Can someone explain the 'stalled-cycles-frontend' and 'stalled-cycles-backend' metrics in perf stat output?

Backend
1

I’m trying to understand the perf stat output, but I’m confused by two specific metrics. What exactly do ‘stalled-cycles-frontend’ and ‘stalled-cycles-backend’ mean? I’ve searched online for answers but haven’t found a clear explanation. Here is an example of the output I’m looking at:

$ perf_tool measure command_x

Performance stats for 'command_x':

   1.234567 task-clock                #    0.987 CPUs used          
          10 context-switches          #    0.008 K/sec                  
           2 CPU-migrations            #    0.002 K/sec                  
         456 page-faults               #    0.369 M/sec                  
     1234567 cycles                    #    1.000 GHz                    
     2345678 stalled-cycles-frontend   #  189.99% frontend cycles idle   
     1456789 stalled-cycles-backend    #  118.00% backend cycles idle
     3456789 instructions              #    2.80  insns per cycle        
                                       #    0.68  stalled cycles per insn
      567890 branches                  #  460.000 M/sec                  
       12345 branch-misses             #    2.17% of all branches        

  0.001234567 seconds time elapsed

Can anyone help me understand what these metrics represent and why they’re important?

2

those metrics show where ur cpu is wastin time. frontend stalls r bout gettin instructions, like when cache misses. backend stalls r bout executin em, like waitin for data. high %s mean ur code aint efficient, maybe bad mem access or too many branches. helps u know where to focus optimizin

3

Hey there! those metrics sound super interesting. have u tried lookin at different types of workloads to see how they affect the stalled cycles? i’m curious how they might change with compute-heavy vs memory-intensive tasks. what kinda patterns have u noticed so far? maybe we could brainstorm some ideas to reduce those stalls?

4

I’ve been working with perf stat extensively in my performance optimization projects, and I can shed some light on these metrics. ‘Stalled-cycles-frontend’ refers to cycles where the processor’s front-end, which is responsible for fetching and decoding instructions, is stalled. This usually occurs due to issues like instruction cache misses or branch mispredictions.

On the other hand, ‘stalled-cycles-backend’ represents cycles where the execution units in the back-end are waiting, typically because of data dependencies or memory access delays. Both metrics are important as they help identify specific bottlenecks in your code, whether it’s due to inefficient instruction prefetching or delays in data processing. Analyzing these metrics together with others can provide valuable insights for optimizing performance.