Spin and Overhead Time

Overhead Time

Overhead time is the time the system takes to deliver a shared resource from a releasing owner to an acquiring owner. Ideally, the Overhead time should be close to zero because it means the resource is not being wasted through idleness. However, not all CPU time in a parallel application may be spent on doing real payload work. In cases when a parallel runtime (for example, Intel® Threading Building Blocks, Intel® Cilk™, OpenMP*) is used inefficiently, a significant portion of time may be spent inside the parallel runtime wasting CPU time at high concurrency levels. For example, if you increase the number of threads performing some fixed load of work in parallel, each thread gets less work and the overhead, as a relative measure, will get larger. It is a basic application of Amdahl's Law.

To detect this wasted CPU time, Intel® VTune™ Amplifier analyzes the call stack at the point of interest and computes the Overhead time performance metric. VTune Amplifier classifies the stack layers into user, system, and overhead layers and attributes the CPU time spent in system functions called by overhead functions to the overhead functions.

Spin Time

Spin time is the Wait time during which the CPU is busy. This often occurs when a synchronization API causes the CPU to poll while the software thread is waiting. Some Spin time may be preferable to the alternative of increased thread context switches. Too much Spin time, however, can reflect lost opportunity for productive work.

Overhead and Spin Time

VTune Amplifier provides the combined Overhead and Spin Time metric in the grid and Timeline view of the Hotspots by CPU Usage, Hotspots by Thread Concurrency, and Hotspots viewpoints. This metric represents the sum of the Overhead and Spin time values calculated as CPU Time where Call Site Type is Overhead + CPU Time where Call Site Type is Synchronization. To view the Overhead and Spin time values separately, expand the column by clicking the symbol.

Possible Issues

A significant portion of CPU time is spent in synchronization or threading overhead. Consider increasing task granularity or the scope of data synchronization.