Profiling Graph Latency - 2020.2 English

Versal ACAP AI Engine Programming Environment User Guide (UG1076)

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2020.2 English

Graph latency can be defined as the time spent from receiving the first input data to producing the first output data. The following example shows how to profile graph throughput using the event API. In the example, gr is the application graph object, plio_out is the PLIO object connecting to the graph output port, and gmio_in is the GMIO object connecting to the graph input port.

event::handle handle = event::start_profiling(gmio_in, plio_out, event::io_stream_start_difference_cycles);;
long long latency_in_cycles = event::read_profiling(handle);

In the example, after graph is initialized, event::start_profiling is called to configure the AI Engine to count the clock cycles from the stream start event of the input I/O port to the stream start event of the output I/O port. The first and the second argument in event::start_profiling can be GMIO or PLIO ports, representing the input and the output I/O port respectively. In this example, gmio_in is the input I/O port and plio_out is the output I/O port. The third argument is set to event::io_stream_start_difference_cycles enumeration. The counter value simply indicates the graph latency in cycles.