Asymmetric multiprocessing (AMP or ASMP) systems have different types of CPUs, some with special roles like executing operating system code or handling I/O operations. Before symmetric multiprocessing (SMP) became widely available, AMP was the go-to method for managing multiple CPUs. It’s also used to offer cheaper alternatives on systems with SMP capability. AMP systems vary in how they distribute tasks among CPUs, making some more specialized for specific task than others. AMP architecture elevates system’s performance and capabilities because the processing resources are distributed in a more efficient way.


Processing cores are stratified in AMP architecture in such a way that high-performance cores are consumed by compute intensive workloads such as big data processing, while workloads that do not require much computing resources are handled by low-performance cores. This ensures that least resources are consumed while maintaining efficiency. AMP systems are often used in embedded systems, such as smartphones, IoT devices, and consumer electronics, where specialized processors handle specific tasks like graphics processing, audio processing, or communication.

Benefits of AMP architecture:

• AMP boosts performance by assigning tasks to specific cores, cutting down response times and making critical apps run smoother.
• It saves power by spreading tasks across different cores, making devices more energy-efficient and giving longer battery life.
• With AMP, devices can handle multiple tasks at once because different cores handle different tasks simultaneously.
• Manufacturers can make devices cheaper by using a mix of powerful and low-power cores in one chip, giving you more bang for your buck.

Heterogeneous Computing

Heterogeneous computing takes asymmetric multiprocessing a step futher by incorporating different kinds of coprocessors and accelerators with specialised processing capabilities. Heterogeneous systems utilize specialized accelerators for tasks like scientific simulations and machine learning, boosting performance significantly. They offer versatility across various applications and environments, optimized energy usage, and scalability through the addition of more accelerators to accommodate increasing workloads efficiently.

In conclusion, the AMP architecture stands out as an exceptionally efficient and resourceful processing design. However, it does come with its own set of drawbacks. Developing software for these architectures is a complex task, as task scheduling and load balancing across different components require advanced algorithms and techniques.