What do stalled-cycles-frontend and stalled-cycles-backend represent in perf stat outputs?

Frontend and Backend Development
1

I’m trying to understand the significance of the stalled-cycles-frontend and stalled-cycles-backend figures produced by the perf stat tool.

Despite looking through several sources, I still find it challenging to grasp what these two metrics indicate regarding CPU performance. Specifically, I am curious about how these results relate to delays in the execution pipeline and whether they point to issues in the frontend or backend processing of instructions. Could someone provide a detailed explanation or examples to illustrate their meanings?

Here is an alternative sample output:

$ sudo perf analyze my_command

Performance metrics for 'my_command':

      0.700745 runtime-clock              #    0.800 CPUs active
             0 context-switches          #    0.000 per sec
           300 minor page faults         #    0.500 per sec
        800000 total cycles
        100000 idle-frontend cycles   #  130.00% of cycles delayed at frontend
         50000 idle-backend cycles   #   90.00% of cycles delayed at backend
        100000 executed instructions   #   0.80 instructions per cycle
        150000 branch operations
       12000 branch errors             #   7.20% error rate

0.001234 seconds elapsed

Any additional insights or practical interpretations of these statistics would be greatly appreciated.

2

hey, im wonderin if high frontend stalls could signal branch mispred or cache misfires while backend stalls might point to resource tention? any1 try tweaking prefetchers to see changes? curious how u all tackle these issues!

3

hey, in my opinon stalled-cycles-frontend seems like the phase where decoding/fetch gets held up. stalled-cycles-backend often points to delays in execution or mem access. has any1 seen these stats correlating directly with specific code segments?

4

hey, im not an expert but these numbers can zero in on pipeline hiccups. if your frontend stalls are high, you might be dealing with fetch/decode delays. backend issues usually point to memory or exec waits. might help to tweak code paths and check cache performance.

5

Stalled-cycles-frontend often represent delays resulting from the instruction fetch and decode phases, while stalled-cycles-backend generally indicate issues in the execution phase such as data dependencies, memory latency, or even contention on execution units. In my experience, these metrics provide a useful starting point when profiling performance issues. For instance, a high proportion of stalled-cycles-frontend may suggest that the instruction feeder isn’t able to supply operations quickly enough due to cache misses or branch mispredictions. Conversely, elevated stalled-cycles-backend can point to delays in actual computation or memory access, guiding further investigation into specific code paths or system limitations.

6

i reckon that stalled-cycles-frontend shows fetching/decoding delays while stalled-cycles-backend signals compute or mem access lags. try to corelate these with specific code areas to track potential bottlenecks.