Low Count Rate Due to CPU Overload

A low countrate may occur due to CPU overload, especially during computationally intensive measurements.

Each initialized measurement runs on its own thread, but only a few of our API measurements, such as HistogramLogBins , can utilize multiple cores. If a single measurement consumes excessive CPU time, the Time Tagger's hardware buffer can fill up, leading to an overflow event and data loss.

Example Scenario

Consider a time-resolved imaging experiment with 500 pixels × 500 pixels × 1000 bins per histogram, resulting in approximately 1 GByte of data. Modern high-performance computers (e.g., processors with DDR5 RAM) have a CPU-to-RAM bandwidth of about 38.4 GByte/s.

Under ideal conditions, assuming no other CPU activity and the data being transferred to an independent memory channel, copying 1 GByte of data theoretically takes at least 26 ms.

To retrieve the data, you would use the getData() method. This method:

• Locks the data pipeline,
• Copies the data to the user, and
• Unlocks the pipeline for further processing.

If getData() is called too frequently while handling large data volumes, it keeps the pipeline locked for longer periods. This reduces the available CPU time to process incoming data, ultimately causing buffer overflows and data loss.

Key Takeaway

To avoid CPU overload and ensure smooth data processing:

• Minimize the frequency of calls to getData() for large data sets.
• Optimize the number of parallel measurements to match your CPU's capabilities.
• Use modern high-bandwidth systems (e.g., DDR5 RAM) for large-scale experiments.