Identifier: "ComputeWorkloadAnalysis"
DisplayName: "Compute Workload Analysis"
Description: "Detailed analysis of the compute resources of the streaming multiprocessors (SM), including the achieved instructions per clock (IPC) and the utilization of each available pipeline. Pipelines with very high utilization might limit the overall performance."
Order: 20
Sets {
  Identifier: "detailed"
}
Sets {
  Identifier: "full"
}
Header {
  Metrics {
    Label: "Executed Ipc Elapsed"
    Name: "sm__inst_executed.avg.per_cycle_elapsed"
  }
  Metrics {
    Label: "SM Busy"
    Name: "sm__instruction_throughput.avg.pct_of_peak_sustained_elapsed"
  }
  Metrics {
    Label: "Executed Ipc Active"
    Name: "sm__inst_executed.avg.per_cycle_active"
  }
  Metrics {
    Label: "Issue Slots Busy"
    Name: "sm__inst_issued.avg.pct_of_peak_sustained_elapsed"
  }
  Metrics {
    Label: "Issued Ipc Active"
    Name: "sm__inst_issued.avg.per_cycle_active"
  }
  Metrics {
    Name: ""
  }
}
Metrics {
  Metrics {
    Label: "Max. Issued Slots Busy"
    Name: "sm__inst_issued.max.pct_of_peak_sustained_elapsed"
  }
}

Body {
  DisplayName: "Pipe Utilization (Elapsed Cycles)"
  SetDefault: true
  Items {
    HorizontalContainer {
      Items {
        BarChart {
          Label: "Aggregate Pipe Utilization (% of elapsed cycles)"
          Description: "Aggregate pipeline utilization based on the number of elapsed (all) cycles in the workload. This takes the rates of different instructions executing on the pipeline into account. For an instruction requiring 4 cycles to complete execution, the counter is increased by 1 for 4 cycles. Use this to understand the overall pipeline utilization over the entire workload."
          SortKey: ByValue
          SortDirection: Descending
          ValueAxis {
            Label: "Utilization [%]"
            Range {
              Max: 100
            }
          }
          ValueAxisAlignment: ValueAxisAlignments_Both
          Metrics {
            Label: "ALU"
            Name: "sm__pipe_alu_cycles_active.avg.pct_of_peak_sustained_elapsed"
          }
          Metrics {
            Label: "FMA"
            Name: "sm__pipe_fma_cycles_active.avg.pct_of_peak_sustained_elapsed"
          }
          Metrics {
            Label: "Tensor (All)"
            Name: "sm__pipe_tensor_cycles_active.avg.pct_of_peak_sustained_elapsed"
            Options {
              Name: "sm__pipe_tensor_cycles_active_v2.avg.pct_of_peak_sustained_elapsed"
              Filter {
                MinArch: CC_89
                MaxArch: CC_89
              }
            }
          }
        }
      }
      Items {
        BarChart {
          Label: "Aggregate Pipe Utilization (% of peak instructions executed over elapsed cycles)"
          Description: "Aggregate pipeline utilization based on the number of executed instructions over elapsed (all) cycles. This does not account for any variation in instruction latencies for this pipeline. For an instruction requiring 4 cycles to complete execution, the counter is increased by 1 only. Use this to understand the composition of instructions/latencies (high-latency, low-rate instructions won't result in peak values)."
          SortKey: ByValue
          SortDirection: Descending
          ValueAxis {
            Label: "Utilization [%]"
            Range {
              Max: 100
            }
          }
          ValueAxisAlignment: ValueAxisAlignments_Both
          Metrics {
            Label: "ALU"
            Name: "sm__inst_executed_pipe_alu.avg.pct_of_peak_sustained_elapsed"
          }
          Metrics {
            Label: "FMA"
            Name: "sm__inst_executed_pipe_fma.avg.pct_of_peak_sustained_elapsed"
          }
        }
      }
    }
  }
  Items {
    HorizontalContainer {
      Items {
        BarChart {
          Label: "Physical Pipe Utilization (% of elapsed cycles)"
          Description: "Physical pipeline utilization based on the number of elapsed (all) cycles in the workload. This takes the rates of different instructions executing on the pipeline into account. For an instruction requiring 4 cycles to complete execution, the counter is increased by 1 for 4 cycles. Use this to understand the overall pipeline utilization over the entire workload."
          SortKey: ByValue
          SortDirection: Descending
          ValueAxis {
            Label: "Utilization [%]"
            Range {
              Max: 100
            }
          }
          ValueAxisAlignment: ValueAxisAlignments_Both
          Metrics {
            Label: "ALU Heavy"
            Name: "sm__pipe_aluheavy_cycles_active.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_120
              }
            }
          }
          Metrics {
            Label: "ALU Lite"
            Name: "sm__pipe_fmaheavy_subpipe_alulite_cycles_active.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_120
              }
            }
          }
          Metrics {
            Label: "Shared FMA Heavy + ALU Lite"
            Name: "sm__pipe_fmaheavy_cycles_active.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_86
              }
            }
          }
          Metrics {
            Label: "FMA Heavy"
            Name: "sm__pipe_fmaheavy_subpipe_fmaheavy_cycles_active.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_120
              }
            }
          }
          Metrics {
            Label: "FMA Lite"
            Name: "sm__pipe_fmalite_cycles_active.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_86
              }
            }
          }
          Metrics {
            Label: "FP64"
            Name: "sm__pipe_fp64_cycles_active.avg.pct_of_peak_sustained_elapsed"
          }
          Metrics {
            Label: "TC"
            Name: "sm__pipe_tc_cycles_active.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_100
                MaxArch: CC_100
              }
              Items {
                MinArch: CC_103
                MaxArch: CC_103
              }
              Items {
                MinArch: CC_110
                MaxArch: CC_110
              }
            }
          }
          Metrics {
            Label: "Tensor (DP)"
            Name: "sm__pipe_tensor_op_dmma_cycles_active.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_80
                MaxArch: CC_80
              }
              Items {
                MinArch: CC_90
                MaxArch: CC_90
              }
            }
            Options {
              Name: "sm__pipe_tensor_subpipe_dmma_cycles_active.avg.pct_of_peak_sustained_elapsed"
              Filter {
                MinArch: CC_100
                MaxArch: CC_100
              }
            }
          }
          Metrics {
            Label: "Tensor (FP)"
            Name: "sm__pipe_tensor_op_hmma_cycles_active.avg.pct_of_peak_sustained_elapsed"
            Options {
              Name: "sm__pipe_tensor_op_hmma_cycles_active_v2.avg.pct_of_peak_sustained_elapsed"
              Filter {
                MinArch: CC_89
                MaxArch: CC_89
              }
            }
            Options {
              Name: "sm__pipe_tensor_subpipe_hmma_cycles_active.avg.pct_of_peak_sustained_elapsed"
              Filter {
                MinArch: CC_100
              }
            }
          }
          Metrics {
            Label: "Tensor (INT)"
            Name: "sm__pipe_tensor_op_imma_cycles_active.avg.pct_of_peak_sustained_elapsed"
            Filter {
              MinArch: CC_75
            }
            Options {
              Name: "sm__pipe_tensor_op_imma_cycles_active_v2.avg.pct_of_peak_sustained_elapsed"
              Filter {
                MinArch: CC_89
                MaxArch: CC_89
              }
            }
            Options {
              Name: "sm__pipe_tensor_subpipe_imma_cycles_active.avg.pct_of_peak_sustained_elapsed"
              Filter {
                MinArch: CC_100
              }
            }
          }
          Metrics {
            Label: "Shared (FP16+Tensor)"
            Name: "sm__pipe_shared_cycles_active.avg.pct_of_peak_sustained_elapsed"
            Filter {
              MinArch: CC_75
              MaxArch: CC_75
            }
            Options {
              Label: "Shared (FP64+Tensor)"
              Name: "sm__pipe_shared_cycles_active.avg.pct_of_peak_sustained_elapsed"
              Filter {
                Items {
                  MinArch: CC_80
                  MaxArch: CC_80
                }
                Items {
                  MinArch: CC_90
                  MaxArch: CC_90
                }
                Items {
                  MinArch: CC_100
                  MaxArch: CC_100
                }
              }
            }
          }
          Metrics {
            Label: "TMA"
            Name: "sm__pipe_tma_cycles_active.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_90
                MaxArch: CC_90
              }
              Items {
                MinArch: CC_100
              }
            }
          }
          Metrics {
            Label: "TMEM (Tensor Memory)"
            Name: "sm__mem_tensor_cycles_active.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_100
                MaxArch: CC_100
              }
              Items {
                MinArch: CC_103
                MaxArch: CC_103
              }
              Items {
                MinArch: CC_110
                MaxArch: CC_110
              }
            }
          }
        }
      }
      Items {
        BarChart {
          Label: "Physical Pipe Utilization (% of peak instructions executed over elapsed cycles)"
          Description: "Physical pipeline utilization based on the number of executed instructions over elapsed (all) cycles. This does not account for any variation in instruction latencies for this pipeline. For an instruction requiring 4 cycles to complete execution, the counter is increased by 1 only. Use this to understand the composition of instructions/latencies (high-latency, low-rate instructions won't result in peak values)."
          SortKey: ByValue
          SortDirection: Descending
          ValueAxis {
            Label: "Utilization [%]"
            Range {
              Max: 100
            }
          }
          ValueAxisAlignment: ValueAxisAlignments_Both
          Metrics {
            Label: "ADU"
            Name: "sm__inst_executed_pipe_adu.avg.pct_of_peak_sustained_elapsed"
          }
          Metrics {
            Label: "ALU Heavy"
            Name: "sm__inst_executed_pipe_aluheavy.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_120
              }
            }
          }
          Metrics {
            Label: "ALU Lite"
            Name: "sm__inst_executed_pipe_fmaheavy_subpipe_alulite.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_120
              }
            }
          }
          Metrics {
            Label: "CBU"
            Name: "sm__inst_executed_pipe_cbu.avg.pct_of_peak_sustained_elapsed"
          }
          Metrics {
            Label: "Shared FMA Heavy"
            Name: "sm__inst_executed_pipe_fmaheavy.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_86
              }
            }
          }
          Metrics {
            Label: "FMA Heavy"
            Name: "sm__inst_executed_pipe_fmaheavy_subpipe_fmaheavy.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_120
              }
            }
          }
          Metrics {
            Label: "FMA Lite"
            Name: "sm__inst_executed_pipe_fmalite.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_86
              }
            }
          }
          Metrics {
            Label: "FP16"
            Name: "sm__inst_executed_pipe_fp16.avg.pct_of_peak_sustained_elapsed"
            Filter {
              MaxArch: CC_80
            }
            Options {
              Label: "FMA (FP16)"
              Name: "sm__inst_executed_pipe_fma_type_fp16.avg.pct_of_peak_sustained_elapsed"
              Filter {
                MinArch: CC_86
              }
            }
          }
          Metrics {
            Label: "FP64 (DMMA)"
            Name: "sm__inst_executed_pipe_fp64_op_dmma.avg.pct_of_peak_sustained_elapsed"
            Filter {
              EcSku: Platform_NotSupported
              Items {
                MinArch: CC_86
                MaxArch: CC_89
              }
              Items {
                MinArch: CC_103
                MaxArch: CC_103
              }
              Items {
                MinArch: CC_120
                MaxArch: CC_121
              }
            }
          }
          Metrics {
            Label: "FP64 (FP64)"
            Name: "sm__inst_executed_pipe_fp64_op_fp64.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_86
                MaxArch: CC_89
              }
              Items {
                MinArch: CC_103
                MaxArch: CC_103
              }
              Items {
                MinArch: CC_120
                MaxArch: CC_121
              }
            }
          }
          Metrics {
            Label: "FP64"
            Name: "sm__inst_executed_pipe_fp64.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MaxArch: CC_75
              }
              Items {
                MinArch: CC_80
                MaxArch: CC_80
              }
              Items {
                MinArch: CC_90
              }
            }
          }
          Metrics {
            Label: "LSU"
            Name: "sm__inst_executed_pipe_lsu.avg.pct_of_peak_sustained_elapsed"
          }
          Metrics {
            Label: "TC"
            Name: "sm__inst_executed_pipe_tc.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_100
                MaxArch: CC_100
              }
              Items {
                MinArch: CC_103
                MaxArch: CC_103
              }
              Items {
                MinArch: CC_110
                MaxArch: CC_110
              }
            }
          }
          Metrics {
            Label: "Tensor (DP)"
            Name: "sm__inst_executed_pipe_tensor_op_dmma.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_80
                MaxArch: CC_80
              }
              Items {
                MinArch: CC_90
                MaxArch: CC_90
              }
            }
            Options {
              Name: "sm__inst_executed_pipe_tensor_subpipe_dmma.avg.pct_of_peak_sustained_elapsed"
              Filter {
                Items {
                  MinArch: CC_100
                  MaxArch: CC_100
                }
              }
            }
          }
          Metrics {
            Label: "Tensor (Warp Group)"
            Name: "sm__inst_executed_pipe_tensor_op_gmma.avg.pct_of_peak_sustained_elapsed"
            Filter {
              MinArch: CC_90
              MaxArch: CC_90
            }
          }
          Metrics {
            Label: "Tensor (FP)"
            Name: "sm__inst_executed_pipe_tensor_op_hmma.avg.pct_of_peak_sustained_elapsed"
            Options {
              Name: "sm__inst_executed_pipe_tensor_op_hmma_v2.avg.pct_of_peak_sustained_elapsed"
              Filter {
                MinArch: CC_89
                MaxArch: CC_89
              }
            }
            Options {
              Name: "sm__inst_executed_pipe_tensor_subpipe_hmma.avg.pct_of_peak_sustained_elapsed"
              Filter {
                MinArch: CC_100
              }
            }
          }
          Metrics {
            Label: "Tensor (INT)"
            Name: "sm__inst_executed_pipe_tensor_op_imma.avg.pct_of_peak_sustained_elapsed"
            Filter {
              MinArch: CC_75
            }
            Options {
              Name: "sm__inst_executed_pipe_tensor_op_imma_v2.avg.pct_of_peak_sustained_elapsed"
              Filter {
                MinArch: CC_89
                MaxArch: CC_89
              }
            }
            Options {
              Name: "sm__inst_executed_pipe_tensor_subpipe_imma.avg.pct_of_peak_sustained_elapsed"
              Filter {
                MinArch: CC_100
              }
            }
          }
          Metrics {
            Label: "TEX"
            Name: "sm__inst_executed_pipe_tex.avg.pct_of_peak_sustained_elapsed"
          }
          Metrics {
            Label: "TMA"
            Name: "sm__inst_executed_pipe_tma.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_90
                MaxArch: CC_90
              }
              Items {
                MinArch: CC_100
              }
            }
          }
          Metrics {
            Label: "TMEM"
            Name: "sm__inst_executed_pipe_tmem.avg.pct_of_peak_sustained_elapsed"
            Filter {
              Items {
                MinArch: CC_100
                MaxArch: CC_100
              }
              Items {
                MinArch: CC_103
                MaxArch: CC_103
              }
              Items {
                MinArch: CC_110
                MaxArch: CC_110
              }
            }
          }
          Metrics {
            Label: "Uniform"
            Name: "sm__inst_executed_pipe_uniform.avg.pct_of_peak_sustained_elapsed"
            Filter {
              MinArch: CC_75
            }
          }
          Metrics {
            Label: "WorkID/CLC"
            Name: "sm__inst_executed_pipe_workid.avg.pct_of_peak_sustained_elapsed"
            Filter {
              MinArch: CC_100
            }
          }
          Metrics {
            Label: "XU"
            Name: "sm__inst_executed_pipe_xu.avg.pct_of_peak_sustained_elapsed"
          }
        }
      }
    }
  }
}

Body {
  DisplayName: "Pipe Utilization (Active Cycles)"
  Items {
    HorizontalContainer {
      Items {
        BarChart {
          Label: "Aggregate Pipe Utilization (% of active cycles)"
          Description: "Aggregate pipeline utilization based on the number of cycles the pipeline was active. This takes the rates of different instructions executing on the pipeline into account. For an instruction requiring 4 cycles to complete execution, the counter is increased by 1 for 4 cycles. Use this to understand the pipeline utilization for the time it was active."
          SortKey: ByValue
          SortDirection: Descending
          ValueAxis {
            Label: "Utilization [%]"
            Range {
              Max: 100
            }
          }
          ValueAxisAlignment: ValueAxisAlignments_Both
          Metrics {
            Label: "ALU"
            Name: "sm__pipe_alu_cycles_active.avg.pct_of_peak_sustained_active"
          }
          Metrics {
            Label: "FMA"
            Name: "sm__pipe_fma_cycles_active.avg.pct_of_peak_sustained_active"
          }
          Metrics {
            Label: "Tensor (All)"
            Name: "sm__pipe_tensor_cycles_active.avg.pct_of_peak_sustained_active"
            Options {
              Name: "sm__pipe_tensor_cycles_active_v2.avg.pct_of_peak_sustained_active"
              Filter {
                MinArch: CC_89
                MaxArch: CC_89
              }
            }
          }
        }
      }
      Items {
        BarChart {
          Label: "Aggregate Pipe Utilization (% of peak instructions executed over active cycles)"
          Description: "Aggregate pipeline utilization based on the number of executed instructions over active cycles. This does not account for any variation in instruction latencies for this pipeline. For an instruction requiring 4 cycles to complete execution, the counter is increased by 1 only. Use this to understand the composition of instructions/latencies (high-latency, low-rate instructions won't result in peak values)."
          SortKey: ByValue
          SortDirection: Descending
          ValueAxis {
            Label: "Utilization [%]"
            Range {
              Max: 100
            }
          }
          ValueAxisAlignment: ValueAxisAlignments_Both
          Metrics {
            Label: "ALU"
            Name: "sm__inst_executed_pipe_alu.avg.pct_of_peak_sustained_active"
          }
          Metrics {
            Label: "FMA"
            Name: "sm__inst_executed_pipe_fma.avg.pct_of_peak_sustained_active"
          }
        }
      }
    }
  }
  Items {
    HorizontalContainer {
      Items {
        BarChart {
          Label: "Physical Pipe Utilization (% of active cycles)"
          Description: "Physical pipeline utilization based on the number of cycles the pipeline was active. This takes the rates of different instructions executing on the pipeline into account. For an instruction requiring 4 cycles to complete execution, the counter is increased by 1 for 4 cycles. Use this to understand the pipeline utilization for the time it was active."
          SortKey: ByValue
          SortDirection: Descending
          ValueAxis {
            Label: "Utilization [%]"
            Range {
              Max: 100
            }
          }
          ValueAxisAlignment: ValueAxisAlignments_Both
          Metrics {
            Label: "ALU Heavy"
            Name: "sm__pipe_aluheavy_cycles_active.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_120
              }
            }
          }
          Metrics {
            Label: "ALU Lite"
            Name: "sm__pipe_fmaheavy_subpipe_alulite_cycles_active.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_120
              }
            }
          }
          Metrics {
            Label: "Shared FMA Heavy"
            Name: "sm__pipe_fmaheavy_cycles_active.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_86
              }
            }
          }
          Metrics {
            Label: "FMA Heavy"
            Name: "sm__pipe_fmaheavy_subpipe_fmaheavy_cycles_active.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_120
              }
            }
          }
          Metrics {
            Label: "FMA Lite"
            Name: "sm__pipe_fmalite_cycles_active.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_86
              }
            }
          }
          Metrics {
            Label: "FP64"
            Name: "sm__pipe_fp64_cycles_active.avg.pct_of_peak_sustained_active"
          }
          Metrics {
            Label: "TC"
            Name: "sm__pipe_tc_cycles_active.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_100
                MaxArch: CC_100
              }
              Items {
                MinArch: CC_103
                MaxArch: CC_103
              }
              Items {
                MinArch: CC_110
                MaxArch: CC_110
              }
            }
          }
          Metrics {
            Label: "Tensor (DP)"
            Name: "sm__pipe_tensor_op_dmma_cycles_active.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_80
                MaxArch: CC_80
              }
              Items {
                MinArch: CC_90
                MaxArch: CC_90
              }
            }
            Options {
              Name: "sm__pipe_tensor_subpipe_dmma_cycles_active.avg.pct_of_peak_sustained_active"
              Filter {
                Items {
                  MinArch: CC_100
                  MaxArch: CC_100
                }
              }
            }
          }
          Metrics {
            Label: "Tensor (FP)"
            Name: "sm__pipe_tensor_op_hmma_cycles_active.avg.pct_of_peak_sustained_active"
            Options {
              Name: "sm__pipe_tensor_op_hmma_cycles_active_v2.avg.pct_of_peak_sustained_active"
              Filter {
                MinArch: CC_89
                MaxArch: CC_89
              }
            }
            Options {
              Name: "sm__pipe_tensor_subpipe_hmma_cycles_active.avg.pct_of_peak_sustained_active"
              Filter {
                MinArch: CC_100
              }
            }
          }
          Metrics {
            Label: "Tensor (INT)"
            Name: "sm__pipe_tensor_op_imma_cycles_active.avg.pct_of_peak_sustained_active"
            Filter {
              MinArch: CC_75
            }
            Options {
              Name: "sm__pipe_tensor_op_imma_cycles_active_v2.avg.pct_of_peak_sustained_active"
              Filter {
                MinArch: CC_89
                MaxArch: CC_89
              }
            }
            Options {
              Name: "sm__pipe_tensor_subpipe_imma_cycles_active.avg.pct_of_peak_sustained_active"
              Filter {
                MinArch: CC_100
              }
            }
          }
          Metrics {
            Label: "Shared (FP16+Tensor)"
            Name: "sm__pipe_shared_cycles_active.avg.pct_of_peak_sustained_active"
            Filter {
              MinArch: CC_75
              MaxArch: CC_75
            }
            Options {
              Label: "Shared (FP64+Tensor)"
              Name: "sm__pipe_shared_cycles_active.avg.pct_of_peak_sustained_active"
              Filter {
                Items {
                  MinArch: CC_80
                  MaxArch: CC_80
                }
                Items {
                  MinArch: CC_90
                  MaxArch: CC_90
                }
                Items {
                  MinArch: CC_100
                  MaxArch: CC_100
                }
              }
            }
          }
          Metrics {
            Label: "TMA"
            Name: "sm__pipe_tma_cycles_active.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_90
                MaxArch: CC_90
              }
              Items {
                MinArch: CC_100
              }
            }
          }
          Metrics {
            Label: "TMEM (Tensor Memory)"
            Name: "sm__mem_tensor_cycles_active.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_100
                MaxArch: CC_100
              }
              Items {
                MinArch: CC_103
                MaxArch: CC_103
              }
              Items {
                MinArch: CC_110
                MaxArch: CC_110
              }
            }
          }
        }
      }
      Items {
        BarChart {
          Label: "Physical Pipe Utilization (% of peak instructions executed over active cycles)"
          Description: "Physical pipeline utilization based on the number of executed instructions over active cycles. This does not account for any variation in instruction latencies for this pipeline. For an instruction requiring 4 cycles to complete execution, the counter is increased by 1 only. Use this to understand the composition of instructions/latencies (high-latency, low-rate instructions won't result in peak values)."
          SortKey: ByValue
          SortDirection: Descending
          ValueAxis {
            Label: "Utilization [%]"
            Range {
              Max: 100
            }
          }
          ValueAxisAlignment: ValueAxisAlignments_Both
          Metrics {
            Label: "ADU"
            Name: "sm__inst_executed_pipe_adu.avg.pct_of_peak_sustained_active"
          }
          Metrics {
            Label: "ALU Heavy"
            Name: "sm__inst_executed_pipe_aluheavy.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_120
              }
            }
          }
          Metrics {
            Label: "ALU Lite"
            Name: "sm__inst_executed_pipe_fmaheavy_subpipe_alulite.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_120
              }
            }
          }
          Metrics {
            Label: "CBU"
            Name: "sm__inst_executed_pipe_cbu.avg.pct_of_peak_sustained_active"
          }
          Metrics {
            Label: "Shared FMA Heavy + ALU Lite"
            Name: "sm__inst_executed_pipe_fmaheavy.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_86
              }
            }
          }
          Metrics {
            Label: "FMA Heavy"
            Name: "sm__inst_executed_pipe_fmaheavy_subpipe_fmaheavy.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_120
              }
            }
          }
          Metrics {
            Label: "FMA Lite"
            Name: "sm__inst_executed_pipe_fmalite.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_86
              }
            }
          }
          Metrics {
            Label: "FP16"
            Name: "sm__inst_executed_pipe_fp16.avg.pct_of_peak_sustained_active"
            Filter {
              MaxArch: CC_80
            }
            Options {
              Label: "FMA (FP16)"
              Name: "sm__inst_executed_pipe_fma_type_fp16.avg.pct_of_peak_sustained_active"
              Filter {
                MinArch: CC_86
              }
            }
          }
          Metrics {
            Label: "FP64 (DMMA)"
            Name: "sm__inst_executed_pipe_fp64_op_dmma.avg.pct_of_peak_sustained_active"
            Filter {
              EcSku: Platform_NotSupported
              Items {
                MinArch: CC_86
                MaxArch: CC_89
              }
              Items {
                MinArch: CC_103
                MaxArch: CC_103
              }
              Items {
                MinArch: CC_120
                MaxArch: CC_121
              }
            }
          }
          Metrics {
            Label: "FP64 (FP64)"
            Name: "sm__inst_executed_pipe_fp64_op_fp64.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_86
                MaxArch: CC_89
              }
              Items {
                MinArch: CC_103
                MaxArch: CC_103
              }
              Items {
                MinArch: CC_120
                MaxArch: CC_121
              }
            }
          }
          Metrics {
            Label: "FP64"
            Name: "sm__inst_executed_pipe_fp64.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MaxArch: CC_75
              }
              Items {
                MinArch: CC_80
                MaxArch: CC_80
              }
              Items {
                MinArch: CC_90
              }
            }
          }
          Metrics {
            Label: "LSU"
            Name: "sm__inst_executed_pipe_lsu.avg.pct_of_peak_sustained_active"
          }
          Metrics {
            Label: "TC"
            Name: "sm__inst_executed_pipe_tc.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_100
                MaxArch: CC_100
              }
              Items {
                MinArch: CC_103
                MaxArch: CC_103
              }
              Items {
                MinArch: CC_110
                MaxArch: CC_110
              }
            }
          }
          Metrics {
            Label: "Tensor (DP)"
            Name: "sm__inst_executed_pipe_tensor_op_dmma.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_80
                MaxArch: CC_80
              }
              Items {
                MinArch: CC_90
                MaxArch: CC_90
              }
            }
            Options {
              Name: "sm__inst_executed_pipe_tensor_subpipe_dmma.avg.pct_of_peak_sustained_active"
              Filter {
                Items {
                  MinArch: CC_100
                  MaxArch: CC_100
                }
              }
            }
          }
          Metrics {
            Label: "Tensor (Warp Group)"
            Name: "sm__inst_executed_pipe_tensor_op_gmma.avg.pct_of_peak_sustained_active"
            Filter {
              MinArch: CC_90
              MaxArch: CC_90
            }
          }
          Metrics {
            Label: "Tensor (FP)"
            Name: "sm__inst_executed_pipe_tensor_op_hmma.avg.pct_of_peak_sustained_active"
            Options {
              Name: "sm__inst_executed_pipe_tensor_op_hmma_v2.avg.pct_of_peak_sustained_active"
              Filter {
                MinArch: CC_89
                MaxArch: CC_89
              }
            }
            Options {
              Name: "sm__inst_executed_pipe_tensor_subpipe_hmma.avg.pct_of_peak_sustained_active"
              Filter {
                MinArch: CC_100
              }
            }
          }
          Metrics {
            Label: "Tensor (INT)"
            Name: "sm__inst_executed_pipe_tensor_op_imma.avg.pct_of_peak_sustained_active"
            Filter {
              MinArch: CC_75
            }
            Options {
              Name: "sm__inst_executed_pipe_tensor_op_imma_v2.avg.pct_of_peak_sustained_active"
              Filter {
                MinArch: CC_89
                MaxArch: CC_89
              }
            }
            Options {
              Name: "sm__inst_executed_pipe_tensor_subpipe_imma.avg.pct_of_peak_sustained_active"
              Filter {
                MinArch: CC_100
              }
            }
          }
          Metrics {
            Label: "TEX"
            Name: "sm__inst_executed_pipe_tex.avg.pct_of_peak_sustained_active"
          }
          Metrics {
            Label: "TMA"
            Name: "sm__inst_executed_pipe_tma.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_90
                MaxArch: CC_90
              }
              Items {
                MinArch: CC_100
              }
            }
          }
          Metrics {
            Label: "TMEM"
            Name: "sm__inst_executed_pipe_tmem.avg.pct_of_peak_sustained_active"
            Filter {
              Items {
                MinArch: CC_100
                MaxArch: CC_100
              }
              Items {
                MinArch: CC_103
                MaxArch: CC_103
              }
              Items {
                MinArch: CC_110
                MaxArch: CC_110
              }
            }
          }
          Metrics {
            Label: "Uniform"
            Name: "sm__inst_executed_pipe_uniform.avg.pct_of_peak_sustained_active"
            Filter {
              MinArch: CC_75
            }
          }
          Metrics {
            Label: "WorkID/CLC"
            Name: "sm__inst_executed_pipe_workid.avg.pct_of_peak_sustained_active"
            Filter {
              MinArch: CC_100
            }
          }
          Metrics {
            Label: "XU"
            Name: "sm__inst_executed_pipe_xu.avg.pct_of_peak_sustained_active"
          }
        }
      }
    }
  }
}
