return new ExpiringMemoizingSupplier<>(delegate, toNanosSaturated(duration));
  }

  @VisibleForTesting
  @SuppressWarnings("GoodTime") // lots of violations
  static final class ExpiringMemoizingSupplier<T extends @Nullable Object>
      implements Supplier<T>, Serializable {
    private transient Object lock = new Object();

    final Supplier<T> delegate;

  /**
   * This is a less carefully-controlled version of {@link #testRemovalNotification_clear} - this is
   * a black-box test that tries to create lots of different thread-interleavings, and asserts that
   * each computation is affected by a call to {@code clear()} (and therefore gets passed to the

  /**
   * This is a less carefully-controlled version of {@link #testRemovalNotification_clear} - this is
   * a black-box test that tries to create lots of different thread-interleavings, and asserts that
   * each computation is affected by a call to {@code clear()} (and therefore gets passed to the

        // We only ever register ArrayReferences with the queue so this is always safe.
        ArrayReference<? extends L> arrayRef = (ArrayReference<? extends L>) ref;
        // Try to clear out the array slot, n.b. if we fail that is fine, in either case the
        // arrayRef will be out of the array after this step.
        locks.compareAndSet(arrayRef.index, arrayRef, null);
      }
    }

    @Override

    //     fgha[c]|[b]de -> fgha[b]|[c]de. Because these two blocks are the same size, we are done.
    // The Dolphin algorithm is attractive because it does the fewest array reads and writes: each
    // 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

    if (expected.equals(in)) {
      assertSame(in, out);
    } else {
      assertEquals(expected, out);
    }
  }

  // Test collapse() a little differently than the rest, as we really want to
  // cover lots of different configurations of input text
  public void testCollapse() {
    // collapsing groups of '-' into '_' or '-'
    doTestCollapse("-", "_");
    doTestCollapse("x-", "x_");
    doTestCollapse("-x", "_x");

     * determined experimentally to match our desired probability of false positives.
     */
    // NB: yes, this is surprisingly high, but that's what the experiments said was necessary
    // Raising this number slows the worst-case contains behavior, speeds up hashFloodingDetected,
    // and reduces the false-positive probability.
    static final int MAX_RUN_MULTIPLIER = 13;

    /**

    if (expected.equals(in)) {
      assertSame(in, out);
    } else {
      assertEquals(expected, out);
    }
  }

  // Test collapse() a little differently than the rest, as we really want to
  // cover lots of different configurations of input text
  public void testCollapse() {
    // collapsing groups of '-' into '_' or '-'
    doTestCollapse("-", "_");
    doTestCollapse("x-", "x_");
    doTestCollapse("-x", "_x");

* **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.
* **Machine Learning**: it normally requires lots of "matrix" and "vector" multiplications. Think of a huge spreadsheet with numbers and multiplying all of them together at the same time.

    assertThat(hpackReader!!.headerCount).isEqualTo(1)
  }

  /** Header table backing array is initially 8 long, let's ensure it grows.  */
  @Test
  fun dynamicallyGrowsBeyond64Entries() {
    // Lots of headers need more room!
    hpackReader = Hpack.Reader(bytesIn, 16384, 4096)
    bytesIn.writeByte(0x3F) // Dynamic table size update (size = 16384).
    bytesIn.writeByte(0xE1)
    bytesIn.writeByte(0x7F)