Asymmetric Multiprocessing (AMP)

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As computing demands evolve, so does our approach to handling complex tasks on multi-CPU systems. One such method is Asymmetric Multiprocessing (AMP). Unlike its counterpart, Symmetric Multiprocessing (SMP), where tasks are evenly distributed among processors, AMP assigns specific tasks to dedicated CPUs. But what makes this division of labor effective, and how does it fit into the broader landscape of modern computing? Journey with us as we unpack the intricacies of AMP and its role in optimizing computer systems.

In this article:

  1. The Basics of Asymmetric Multiprocessing (AMP)
  2. How AMP Works: A Deep Dive
  3. Comparison: AMP vs. Symmetric Multiprocessing (SMP)
  4. Asymmetric Multiprocessing in Today’s Tech Landscape
  5. Future of Multiprocessing
  6. Conclusion
  7. Video

1. The Basics of Asymmetric Multiprocessing (AMP)

Asymmetric Multiprocessing (AMP) refers to a design approach in multiprocessor computer systems where each processor, or central processing unit (CPU), is allocated specific tasks to execute. This allocation is predefined, meaning each processor has a set role or function that doesn’t change dynamically based on system demands. For instance, in an AMP-configured system, one processor might be dedicated exclusively to input/output (I/O) operations, while another might be reserved solely for executing network requests or running particular user applications.

The concept of AMP arises from the need to optimize processing capabilities in computers with multiple CPUs. By allocating specific tasks to individual processors, systems can ensure that there’s a specialized unit handling each operation type, leading to potential improvements in efficiency and responsiveness.

 Asymmetric Multiprocessing - AMP
Asymmetric Multiprocessing – AMP

Historical Context and Evolution

The origins of Asymmetric Multiprocessing date back to the early days of computing, when the initial multiprocessor systems were being developed. These early systems faced challenges in managing the distribution of tasks among available processors. There was a need to ensure that while making the best use of the additional processing power, system complexities didn’t result in reduced overall performance.

Initially, assigning specific roles to processors seemed like an intuitive solution. It minimized contention for resources and simplified the design of the operating system since each CPU had a clear, delineated role. For instance, systems might have had one processor handling all system calls and another handling user-level computations.

However, as technology evolved, so did the methodologies for task distribution. The rise of Symmetric Multiprocessing (SMP), where tasks are dynamically assigned to processors based on availability, began to overshadow AMP. SMP offered more flexibility and could potentially use all available processors more uniformly, thereby maximizing resource utilization.

Yet, AMP wasn’t entirely abandoned. Even as SMP became the dominant model, specific scenarios and systems benefited from the predictable and specialized nature of Asymmetric Multiprocessing. Especially in real-time and embedded systems, where predictability can be more crucial than raw performance, AMP found its niche.

2. How AMP Works: A Deep Dive

Assigning Specific Tasks to CPUs

In an Asymmetric Multiprocessing (AMP) environment, the architecture is intentionally designed so that specific tasks are assigned to individual central processing units (CPUs). This is unlike Symmetric Multiprocessing (SMP), where tasks are dispatched to any available processor without predefined specialization.

The assignment of tasks in Asymmetric Multiprocessing often mirrors the nature and criticality of those tasks. For instance, time-critical tasks might be assigned to a high-performance processor, while less urgent tasks might be allocated to a standard processor. This process begins during system design and configuration, where decisions are made about which processor will handle which tasks based on factors like task priority, expected load, and processor capability.

Typically, operating systems running on AMP architectures have mechanisms in place to ensure these assignments are adhered to. Task schedulers and other system tools are designed to recognize the specialized roles of each processor and distribute tasks accordingly.

Benefits of Task-Specific Allocation

  1. Predictable Performance: One of the foremost advantages of AMP is the predictability it offers. When tasks are allocated to specific processors, it’s easier to anticipate system behavior, making AMP ideal for real-time systems where consistent response times are crucial.
  2. Optimized Utilization: By dedicating processors to specific tasks, systems can ensure that specialized processors are fully utilized for their intended purposes, leading to potential gains in efficiency.
  3. Simplified System Design: With processors assigned clear, defined roles, system design and operating system architecture can be simplified. This reduces the complexities involved in dynamic task allocation.
  4. Reduced Resource Contention: In AMP systems, because processors have designated roles, there’s a lower likelihood of multiple processors contending for the same resources, leading to smoother operations.

Potential Limitations and Challenges

  1. Inflexibility: One of the main challenges of AMP is its relative inflexibility. Because processors have predefined roles, they might remain idle if their specific task isn’t demanding resources, while other processors are overloaded.
  2. Complex Initial Setup: While system design might be simplified in the long run, the initial setup and configuration can be complex, requiring careful planning to allocate tasks optimally.
  3. Scalability Concerns: As the number of tasks or the nature of tasks change over time, an AMP system might need significant reconfiguration to adapt, making scalability a potential concern.
  4. Underutilization: If one specific task doesn’t have much to process, the dedicated CPU for that task can remain underutilized, wasting potential computational power.

In conclusion, while AMP offers a structured and predictable approach to task management in multiprocessor systems, it’s not without its challenges. The choice between AMP and other methodologies often depends on the specific needs and priorities of the system in question.

3. Comparison: AMP vs. Symmetric Multiprocessing (SMP)

This contrasts symmetric multiprocessing (SMP), in which the operating system evenly distributes the application load across multiple processors. In SMP, individual processes are not mapped to specific processors but instead are assigned to available processors by the operating system.

Core Differences

  • Task Assignment: At the heart of the distinction between AMP and SMP is task assignment. In AMP, individual processors are dedicated to specific tasks. Conversely, in SMP, tasks are allocated dynamically to any available processor without such specialization.
  • Design Philosophy: AMP follows a philosophy of task specialization, giving processors dedicated roles. On the other hand, SMP operates on the principle of flexibility, with the operating system freely distributing tasks based on processor availability.
  • System Complexity: While AMP might simplify system design by defining clear roles for each processor, SMP, by its nature, requires more complex task scheduling and load balancing algorithms.

Pros and Cons of Each Approach


  • Pros: Predictable performance, optimized processor utilization, and reduced resource contention.
  • Cons: Inflexibility, potential for underutilization of processors, and more complex initial setup.


  • Pros: Flexibility in task allocation, better scalability, and potential for more evenly distributed processor load.
  • Cons: Less predictability, potential for resource contention, and increased complexity in task scheduling.

Real-world Scenarios: When to Use AMP vs. SMP

  • AMP: Best suited for systems where predictability and response time are paramount. Examples include real-time systems in industries like aerospace, where consistent performance is crucial.
  • SMP: Ideal for general-purpose computing environments, where tasks vary in nature and intensity. Most modern desktops and servers use SMP due to its dynamic load balancing capabilities.

4. Asymmetric Multiprocessing in Today’s Tech Landscape

Modern Implementations of AMP

While the pure form of AMP might seem like a relic of the past, the concept still thrives in specialized domains. For instance, in heterogeneous computing environments, where different types of processors (like CPUs and GPUs) co-exist, a form of AMP can be observed. Here, specific tasks are offloaded to the most suitable processor type, optimizing performance and energy efficiency.

The Role of AMP in Advanced Computer Architectures

In the realm of advanced computing, Asymmetric Multiprocessing plays a pivotal role, especially in systems that prioritize energy efficiency. Modern chip designs, particularly in mobile devices, often incorporate big.LITTLE architectures. In such setups, ‘big’ cores handle intensive tasks, while ‘LITTLE’ cores manage lighter, background tasks – a manifestation of AMP’s principles.

Additionally, as we push towards edge computing and the Internet of Things (IoT), there’s a renewed interest in AMP. These environments often demand a balance between power efficiency and performance, making the specialized approach of AMP a valuable asset.

In conclusion, while Asymmetric Multiprocessing might not be the go-to for general computing anymore, its principles are very much alive, guiding innovations in various tech niches. Through understanding AMP, we gain insights into the intricate dance of task allocation and processor specialization, a theme that remains ever-relevant in our rapidly evolving tech landscape.

5. Future of Multiprocessing

Predictions and Trends

As the demand for computational power grows, multiprocessor systems will undoubtedly play a more significant role in meeting these needs. Here’s a glimpse into the predicted trends:

  • Integrated Heterogeneous Systems: With the rise of AI and machine learning, we’ll likely see more systems that integrate different types of processors (CPUs, GPUs, TPUs, etc.) to optimize specific tasks. Such systems will adopt an AMP-like approach, allocating tasks to the best-suited processor.
  • Energy-Efficiency: With the increasing number of mobile devices and edge computing modules, power consumption is a growing concern. Systems will be designed to balance performance with power consumption, which could see a resurgence in AMP principles.
  • Scalability: As tasks become more complex, systems will need to be scalable. Dynamic resource allocation, a forte of SMP, will be crucial. However, task-specific optimization, characteristic of AMP, will also have its place, especially in real-time applications.

How Asymmetric Multiprocessing Might Shape Future Systems

The principles of AMP remain relevant, particularly in systems that prioritize task-specific optimization and predictability. We can anticipate:

  • Real-time Systems: With the growth of IoT and automated machinery, real-time systems will become commonplace. Asymmetric Multiprocessing, with its predictable performance, will likely be a favored approach for these applications.
  • Embedded Systems: Many embedded systems, found in everything from cars to home appliances, will benefit from the dedicated task-to-processor mapping of AMP. This ensures optimized performance with minimal resource wastage.
  • Specialized Hardware Modules: We’ll see more hardware modules designed for specific tasks, like neural processing units (NPUs) for AI tasks. These modules could operate on AMP principles, ensuring maximum efficiency.

6. Conclusion

Asymmetric Multiprocessing (AMP) offers a fascinating glimpse into the world of computer system design. Its emphasis on task-specific processor allocation has had significant implications in various computational domains. While Symmetric Multiprocessing (SMP) may dominate general-purpose computing, the principles of AMP are far from obsolete. They continue to guide innovations, especially in environments that demand predictable performance and task-specific optimizations.

As we stand on the precipice of a technological revolution, marked by AI, IoT, and a host of other advancements, understanding concepts like AMP becomes even more critical. It not only offers insights into the past but provides valuable lessons that will shape the future. So, as we delve deeper into the realm of computer design, let’s appreciate the foundations laid by approaches like AMP and anticipate the innovations they’ll inspire in the coming years.

7. Video

Learn about Asymmetric Multiprocessing