Everyone has a part to play in the climate solution.

We all know that energy consumption is a major problem today. By 2040, the information and technology sector are expected to account for 14% of the world’s carbon emissions if the current trend continues. What if every techie out there can contribute to conserving the environment through simple coding practices?

Sustainable software engineering, a part of which we call ‘Green Coding’ aims at minimizing the energy used to complete a task. It works at the convergence of climate science, software, hardware, electricity market, and data center design to build and run sustainable software applications through efficient coding.

In order to reach a balance between performance and energy consumption, sustainable coding practices is the way to go. Simply put, Green Coding is a programming practice where codes are written to minimise the energy consumption of software, thereby limiting the potential environmental impact.

Performance of your code can be measured by:

  1. Execution time
  2. Memory used
  3. Energy consumed

Therefore, optimizing your code for maximum efficiency and minimal energy consumption can be done by improving these parameters towards sustainability.

Computational Efficiency in Your Coding Practices

Computational efficiency can be defined as getting the work done as quickly as possible. The task does not necessarily have to be completed in a shorter time for energy efficiency, however, completing a task faster allows the computer to return to a low-power-state so that more energy can be saved.

1. Code Size

More amount of data being sent over the Internet would mean more electricity consumed. Efficient coding practice would include having a check over the size of the code being sent over the Internet to reduce carbon emissions.

Decrease what is bloating your code that you don’t require, or users might not need. Install small part of packages wherever possible instead of large ones.

2. Coding Style and Choice of Compiler

Different coding practices for the same problem could produce different performance and energy consumption rates.

The process of choosing the right combination of the coding style and compiler, the combination which works best with the nature of the application and the target hardware, is necessary if the balance between performance and energy is a software design goal.

3. Use of Efficient Algorithms and Data Structures

Careless choice of algorithms and data structures can lead to significant energy wasting. Whereas targeted selection of algorithms and data structures can make massive difference in software performance.

Energy efficient programming requires using high performance algorithms that complete tasks faster, allowing the processor to idle. Central processor unit (CPU) being a dominant source of power consumption; therefore, optimization of the CPU can lead to significant energy efficiency improvements. Software engineers should investigate efficient solutions for a particular problem in order to exploit this energy saving potential.
The effort that has been put into choosing the most efficient algorithms will in turn benefit over time.

4. Multi-Threading

Single threaded applications are inefficient and prove to be waste of energy.

While you consider your OS for the implementation of threads and processes, usually threads are contained inside a process. Multiple threads can exist within the same process and share resources like memory. Multiprogramming operating systems permit two or more processes to be loaded in the executable memory at a time and loaded processes share the CPU using time multiplexing.

5. Efficient Use of Loops

Inefficient programming of loops and overuse of spinning and polling loops can be problematic. Designing the loops by following some simple rules can lead to important energy savings.

Energy efficiency can be optimized immensely by loop unrolling. Instructions called in multiple iterations of the loop into one single iteration reduces comparison and testing overhead associated with loops.

6. Efficient Use of Programming Languages

Energy consumed by the same algorithm varies differently based on the choice of programming language. Therefore, programming languages have a huge impact on the software energy consumption.

7. Energy Efficient Libraries and Drivers

Not exploiting the well-proven energy efficient solutions can lead to inefficient software. Libraries contain optimized implementations of common algorithms. Utilizing libraries and drivers, which are optimized for energy consumption, can improve the energy efficiency of an application.

8. Data Efficiency

Data retrieval from cache or memory costs time and energy. A data efficient software can be chosen that lessens the consumption of energy caused by data movement across memory hierarchy as well as increases software performance.

Therefore, reach a balance between performance and energy consumption by minimizing data movement and minimizing memory access.

Every small change in your sustainable practices leads to significant impact. As Sustainable Software Engineers, there are many advantages to building sustainable applications.

It is important to look end-to-end and take it step by step. Often making the effort to understand the full stack, from user experience to data center design or electricity grids, yields simple solutions that significantly improve carbon efficiency.