performance limitations.

## Multi-Tenant environments

It is possible to run multiple TensorFlow models in parallel. For example,
`ModelServer` collates all computation graphs exposed to it (from multiple
`SavedModel`) and executes them in parallel on available executors. Running
TensorFlow in a multitenant design mixes the risks described above with the

        network.addNode(gen.nextInt(NODE_POOL_SIZE));
      }
      ArrayList<Integer> nodeList = new ArrayList<>(network.nodes());
      for (int i = 0; i < NUM_EDGES; ++i) {
        // Parallel edges are allowed, so this should always succeed.
        assertThat(
                network.addEdge(
                    getRandomElement(nodeList, gen), getRandomElement(nodeList, gen), new Object()))
            .isTrue();

import java.util.HashMap;
import java.util.Map;
import java.util.Set;
import org.jspecify.annotations.Nullable;

/**
 * An implementation of {@link NetworkConnections} for undirected networks with parallel edges.
 *
 * @author James Sexton
 * @param <N> Node parameter type
 * @param <E> Edge parameter type
 */
final class UndirectedMultiNetworkConnections<N, E>
    extends AbstractUndirectedNetworkConnections<N, E> {

        /** Language field name key. */
        public static final String LANG_FIELD_NAME = "langFieldName";
        /** Parallel processing key. */
        public static final String PARALLEL_PROCESSING = "parallel";
        /** Max content length key. */
        public static final String MAX_CONTENT_LENGTH = "maxContextLength";

        private DefaultKeys() {
        }
    }

fs.s3a.connection.maximum=8192 # Maximum number of concurrent conns
fs.s3a.fast.upload.active.blocks=2048 # Number of parallel uploads
fs.s3a.fast.upload.buffer=disk # Use disk as the buffer for uploads
fs.s3a.fast.upload=true # Turn on fast upload mode
fs.s3a.max.total.tasks=2048 # Maximum number of parallel tasks
fs.s3a.multipart.size=512M # Size of each multipart chunk
fs.s3a.multipart.threshold=512M # Size before using multipart uploads

        param("env.ANDROID_SDK_ROOT", os.androidHome)
        param("env.GRADLE_INTERNAL_REPO_URL", "%gradle.internal.repository.url%")
        if (os == Os.MACOS && arch == Arch.AMD64) {
            // Use fewer parallel forks only on Intel macOS builds, since they are not very powerful.
            param("maxParallelForks", "2")
        }
        if (os == Os.LINUX || os == Os.MACOS) {
            param("env.LC_ALL", "en_US.UTF-8")

     * <ul>
     *   <li>Returning cached results for previously executed requests</li>
     *   <li>Grouping similar requests for batch processing</li>
     *   <li>Processing requests in parallel where appropriate</li>
     * </ul>
     *
     * @param <REQ> The request type
     * @param <REP> The response type
     * @param req List of requests to process

                    "org.gradle.performance.regression.java.JavaIDEModelPerformanceTest.get IDE model for IDEA",
                    "org.gradle.performance.regression.java.JavaUpToDatePerformanceTest.up-to-date assemble (parallel true)",
                    "org.gradle.performance.regression.corefeature.TaskAvoidancePerformanceTest.help with lazy and eager tasks",
                ),
            )

            checkCleanM2AndAndroidUserHome(os)

                    ),
                functionalTests =
                    listOf(
                        TestCoverage(
                            7,
                            TestType.PARALLEL,
                            Os.LINUX,
                            JvmCategory.MAX_LTS_VERSION,
                            DEFAULT_LINUX_FUNCTIONAL_TEST_BUCKET_SIZE,
                        ),

		},
		{
			meta:           nmeta2,
			pools:          orderChangePools,
			name:           "Invalid-Orderchange-Decom",
			expectedErr:    false,
			expectedUpdate: true,
		},
	}

	t.Parallel()
	for _, testCase := range testCases {
		t.Run(testCase.name, func(t *testing.T) {
			update, err := testCase.meta.validate(testCase.pools)
			if testCase.expectedErr {
				t.Log(err)
			}