ASP Lab 2

Lab 2: Energy Efficiency in Programming Languages

This lab explores the energy efficiency implications of programming language choices.

Key Findings on C Energy Efficiency

1. C tends to be more energy efficient than managed languages for several reasons:

   • Minimal runtime overhead (no garbage collection, JIT compilation)
   • Direct memory access without indirection
   • More efficient CPU instruction usage
   • Lower memory footprint

2. Research supports C efficiency: Studies like “Energy Efficiency across Programming Languages” (Pereira et al.) typically show C among the most energy-efficient languages, with Python and Java often using 2-3x more energy for equivalent tasks.

3. Trade-offs exist: C’s efficiency comes at the cost of development time, safety, and maintainability.

Broader Energy Considerations

1. Device usage profile matters:

   • For always-on server applications, language efficiency can significantly impact energy usage
   • For mobile/IoT devices with mostly idle time, language choice matters less than sleep/wake efficiency
   • For rarely-run applications, implementation efficiency matters less than algorithmic efficiency

2. Embodied carbon perspective:

   • Manufacturing a device typically represents 50-80% of its lifetime carbon footprint
   • Extending device lifespan through more efficient software can reduce overall environmental impact
   • For most consumer devices, the energy used during manufacturing exceeds the energy used during operation

3. Relative impact of programming language:

   • For compute-intensive applications (ML, rendering, simulation), language choice is significant
   • For I/O-bound or user-interaction applications, language efficiency has minimal impact
   • System architecture decisions usually have greater energy impact than language choice