How can I distinguish between high- and low-performance cores/threads in C++?

How to distinguish between high- and low-performance cores/threads in C++?

Please understand that “thread” is an abstraction of the hardware’s capabilities and that something beyond your control (the OS, the kernel’s scheduler) is responsible for creating and managing this abstraction. “Importance” and performance hints are part of that abstraction (typically presented in the form of a thread priority).

Any attempt to break the “thread” abstraction (e.g. determine if the core is a low-performance or high-performance core) is misguided. E.g. OS could change your thread to a low performance core immediately after you find out that you were running on a high performance core, leading you to assume that you’re on a high performance core when you are not.

Even pinning your thread to a specific core (in the hope that it’ll always be using a high-performance core) can/will backfire (cause you to get less work done because you’ve prevented yourself from using a “faster than nothing” low-performance core when high-performance core/s are busy doing other work).

The biggest problem is that C++ creates a worse abstraction (std::thread) on top of the “likely better” abstraction provided by the OS. Specifically, there’s no way to set, modify or obtain the thread priority using std::thread; so you’re left without any control over the “performance hints” that are necessary (for the OS, scheduler) to make good “load vs. performance vs. power management” decisions.

When talking about multi-threading, it often seems like threads are treated as equal

Often people think we’re still using time-sharing systems from the 1960s. Stop listening to these fools. Modern systems do not allow CPU time to be wasted on unimportant work while more important work waits. Effective use of thread priorities is a fundamental performance requirement. Everything else (“load vs. performance vs. power management” decisions) is, by necessity, beyond your control (on the other side of the “thread” abstraction you’re using).

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