CPU Usage: A Complicated Matter Instead of a Simple Fact

In the realm of embedded systems, performance optimization has become a crucial aspect, especially with the evolving landscape of modern CPUs and operating systems. A recent study conducted by Brendan Long sheds light on this topic, focusing on server utilization in embedded systems.

The traditional theory that embedded systems should only use 80% of the CPU is problematic. Modern CPUs and operating systems have evolved beyond this limitation. For instance, a 24-core AMD processor might have 12 complete CPUs that can fast switch between two contexts, allowing for more efficient use of resources.

However, performance in a system isn't as straightforward as it might seem. Measuring and predicting performance is complex due to various factors, including non-linear CPU scaling and OS resource utilization. Modern CPUs do not scale linearly as the theory suggests, running faster when lightly loaded and slower with increased load.

Moreover, the operating system plays a significant role in resource management. Even when a program is at 100% load and slow performance, modern operating systems utilize idle resources. This means a program might still be able to work in 4.7 seconds with 50% of the CPU and 70% of the memory, as the OS might be giving those resources because they would otherwise be idle.

To optimize performance, a low-priority task can be used to consume unused resources in a system, allowing a program to run while still meeting required time. This approach can be particularly useful for projects that demand high performance.

It's important to note that not all projects require performance optimization. However, for those that do, it's crucial to consider the complexities involved. Assuming a boss wants a task to be done every five seconds, a program using 80% of the CPU and 90% of the memory might still complete the task in 4.6 seconds, but could potentially complete it faster with less resource usage.

In terms of displaying system stats, there are multiple options available. While digital solutions are common, analog solutions can also be used. The idea that some overhead for expansion is necessary in embedded systems may have been reasonable in the past, but is no longer applicable in modern systems.

In conclusion, understanding system performance in embedded systems requires a holistic approach that takes into account the complexities of modern CPUs and operating systems. By optimizing resource usage and leveraging the capabilities of modern hardware, we can achieve better performance and more efficient systems.