atomic.AddInt64(&lat, latency)
				})
				spent := time.Since(t)
				if spent > 0 && n > 0 {
					// Since we are benchmarking n parallel servers we need to multiply by n.
					// This will give an estimate of the total ops/s.
					latency := float64(atomic.LoadInt64(&lat)) / float64(time.Millisecond)
					b.ReportMetric(float64(n)*float64(ops)/spent.Seconds(), "vops/s")
					b.ReportMetric(latency/float64(ops), "ms/op")

		Kind:       KindFloat64,
		Cumulative: true,
	},
	{
		Name: "/cpu/classes/user:cpu-seconds",
		Description: "Estimated total CPU time spent running user Go code. This may " +
			"also include some small amount of time spent in the Go runtime. " +
			"This metric is an overestimate, and not directly comparable to " +
			"system CPU time measurements. Compare only with other /cpu/classes " +
			"metrics.",

		last  *_Plink
		first *_Plink
		pid   uint32
		what  uint32
	}
	cyclefreq uint64 // cycle clock frequency if there is one, 0 otherwise
	kcycles   int64  // cycles spent in kernel
	pcycles   int64  // cycles spent in process (kernel + user)
	pid       uint32 // might as well put the pid here
	clock     uint32
	// top of stack is here
}

const (
	_NSIG   = 14  // number of signals in sigtable array

        normalizedOutput
            .replaceAll(/Received \d+ file system events .*\n/, '')
            .replaceAll(/Spent \d+ ms processing file system events since last build\n/, '')
            .replaceAll(/Spent \d+ ms registering watches for file system events\n/, '')
            .replaceAll(/Virtual file system .*\n/, '')
    }

package main

// Make many C-to-Go callback while collecting a CPU profile.
//
// This is a regression test for issue 50936.

/*
#include <unistd.h>

void goCallbackPprof();

static void callGo() {
	// Spent >20us in C so this thread is eligible for sysmon to retake its
	// P.
	usleep(50);
	goCallbackPprof();
}
*/
import "C"

import (
	"fmt"
	"os"
	"runtime"
	"runtime/pprof"
	"time"
)

		Estimated total CPU time goroutines spent performing GC
		tasks to assist the GC and prevent it from falling behind the
		application. This metric is an overestimate, and not directly
		comparable to system CPU time measurements. Compare only with
		other /cpu/classes metrics.

	/cpu/classes/gc/mark/dedicated:cpu-seconds
		Estimated total CPU time spent performing GC tasks on processors

message XlaJitCompilationActivity {
  string cluster_name = 1;

  // The number of time this cluster has been compiled.
  int32 compile_count = 2;

  // Microseconds spent in the individual compilation being reported.
  int64 compile_time_us = 3;

  // Total microseconds spent in (re-)compiling this cluster so far.
  int64 cumulative_compile_time_us = 4;

  // Whether a persistent compilation cache entry was used.

{{end}}
</table>

<h3 id="ranges">Special ranges</h3>

The table below describes how much of the traced period each goroutine spent in
certain special time ranges.
If a goroutine has spent no time in any special time ranges, it is excluded from
the table.
For example, how much time it spent helping the GC. Note that these times do
overlap with the times from the first table.

{{end}}
</table>

<h3 id="ranges">Special ranges</h3>

The table below describes how much of the traced period each goroutine spent in
certain special time ranges.
If a goroutine has spent no time in any special time ranges, it is excluded from
the table.
For example, how much time it spent helping the GC. Note that these times do
overlap with the times from the first table.

			expectedValue: `
        # HELP apiserver_authentication_jwt_authenticator_latency_seconds [ALPHA] Latency of jwt authentication operations in seconds. This is the time spent authenticating a token for cache miss only (i.e. when the token is not found in the cache).
        # TYPE apiserver_authentication_jwt_authenticator_latency_seconds histogram