Computational cost refers to the resources required to execute an algorithm or process, including time, memory, and energy consumption. Understanding computational cost is crucial for optimizing performance and efficiency, especially in resource-constrained environments such as embedded systems or large-scale data processing.

Computational Cost

Computational cost

resources required

execute an algorithm

Time is a fundamental dimension that allows for the sequencing of events, the comparison of durations, and the understanding of change. It is a central concept in physics, philosophy, and various other disciplines, influencing how we perceive the universe and our place within it.

time

Memory is a cognitive process that involves encoding, storing, and retrieving information, allowing humans to retain past experiences and knowledge for future use. It is a complex system influenced by biological, psychological, and environmental factors, crucial for learning, decision-making, and identity formation.

memory

Energy consumption refers to the amount of energy utilized by various systems, industries, and households, which is a critical factor in economic development and environmental impact. Managing energy consumption efficiently is essential for reducing carbon emissions and promoting sustainable energy practices.

energy consumption

optimizing performance

Efficiency is the ability to achieve a desired outcome with the least amount of wasted resources, such as time, energy, or materials. It is a critical factor in both economic systems and engineering processes, driving innovation and competitiveness by maximizing output while minimizing input.

efficiency

resource-constrained environments

Embedded systems are specialized computing systems that perform dedicated functions within larger mechanical or electrical systems, often operating with real-time constraints. They are integral to a wide range of applications, from consumer electronics to industrial machines, where they enhance functionality, efficiency, and reliability.

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