

Floating point operations cost more time and power on embedded systems.

Use integers when possible to make your program faster and more efficient.

Measure and test your code to choose the best number type for your needs.

Practice

1. Why are floating point operations generally avoided on embedded systems?

easy

A. They require less memory than integer operations.

B. They consume more time and power compared to integer operations.

C. They always produce inaccurate results.

D. They are easier to implement than integer operations.

Solution

1. Step 1: Understand floating point vs integer operations

   Floating point operations involve more complex calculations than integer operations.

2. Step 2: Consider embedded system constraints

   Embedded systems have limited processing power and battery life, so slower and power-hungry operations are costly.

3. Final Answer:

   They consume more time and power compared to integer operations. -> Option B

4. Quick Check:

   Floating point cost = More time and power [OK]

Hint: Floating point = slower and power hungry on embedded [OK]

Common Mistakes:

• Thinking floating point uses less memory
• Assuming floating point is always more accurate
• Believing floating point operations are faster

2. Which of the following is the correct way to declare a floating point variable in embedded C?

easy

A. float temperature = 23.5;

B. int temperature = 23.5;

C. double temperature = '23.5';

D. float temperature = '23,5';

Solution

1. Step 1: Check variable type and value format

   Floating point variables use the keyword 'float' and values use dot (.) as decimal separator.

2. Step 2: Validate syntax correctness

   float temperature = 23.5; uses float and a correct decimal number with dot, so it is correct.

3. Final Answer:

   float temperature = 23.5; -> Option A

4. Quick Check:

   float with dot decimal = correct syntax [OK]

Hint: Use float keyword and dot decimal for floats [OK]

Common Mistakes:

• Using int for decimal numbers
• Using quotes around numbers
• Using comma instead of dot for decimals

3. What is the main drawback of this embedded C code snippet?

float a = 1.5f;
float b = 2.5f;
float c = a * b;
printf("%f", c);

medium

A. It uses floating point multiplication which is slower on embedded systems.

B. It will print an integer instead of a float.

C. It will cause a syntax error due to missing semicolons.

D. It uses incorrect format specifier in printf.

Solution

1. Step 1: Analyze the code operations

   The code multiplies two float variables and prints the result using %f, which is correct syntax.

2. Step 2: Consider embedded system performance

   Floating point multiplication is slower and consumes more power on embedded systems compared to integer operations.

3. Final Answer:

   It uses floating point multiplication which is slower on embedded systems. -> Option A

4. Quick Check:

   Floating point multiply = slower on embedded [OK]

Hint: Floating point math is slower than integer math [OK]

Common Mistakes:

• Thinking code has syntax errors
• Confusing format specifiers
• Assuming output is integer

4. Identify the error in this embedded C code snippet:

float x = 3.0;
int y = 2;
float z = x / y;
printf("%d", z);

medium

A. Variable z should be declared as int.

B. Division between float and int is not allowed.

C. Using %d to print a float variable causes incorrect output.

D. Missing semicolon after variable declarations.

Solution

1. Step 1: Check variable types and operations

   Variable z is float, result of float divided by int, which is valid and results in float.

2. Step 2: Check printf format specifier

   Using %d expects an int, but z is float, so output will be incorrect or undefined.

3. Final Answer:

   Using %d to print a float variable causes incorrect output. -> Option C

4. Quick Check:

   Printf %d with float = wrong output [OK]

Hint: Match printf format to variable type [OK]

Common Mistakes:

• Thinking division of float and int is invalid
• Assuming variable type declaration is wrong
• Ignoring printf format specifier importance

5. You want to optimize an embedded system program that calculates average sensor readings. Which approach best reduces floating point cost while keeping accuracy?

hard

A. Replace all floats with doubles for better precision.

B. Convert sensor readings to strings and parse them later.

C. Use floating point operations directly for all calculations.

D. Use integer arithmetic by scaling sensor values and divide after summing.

Solution

1. Step 1: Understand floating point cost and accuracy needs

   Floating point operations are costly; using integers scaled by a factor preserves accuracy and reduces cost.

2. Step 2: Evaluate options for optimization

   Use integer arithmetic by scaling sensor values and divide after summing. uses integer math with scaling, which is efficient and accurate. Replace all floats with doubles for better precision. increases cost. Use floating point operations directly for all calculations. ignores cost. Convert sensor readings to strings and parse them later. is inefficient and unnecessary.

3. Final Answer:

   Use integer arithmetic by scaling sensor values and divide after summing. -> Option D

4. Quick Check:

   Scale integers to avoid floats = efficient and accurate [OK]

Hint: Scale integers to avoid floats for efficiency [OK]

Common Mistakes:

• Assuming doubles are always better
• Ignoring floating point cost
• Using string conversions unnecessarily