myc := make(chan int, 128)
	myclose := make(chan bool)
	for p := 0; p < procs; p++ {
		go func() {
			// Producer: sends to myc.
			foo := 0
			// Intended to not fire during benchmarking.
			mytimer := time.After(time.Hour)
			for atomic.AddInt32(&N, -1) >= 0 {
				for g := 0; g < CallsPerSched; g++ {
					// Model some local work.
					for i := 0; i < 100; i++ {
						foo *= 2

    // array slot is read and written exactly once. However, it can have very poor memory locality:
    // benchmarking shows it can take 7 times longer than the other two in some cases. The other two
    // do n swaps, minus a delta (0 or 2 for Reversal, gcd(d, n) for Successive), so that's about
    // twice as many reads and writes. But benchmarking shows that they usually perform better than

  private static final int DEFAULT_INITIAL_CAPACITY = 16;
  private static final int DEFAULT_CONCURRENCY_LEVEL = 4;

  static final int UNSET_INT = -1;

  // TODO(kevinb): dispense with this after benchmarking
  boolean useCustomMap;

  int initialCapacity = UNSET_INT;
  int concurrencyLevel = UNSET_INT;

  @CheckForNull Strength keyStrength;
  @CheckForNull Strength valueStrength;

  private static final int DEFAULT_INITIAL_CAPACITY = 16;
  private static final int DEFAULT_CONCURRENCY_LEVEL = 4;

  static final int UNSET_INT = -1;

  // TODO(kevinb): dispense with this after benchmarking
  boolean useCustomMap;

  int initialCapacity = UNSET_INT;
  int concurrencyLevel = UNSET_INT;

  @CheckForNull Strength keyStrength;
  @CheckForNull Strength valueStrength;

// point to same memory region, we can use a faster version of copy using only MVC here.
// In the following implementation, we have three copy loops, each copying a word, 4 words, and
// 32 words at a time.  Via benchmarking, this implementation is faster than calling runtime·memmove.
copySetup:
	ADD R12, R6
	ADD R12, R8

	CMPBGE R5, $4, mediumLoop

smallLoop:  // does a loop unrolling to copy word when n < 4

				stop := applyGCLoad(b)
				runOne(b)
				// Make sure to stop the timer before we wait! The load created above
				// is very heavy-weight and not easy to stop, so we could end up
				// confusing the benchmarking framework for small b.N.
				b.StopTimer()
				stop()
			})
		}
	}

	// Measure the cost of counting goroutines
	b.Run("small-nil", run(func() bool {
		GoroutineProfile(nil)
		return true

    // array slot is read and written exactly once. However, it can have very poor memory locality:
    // benchmarking shows it can take 7 times longer than the other two in some cases. The other two
    // do n swaps, minus a delta (0 or 2 for Reversal, gcd(d, n) for Successive), so that's about
    // twice as many reads and writes. But benchmarking shows that they usually perform better than

   *
   * <p><b>Performance note:</b> {@link ArrayList} and {@link java.util.ArrayDeque} consistently
   * outperform {@code LinkedList} except in certain rare and specific situations. Unless you have
   * spent a lot of time benchmarking your specific needs, use one of those instead.
   *
   * <p><b>Note:</b> this method is now unnecessary and should be treated as deprecated. Instead,

        int stride = 8;
        int minLength = Math.min(left.length, right.length);
        int strideLimit = minLength & ~(stride - 1);
        int i;

        /*
         * Compare 8 bytes at a time. Benchmarking on x86 shows a stride of 8 bytes is no slower
         * than 4 bytes even on 32-bit. On the other hand, it is substantially faster on 64-bit.
         */
        for (i = 0; i < strideLimit; i += stride) {

It was found that the directory staging committer was the fastest among the three, S3A connector should be configured with the following parameters for optimal results:

```