Par exemple :

* Traitements d'**audio** et d'**images**.
* La **vision par ordinateur** : une image est composée de millions de pixels, chaque pixel ayant 3 valeurs / couleurs, les traiter tous va nécessiter d'effectuer des traitements sur chaque pixel, et de préférence tous en même temps.

---

Common examples of CPU bound operations are things that require complex math processing.

For example:

* **Audio** or **image processing**.
* **Computer vision**: an image is composed of millions of pixels, each pixel has 3 values / colors, processing that normally requires computing something on those pixels, all at the same time.

    ImmutableMap<Service, Long> startupTimes = serviceManager.startupTimes();
    assertThat(startupTimes).hasSize(2);
    assertThat(startupTimes.get(a)).isAtLeast(150);
    // Service b startup takes at least 353 millis, but starting the timer is delayed by at least
    // 150 milliseconds. so in a perfect world the timing would be 353-150=203ms, but since either

 * StatsAccumulator#add} and {@link StatsAccumulator#addAll} methods. For tests of the {@link
 * StatsAccumulator#snapshot} method which returns {@link Stats} instances, see {@link StatsTest}.
 *
 * @author Pete Gillin
 */
@NullUnmarked
public class StatsAccumulatorTest extends TestCase {

  private StatsAccumulator emptyAccumulator;
  private StatsAccumulator emptyAccumulatorByAddAllEmptyIterable;

  }

  /**
   * Returns the service load times. This value will only return startup times for services that
   * have finished starting.
   *
   * @return Map of services and their corresponding startup time in millis, the map entries will be
   *     ordered by startup time.
   */
  public ImmutableMap<Service, Long> startupTimes() {
    return state.startupTimes();
  }

  /**

  }

  /**
   * Returns the service load times. This value will only return startup times for services that
   * have finished starting.
   *
   * @return Map of services and their corresponding startup time in millis, the map entries will be
   *     ordered by startup time.
   */
  public ImmutableMap<Service, Long> startupTimes() {
    return state.startupTimes();
  }

  /**

---

Typische Beispiele für CPU-lastige Vorgänge sind Dinge, die komplexe mathematische Berechnungen erfordern.

Zum Beispiel:

* **Audio-** oder **Bildbearbeitung**.
* **Computer Vision**: Ein Bild besteht aus Millionen von Pixeln, jedes Pixel hat 3 Werte / Farben, die Verarbeitung erfordert normalerweise, Berechnungen mit diesen Pixeln durchzuführen, alles zur gleichen Zeit.

 * calculate <i>only</i> the mean.
 *
 * <p><b>Java 8+ users:</b> If you are not using any of the variance statistics, you may wish to use
 * built-in JDK libraries instead of this class.
 *
 * @author Pete Gillin
 * @author Kevin Bourrillion
 * @since 20.0
 */
@J2ktIncompatible
@GwtIncompatible
public final class Stats implements Serializable {

  private final long count;
  private final double mean;

 * either form}), only the overhead is required. The number of object allocations is independent of
 * N in both cases.
 *
 * @author Pete Gillin
 * @since 20.0
 */
@J2ktIncompatible
@GwtIncompatible
public final class Quantiles {
  /**
   * Constructor for a type that is not meant to be instantiated.
   *

          "intervalFactor": 1,
          "legendFormat": "{{bucket,range,operation}}",
          "refId": "A",
          "step": 300
        }
      ],
      "title": "Replication Latency (millis)",
      "type": "bargauge"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${DS_PROMETHEUS}"
      },
      "fieldConfig": {
        "defaults": {