* offering expected O(n + k log k) performance (worst case O(n log k)) for n calls to {@link
 * #offer} and a call to {@link #topK}, with O(k) memory. In comparison, quickselect has the same
 * asymptotics but requires O(n) memory, and a {@code PriorityQueue} implementation takes O(n log
 * k). In benchmarks, this implementation performs at least as well as either implementation, and

### Arbeitsspeicher pro Prozess { #memory-per-process }

Wenn das Programm nun Dinge in den Arbeitsspeicher lädt, zum Beispiel ein Modell für maschinelles Lernen in einer Variablen oder den Inhalt einer großen Datei in einer Variablen, verbraucht das alles **einen Teil des Arbeitsspeichers (RAM – Random Access Memory)** des Servers.

    `tf.raw_ops.DataFormatDimMap` which can cause uninitialized memory access,
    read outside bounds of arrays, data corruption and segmentation faults
    ([CVE-2020-26267](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-26267))
*   Fixes a crash caused by writing to read only memory region
    ([CVE-2020-26268](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-26268))

   * 2^n}, its memory usage is only {@code O(n)}. When the power set is constructed, the input set
   * is merely copied. Only as the power set is iterated are the individual subsets created, and
   * these subsets themselves occupy only a small constant amount of memory.
   *
   * @param set the set of elements to construct a power set from

            final MessageDigest md4 = Crypto.getMD4();
            md4.update(Strings.getUNIBytes(tempStr));
            return md4.digest();
        } finally {
            // Clear the temporary string from memory (best effort)
            if (tempStr != null) {
                tempStr.intern();
            }
        }
    }

    /**
     * Generates the NTOWFv1 hash for the given password.
     *

      description: If compiling from source
  - type: input
    id: Cuda
    attributes:
      label: CUDA/cuDNN version
  - type: input
    id: Gpu
    attributes:
      label: GPU model and memory
      description: If compiling from source
  - type: textarea
    id: what-happened
    attributes:
      label: Current behavior?
      description: Also tell us, what did you expect to happen?

 * }
 * public void testFooLeak() {
 *   GcFinalization.awaitClear(fooWeakRef());
 * }
 * }
 *
 * <p>This class cannot currently be used to test soft references, since this class does not try to
 * create the memory pressure required to cause soft references to be cleared.
 *
 * <p>This class only provides testing utilities. It is not designed for direct use in production or
 * for benchmarking.
 *
 * @author mike nonemacher

        try {
            toolchainsWriter.write(stringWriter, null, toolchains);
        } catch (IOException e) {
            throw new IllegalStateException("Failed to serialize toolchains to memory", e);
        }

        String serializedToolchains = stringWriter.toString();

        RegexBasedInterpolator interpolator = new RegexBasedInterpolator();

        try {

   *       and virtual memory, this is not a problem - because it is mapped read-only, the kernel
   *       can always page it to disk "for free". However, on systems where killing processes
   *       happens all the time in normal conditions (i.e., android) the OS must make a tradeoff

   * map of public suffixes. The encoded trie string may be broken into multiple chunks to avoid the
   * 64k limit on string literal size. In-memory strings can be much larger (2G).
   */
  static ImmutableMap<String, PublicSuffixType> parseTrie(CharSequence... encodedChunks) {
    String encoded = DIRECT_JOINER.join(encodedChunks);
    return parseFullString(encoded);