Add configurable resource distribution at host level (#355)

10 files changed, 1067 insertions, 1 deletions

diff --git a/opendc-experiments/opendc-experiments-base/src/test/kotlin/org/opendc/experiments/base/DistributionPoliciesTest.kt b/opendc-experiments/opendc-experiments-base/src/test/kotlin/org/opendc/experiments/base/DistributionPoliciesTest.kt
new file mode 100644
index 00000000..68111bc1
--- /dev/null
+++ b/opendc-experiments/opendc-experiments-base/src/test/kotlin/org/opendc/experiments/base/DistributionPoliciesTest.kt
@@ -0,0 +1,782 @@
+/*
+ * Copyright (c) 2025 AtLarge Research
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+
+package org.opendc.experiments.base
+
+import org.junit.jupiter.api.Assertions.assertEquals
+import org.junit.jupiter.api.Test
+import org.junit.jupiter.api.assertAll
+import org.opendc.compute.workload.Task
+import org.opendc.simulator.compute.workload.trace.TraceFragment
+import org.opendc.simulator.engine.graph.distributionPolicies.FlowDistributorFactory.DistributionPolicy
+import java.util.ArrayList
+
+class DistributionPoliciesTest {
+    /**
+     * This test verifies that the DistributionPolicies are correctly loaded from the configuration.
+     */
+    @Test
+    fun distributionPoliciesTest() {
+        val maxMinFairnessGpuTopology = createTopology("DistributionPolicies/maxMinFairness/multi_gpu_host.json")
+        val equalShareGpuTopology = createTopology("DistributionPolicies/equalShare/dual_core_gpu_host.json")
+        val fixedShareGpuTopology = createTopology("DistributionPolicies/fixedShare/multi_gpu_host.json")
+        val bestEffortGpuTopology = createTopology("DistributionPolicies/bestEffort/multi_gpu_host.json")
+
+        assertAll(
+            {
+                assertEquals(
+                    DistributionPolicy.MAX_MIN_FAIRNESS,
+                    maxMinFairnessGpuTopology[0].hostSpecs[0].model.gpuDistributionStrategy,
+                    "MaxMinFairnessDistributionPolicy should be used",
+                )
+            },
+            {
+                assertEquals(
+                    DistributionPolicy.EQUAL_SHARE,
+                    equalShareGpuTopology[0].hostSpecs[0].model.gpuDistributionStrategy,
+                    "EqualShareDistributionPolicy should be used",
+                )
+            },
+            {
+                assertEquals(
+                    DistributionPolicy.FIXED_SHARE,
+                    fixedShareGpuTopology[0].hostSpecs[0].model.gpuDistributionStrategy,
+                    "FixedShareDistributionPolicy should be used",
+                )
+            },
+            {
+                assertEquals(
+                    0.5,
+                    fixedShareGpuTopology[0].hostSpecs[0].model.gpuDistributionStrategy.getProperty("shareRatio"),
+                    "FixedShareDistributionPolicy should have a share ratio of 0.5",
+                )
+            },
+            {
+                assertEquals(
+                    DistributionPolicy.BEST_EFFORT,
+                    bestEffortGpuTopology[0].hostSpecs[0].model.gpuDistributionStrategy,
+                    "BestEffortDistributionPolicy should be used",
+                )
+            },
+        )
+    }
+
+    /**
+     * This test verifies that the [EqualShareDistributionPolicy] correctly distributes supply according to the number of suppliers.
+     * The supply is divided equally among all suppliers.
+     */
+    @Test
+    fun equalShareDistributionPolicyTest1() {
+        val workload: ArrayList<Task> =
+            arrayListOf(
+                createTestTask(
+                    name = "0",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 2000.0, 1),
+                        ),
+                ),
+            )
+
+        val singleGpuTopology = createTopology("DistributionPolicies/equalShare/dual_core_gpu_host.json")
+        val doubleGpuTopology = createTopology("DistributionPolicies/equalShare/multi_gpu_host.json")
+
+        val singleMonitor = runTest(singleGpuTopology, workload)
+        val doubleMonitor = runTest(doubleGpuTopology, workload)
+
+        assertAll(
+            // single gpu
+            { assertEquals(2000.0, singleMonitor.taskGpuDemands["0"]?.get(1), "Single GPU demand in task \"0\" should be 2000.0") },
+            { assertEquals(4000.0, singleMonitor.taskGpuSupplied["0"]?.get(1), "Single GPU demand in task \"0\" should be 2000.0") },
+            {
+                assertEquals(
+                    4000.0,
+                    singleMonitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(0),
+                    "Single GPU demand at host \"DualGpuHost\" should be 2000.0",
+                )
+            },
+            {
+                assertEquals(
+                    4000.0,
+                    singleMonitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(0),
+                    "Single GPU supply at host \"DualGpuHost\" should be 2000.0",
+                )
+            },
+            // double gpu
+            { assertEquals(2000.0, doubleMonitor.taskGpuDemands["0"]?.get(1), "Double GPU demand in task \"0\" should be 2000.0") },
+            { assertEquals(4000.0, doubleMonitor.taskGpuSupplied["0"]?.get(1), "Double GPU supplied in task \"0\" should be 4000.0") },
+            {
+                assertEquals(
+                    2000.0,
+                    doubleMonitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(0),
+                    "Double GPU demand for GPU 0 at host \"DualGpuHost\" should be 2000.0",
+                )
+            },
+            {
+                assertEquals(
+                    2000.0,
+                    doubleMonitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(0),
+                    "Double GPU supplied for GPU 0 at host \"DualGpuHost\" should be 2000.0",
+                )
+            },
+            {
+                assertEquals(
+                    2000.0,
+                    doubleMonitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(1),
+                    "Double GPU demand for GPU 1 at host \"DualGpuHost\" should be 2000.0",
+                )
+            },
+            {
+                assertEquals(
+                    2000.0,
+                    doubleMonitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(1),
+                    "Double GPU supplied for GPU 1 at host \"DualGpuHost\" should be 2000.0",
+                )
+            },
+        )
+    }
+
+    /**
+     * This test verifies that the [EqualShareDistributionPolicy] correctly distributes supply according to the number of suppliers.
+     * The supply is divided equally among all suppliers.
+     */
+    @Test
+    fun equalShareDistributionPolicyTest2() {
+        val workload: ArrayList<Task> =
+            arrayListOf(
+                createTestTask(
+                    name = "0",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 4000.0, 2),
+                        ),
+                ),
+                createTestTask(
+                    name = "1",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 4000.0, 2),
+                        ),
+                ),
+            )
+
+        val singleGpuTopology = createTopology("DistributionPolicies/equalShare/dual_core_gpu_host.json")
+        val doubleGpuTopology = createTopology("DistributionPolicies/equalShare/multi_gpu_host.json")
+
+        val singleMonitor = runTest(singleGpuTopology, workload)
+        val doubleMonitor = runTest(doubleGpuTopology, workload)
+
+        assertAll(
+            // single gpu
+            // task 0
+            { assertEquals(4000.0, singleMonitor.taskGpuDemands["0"]?.get(1), "Single GPU demand in task \"0\" should be 4000.0") },
+            { assertEquals(2000.0, singleMonitor.taskGpuSupplied["0"]?.get(1), "Single GPU supplied in task \"0\" should be 2000.0") },
+            // task 1
+            { assertEquals(4000.0, singleMonitor.taskGpuDemands["1"]?.get(1), "Single GPU demand in task \"0\" should be 4000.0") },
+            { assertEquals(2000.0, singleMonitor.taskGpuSupplied["1"]?.get(1), "Single GPU supplied in task \"0\" should be 2000.0") },
+            // host
+            {
+                assertEquals(
+                    4000.0,
+                    singleMonitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(0),
+                    "Single GPU demand at host \"DualGpuHost\" should be 4000.0",
+                )
+            },
+            {
+                assertEquals(
+                    4000.0,
+                    singleMonitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(0),
+                    "Single GPU supply at host \"DualGpuHost\" should be 4000.0",
+                )
+            },
+            // double gpu
+            // task 0
+            { assertEquals(4000.0, doubleMonitor.taskGpuDemands["0"]?.get(1), "Double GPU demand in task \"0\" should be 4000.0") },
+            { assertEquals(2000.0, doubleMonitor.taskGpuSupplied["0"]?.get(1), "Double GPU supply in task \"0\" should be 2000.0") },
+            // task 1
+            { assertEquals(4000.0, doubleMonitor.taskGpuDemands["1"]?.get(1), "Double GPU demand in task \"0\" should be 4000.0") },
+            { assertEquals(2000.0, doubleMonitor.taskGpuSupplied["1"]?.get(1), "Double GPU supply in task \"0\" should be 2000.0") },
+            // host
+            {
+                assertEquals(
+                    2000.0,
+                    doubleMonitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(0),
+                    "Double GPU demand for GPU 0 at host \"DualGpuHost\" should be 2000.0",
+                )
+            },
+            {
+                assertEquals(
+                    2000.0,
+                    doubleMonitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(0),
+                    "Double GPU supply for GPU 0 at host \"DualGpuHost\" should be 2000.0",
+                )
+            },
+            {
+                assertEquals(
+                    2000.0,
+                    doubleMonitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(1),
+                    "Double GPU demand for GPU 1 at host \"DualGpuHost\" should be 2000.0",
+                )
+            },
+            {
+                assertEquals(
+                    2000.0,
+                    doubleMonitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(1),
+                    "Double GPU supply for GPU 1 at host \"DualGpuHost\" should be 2000.0",
+                )
+            },
+        )
+    }
+
+    /**
+     * This test verifies that the [FixedShareDistributionPolicy] correctly distributes supply according to the fixed share.
+     * The supply is divided according to the fixed share defined for each supplier.
+     */
+    @Test
+    fun fixedShareDistributionPolicyTest() {
+        val workload: ArrayList<Task> =
+            arrayListOf(
+                createTestTask(
+                    name = "0",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 4000.0, 2),
+                        ),
+                ),
+            )
+
+        val topology = createTopology("DistributionPolicies/fixedShare/multi_gpu_host.json")
+
+        val monitor = runTest(topology, workload)
+
+        assertAll(
+            { assertEquals(4000.0, monitor.taskGpuDemands["0"]?.get(1), "Task GPU demand should be 4000.0") },
+            { assertEquals(1000.0, monitor.taskGpuSupplied["0"]?.get(1), "Task GPU supplied should be 1000.0") },
+            // Host
+            {
+                assertEquals(
+                    1000.0,
+                    monitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(0),
+                    "GPU 0 demand at host should be 1000.0 (50% of the capacity)",
+                )
+            },
+            { assertEquals(1000.0, monitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(0), "GPU 0 supplied at host should be 1000.0") },
+            {
+                assertEquals(
+                    1000.0,
+                    monitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(1),
+                    "GPU 1 demand at host should be 1000.0 (50% of the capacity)",
+                )
+            },
+            { assertEquals(1000.0, monitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(1), "GPU 1 supplied at host should be 1000.0") },
+        )
+    }
+
+    /**
+     * This test verifies that the [FixedShareDistributionPolicy] correctly handles resource contention.
+     * When total demand exceeds available supply, resources should be distributed according to the fixed share ratio.
+     */
+    @Test
+    fun fixedShareDistributionPolicyContentionTest() {
+        val workload: ArrayList<Task> =
+            arrayListOf(
+                createTestTask(
+                    name = "0",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 6000.0, 2),
+                        ),
+                ),
+            )
+
+        val topology = createTopology("DistributionPolicies/fixedShare/multi_gpu_host.json")
+
+        val monitor = runTest(topology, workload)
+
+        // With demand of 6000.0 but total GPU capacity of 4000.0 (2 GPUs * 2000.0 each)
+        // Fixed share ratio of 0.5 means each GPU gets 50% of available capacity = 2000.0 each
+        // Total supplied should be 4000.0 (limited by total capacity)
+        assertAll(
+            { assertEquals(6000.0, monitor.taskGpuDemands["0"]?.get(1), "Task GPU demand should be 6000.0") },
+            { assertEquals(1000.0, monitor.taskGpuSupplied["0"]?.get(1), "Task GPU supplied should be 1000.0 (limited by the capacity)") },
+            // Host
+            {
+                assertEquals(
+                    1000.0,
+                    monitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(0),
+                    "GPU 0 demand at host should be 1000.0 (50% of the gpu capacity)",
+                )
+            },
+            {
+                assertEquals(
+                    1000.0,
+                    monitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(0),
+                    "GPU 0 supplied at host should be 1000.0 (limited by GPU capacity)",
+                )
+            },
+            {
+                assertEquals(
+                    1000.0,
+                    monitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(1),
+                    "GPU 1 demand at host should be 1000.0 (50% of the gpu capacity)",
+                )
+            },
+            {
+                assertEquals(
+                    1000.0,
+                    monitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(1),
+                    "GPU 1 supplied at host should be 1000.0 (limited by GPU capacity)",
+                )
+            },
+        )
+    }
+
+    /**
+     * This test verifies that the [FixedShareDistributionPolicy] correctly handles multiple tasks competing for resources.
+     * Resources should be distributed proportionally according to the fixed share ratio among all tasks.
+     */
+    @Test
+    fun fixedShareDistributionPolicyMultipleTasksTest() {
+        val workload: ArrayList<Task> =
+            arrayListOf(
+                createTestTask(
+                    name = "0",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 3000.0, 2),
+                        ),
+                ),
+                createTestTask(
+                    name = "1",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 3000.0, 2),
+                        ),
+                ),
+            )
+
+        val topology = createTopology("DistributionPolicies/fixedShare/multi_gpu_host.json")
+
+        val monitor = runTest(topology, workload)
+
+        // Total demand: 6000.0 (3000.0 from each task)
+        // Total capacity: 4000.0 (2 GPUs * 2000.0 each)
+        // So each task gets 1000.0, distributed as 1000.0 per GPU (50% share ratio)
+        assertAll(
+            // Task 0
+            { assertEquals(3000.0, monitor.taskGpuDemands["0"]?.get(1), "Task 0 GPU demand should be 3000.0") },
+            { assertEquals(1000.0, monitor.taskGpuSupplied["0"]?.get(1), "Task 0 GPU supplied should be 1000.0") },
+            // Task 1
+            { assertEquals(3000.0, monitor.taskGpuDemands["1"]?.get(1), "Task 1 GPU demand should be 3000.0") },
+            { assertEquals(1000.0, monitor.taskGpuSupplied["1"]?.get(1), "Task 1 GPU supplied should be 1000.0") },
+            // Host
+            { assertEquals(1000.0, monitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(0), "GPU 0 total demand at host should be 1000.0") },
+            {
+                assertEquals(
+                    1000.0,
+                    monitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(0),
+                    "GPU 0 total supplied at host should be 1000.0",
+                )
+            },
+            { assertEquals(1000.0, monitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(1), "GPU 1 total demand at host should be 1000.0") },
+            {
+                assertEquals(
+                    1000.0,
+                    monitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(1),
+                    "GPU 1 total supplied at host should be 1000.0",
+                )
+            },
+        )
+    }
+
+    /**
+     * This test verifies that the [BestEffortDistributionPolicy] correctly distributes supply based on demand
+     * when resources are abundant. It should satisfy all demands and distribute remaining capacity optimally.
+     */
+    @Test
+    fun bestEffortDistributionPolicyBasicTest() {
+        val workload: ArrayList<Task> =
+            arrayListOf(
+                createTestTask(
+                    name = "0",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 1500.0, 1),
+                        ),
+                ),
+            )
+
+        val singleGpuTopology = createTopology("DistributionPolicies/bestEffort/dual_core_gpu_host.json")
+        val doubleGpuTopology = createTopology("DistributionPolicies/bestEffort/multi_gpu_host.json")
+
+        val singleMonitor = runTest(singleGpuTopology, workload)
+        val doubleMonitor = runTest(doubleGpuTopology, workload)
+
+        assertAll(
+            // single gpu - should satisfy demand and utilize remaining capacity
+            { assertEquals(1500.0, singleMonitor.taskGpuDemands["0"]?.get(1), "Single GPU demand in task \"0\" should be 1500.0") },
+            { assertEquals(1500.0, singleMonitor.taskGpuSupplied["0"]?.get(1)) { "Single GPU should supply the demanded 1500.0" } },
+            // Host
+            {
+                assertEquals(
+                    1500.0,
+                    singleMonitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(0),
+                    "Single GPU demand at host \"DualGpuHost\" should be 1500.0",
+                )
+            },
+            {
+                assertEquals(
+                    1500.0,
+                    singleMonitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(0),
+                    "Single GPU supply at host \"DualGpuHost\" should be 1500.0",
+                )
+            },
+            // double gpu - should distribute across both GPUs and utilize remaining capacity
+            { assertEquals(1500.0, doubleMonitor.taskGpuDemands["0"]?.get(1), "Double GPU demand in task \"0\" should be 1500.0") },
+            { assertEquals(1500.0, doubleMonitor.taskGpuSupplied["0"]?.get(1), "Double GPU should supply the demanded 1500.0") },
+            // Host
+            {
+                assertEquals(
+                    1500.0,
+                    doubleMonitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(0),
+                    "GPU 0 demand at host \"DualGpuHost\" should be 750.0",
+                )
+            },
+            {
+                assertEquals(
+                    1500.0,
+                    doubleMonitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(0),
+                    "GPU 0 supply at host \"DualGpuHost\" should be 750.0",
+                )
+            },
+            {
+                assertEquals(
+                    0.0,
+                    doubleMonitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(1),
+                    "GPU 1 demand at host \"DualGpuHost\" should be 750.0",
+                )
+            },
+            {
+                assertEquals(
+                    0.0,
+                    doubleMonitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(1),
+                    "GPU 1 supply at host \"DualGpuHost\" should be 750.0",
+                )
+            },
+        )
+    }
+
+    /**
+     * This test verifies that the [BestEffortDistributionPolicy] correctly handles resource contention
+     * by using round-robin distribution when demand exceeds supply.
+     */
+    @Test
+    fun bestEffortDistributionPolicyContentionTest() {
+        val workload: ArrayList<Task> =
+            arrayListOf(
+                createTestTask(
+                    name = "0",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 3000.0, 2),
+                        ),
+                ),
+                createTestTask(
+                    name = "1",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 2500.0, 2),
+                        ),
+                ),
+            )
+
+        val topology = createTopology("DistributionPolicies/bestEffort/multi_gpu_host.json")
+        val monitor = runTest(topology, workload)
+
+        // Total demand: 5500.0 (3000.0 + 2500.0)
+        // Total capacity: 4000.0 (2 GPUs * 2000.0 each)
+        // Best effort should distribute proportionally based on demand while using round-robin
+        assertAll(
+            // Task 0
+            { assertEquals(3000.0, monitor.taskGpuDemands["0"]?.get(1), "Task 0 GPU demand should be 3000.0") },
+            { assertEquals(3000.0, monitor.taskGpuSupplied["0"]?.get(1), "Task 0 GPU supply should be 1000.0") },
+            // Task 1
+            { assertEquals(2500.0, monitor.taskGpuDemands["1"]?.get(1), "Task 1 GPU demand should be 2500.0") },
+            { assertEquals(1000.0, monitor.taskGpuSupplied["1"]?.get(1), "Task 0 GPU supply should be 1000.0") },
+            // Host
+            { assertEquals(2750.0, monitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(0), "GPU 0 demand at host should be 2000.0") },
+            { assertEquals(2000.0, monitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(0), "GPU 0 supplied at host should be 2000.0") },
+            { assertEquals(2750.0, monitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(1), "GPU 1 demand at host should be 2000.0") },
+            { assertEquals(2000.0, monitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(1), "GPU 1 supplied at host should be 2000.0") },
+        )
+    }
+
+    /**
+     * This test verifies that the [BestEffortDistributionPolicy] prioritizes already utilized resources
+     * when supply exceeds demand, demonstrating the efficiency optimization principle.
+     */
+    @Test
+    fun bestEffortDistributionPolicyUtilizationOptimizationTest() {
+        val workload: ArrayList<Task> =
+            arrayListOf(
+                createTestTask(
+                    name = "0",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 1000.0, 1),
+                        ),
+                ),
+            )
+
+        val doubleGpuTopology = createTopology("DistributionPolicies/bestEffort/multi_gpu_host.json")
+        val monitor = runTest(doubleGpuTopology, workload)
+
+        // With low demand (1000.0) and high capacity (4000.0), best effort should:
+        // 1. Satisfy the demand
+        // 2. Utilize remaining capacity efficiently
+        assertAll(
+            { assertEquals(1000.0, monitor.taskGpuDemands["0"]?.get(1), "Task GPU demand should be 1000.0") },
+            { assertEquals(1000.0, monitor.taskGpuSupplied["0"]?.get(1), "Task GPU supplied should be 1000.0") },
+            // host
+            { assertEquals(1000.0, monitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(0), "GPU 0 demand at host should be 1000.0") },
+            { assertEquals(1000.0, monitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(0), "GPU 0 supplied at host should be 1000.0") },
+            { assertEquals(0.0, monitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(1), "GPU 1 demand at host should be 0.0") },
+            { assertEquals(0.0, monitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(1), "GPU 1 supplied at host should be 0.0") },
+        )
+    }
+
+    /**
+     * This test verifies that the [BestEffortDistributionPolicy] handles varying demands correctly
+     * and does not distribute the resources equally.
+     */
+    @Test
+    fun bestEffortDistributionPolicyVaryingDemandsTest() {
+        val workload: ArrayList<Task> =
+            arrayListOf(
+                createTestTask(
+                    name = "0",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 3500.0, 2),
+                        ),
+                ),
+                createTestTask(
+                    name = "1",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 500.0, 2),
+                        ),
+                ),
+            )
+
+        val topology = createTopology("DistributionPolicies/bestEffort/multi_gpu_host.json")
+
+        val monitor = runTest(topology, workload)
+
+        // Best effort should prioritize the high-demand task differently than equal share
+        assertAll(
+            // Best effort should allocate more to high-demand task compared to equal share
+            { assertEquals(3500.0, monitor.taskGpuDemands["0"]?.get(1), "Task 0 demand should be 3500.0") },
+            { assertEquals(3500.0, monitor.taskGpuDemands["0"]?.get(1), "Task 0 supply should be 3500.0") },
+            { assertEquals(500.0, monitor.taskGpuDemands["1"]?.get(1), "Task 1 demand should be 500.0") },
+            { assertEquals(500.0, monitor.taskGpuSupplied["1"]?.get(1), "Task 1 supply should be 500.0") },
+            // Host
+            { assertEquals(2000.0, monitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(0), "GPU 0 demand at host should be 2000.0") },
+            { assertEquals(2000.0, monitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(0), "GPU 0 supplied at host should be 2000.0") },
+            { assertEquals(2000.0, monitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(1), "GPU 1 demand at host should be 2000.0") },
+            { assertEquals(2000.0, monitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(1), "GPU 1 supplied at host should be 2000.0") },
+        )
+    }
+
+    /**
+     * This test verifies that the [BestEffortDistributionPolicy] maintains fairness over time
+     * through its round-robin mechanism when resources are constrained.
+     */
+    @Test
+    fun bestEffortDistributionPolicyFairnessTest() {
+        val workload: ArrayList<Task> =
+            arrayListOf(
+                createTestTask(
+                    name = "0",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 2000.0, 2),
+                        ),
+                ),
+                createTestTask(
+                    name = "1",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 2000.0, 2),
+                        ),
+                ),
+                createTestTask(
+                    name = "2",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 2000.0, 2),
+                        ),
+                ),
+            )
+
+        val topology = createTopology("DistributionPolicies/bestEffort/multi_gpu_host.json")
+        val monitor = runTest(topology, workload)
+
+        // With equal demands (2000.0 each) and limited capacity (4000.0 total)
+        // Best effort should distribute fairly among all tasks in a round-robin manner
+        assertAll(
+            // Task Demands at start
+            { assertEquals(2000.0, monitor.taskGpuDemands["0"]?.get(1), "Task 0 demand should be 2000.0") },
+            { assertEquals(2000.0, monitor.taskGpuDemands["1"]?.get(1), "Task 1 demand should be 2000.0") },
+            { assertEquals(2000.0, monitor.taskGpuDemands["2"]?.get(1), "Task 2 demand should be 2000.0") },
+            // Task supplies at start
+            { assertEquals(2000.0, monitor.taskGpuSupplied["0"]?.get(1), "Task 0 supply at the start should be 2000.0") },
+            { assertEquals(0.0, monitor.taskGpuSupplied["1"]?.get(1), "Task 1 supply at the start  should be 2000.0") },
+            { assertEquals(2000.0, monitor.taskGpuSupplied["2"]?.get(1), "Task 2 supply at the start  should be 0.0") },
+            // Task supplies second step
+            { assertEquals(0.0, monitor.taskGpuSupplied["0"]?.get(2), "Task 0 supply at the second step should be 2000.0") },
+            { assertEquals(2000.0, monitor.taskGpuSupplied["1"]?.get(2), "Task 1 supply at the second step should be 0.0") },
+            { assertEquals(2000.0, monitor.taskGpuSupplied["2"]?.get(2), "Task 2 supply at the second step should be 2000.0") },
+            // Task supplies third step
+            { assertEquals(2000.0, monitor.taskGpuSupplied["0"]?.get(3), "Task 0 supply at the third step should be 2000.0") },
+            { assertEquals(2000.0, monitor.taskGpuSupplied["1"]?.get(3), "Task 1 supply at the third step should be 2000.0") },
+            { assertEquals(0.0, monitor.taskGpuSupplied["2"]?.get(3), "Task 2 supply at the third step should be 0.0") },
+            // Host
+            // At start
+            { assertEquals(3000.0, monitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(0), "GPU 0 demand at host should be 2000.0") },
+            { assertEquals(2000.0, monitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(0), "GPU 0 supplied at host should be 2000.0") },
+            { assertEquals(3000.0, monitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(1), "GPU 1 demand at host should be 2000.0") },
+            { assertEquals(2000.0, monitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(1), "GPU 1 supplied at host should be 2000.0") },
+            // Next Round
+            { assertEquals(3000.0, monitor.hostGpuDemands["DualGpuHost"]?.get(2)?.get(0), "GPU 0 demand at host should be 2000.0") },
+            { assertEquals(2000.0, monitor.hostGpuSupplied["DualGpuHost"]?.get(2)?.get(0), "GPU 0 supplied at host should be 2000.0") },
+            { assertEquals(3000.0, monitor.hostGpuDemands["DualGpuHost"]?.get(2)?.get(1), "GPU 1 demand at host should be 2000.0") },
+            { assertEquals(2000.0, monitor.hostGpuSupplied["DualGpuHost"]?.get(2)?.get(1), "GPU 1 supplied at host should be 2000.0") },
+            // Next Round
+            { assertEquals(3000.0, monitor.hostGpuDemands["DualGpuHost"]?.get(3)?.get(0), "GPU 0 demand at host should be 2000.0") },
+            { assertEquals(2000.0, monitor.hostGpuSupplied["DualGpuHost"]?.get(3)?.get(0), "GPU 0 supplied at host should be 2000.0") },
+            { assertEquals(3000.0, monitor.hostGpuDemands["DualGpuHost"]?.get(3)?.get(1), "GPU 1 demand at host should be 2000.0") },
+            { assertEquals(2000.0, monitor.hostGpuSupplied["DualGpuHost"]?.get(3)?.get(1), "GPU 1 supplied at host should be 2000.0") },
+        )
+    }
+
+    /**
+     * This test verifies that the [FirstFitDistributionPolicy] places workloads on the first GPU
+     * before utilizing the second GPU, demonstrating the First Fit allocation strategy.
+     * All tasks should be satisfied as total demand is within available capacity.
+     */
+    @Test
+    fun firstFitDistributionPolicyGpuPlacementTest() {
+        val workload: ArrayList<Task> =
+            arrayListOf(
+                createTestTask(
+                    name = "0",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 1500.0, 1),
+                        ),
+                ),
+                createTestTask(
+                    name = "1",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 1000.0, 1),
+                        ),
+                ),
+            )
+
+        val topology = createTopology("DistributionPolicies/firstFit/multi_gpu_host.json")
+        val monitor = runTest(topology, workload)
+
+        // With First Fit policy, tasks should be placed on first GPU before second GPU
+        // Total demand (2500.0) is less than total capacity (4000.0), so all should be satisfied
+        assertAll(
+            // Task demands should remain as requested
+            { assertEquals(1500.0, monitor.taskGpuDemands["0"]?.get(1), "Task 0 GPU demand should be 1500.0") },
+            { assertEquals(1000.0, monitor.taskGpuDemands["1"]?.get(1), "Task 1 GPU demand should be 1000.0") },
+            // All tasks should be fully satisfied
+            { assertEquals(1500.0, monitor.taskGpuSupplied["0"]?.get(1), "Task 0 GPU supply should be 1500.0") },
+            { assertEquals(1000.0, monitor.taskGpuSupplied["1"]?.get(1), "Task 1 GPU supply should be 1000.0") },
+            // First GPU should handle both tasks (total 2500.0, within its 2000.0 capacity limit per task)
+            { assertEquals(2000.0, monitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(0), "GPU 0 demand should be 2000.0") },
+            { assertEquals(2000.0, monitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(0), "GPU 0 supply should be 2000.0") },
+            // Second GPU should have remaining demand
+            { assertEquals(500.0, monitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(1), "GPU 1 demand should be 500.0") },
+            { assertEquals(500.0, monitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(1), "GPU 1 supply should be 500.0") },
+        )
+    }
+
+    /**
+     * This test verifies that the [FirstFitDistributionPolicy] correctly handles scenarios
+     * where overall demand exceeds total available supply. Some tasks should receive no supply
+     * if they cannot be satisfied by a single GPU.
+     */
+    @Test
+    fun firstFitDistributionPolicyOverdemandTest() {
+        val workload: ArrayList<Task> =
+            arrayListOf(
+                createTestTask(
+                    name = "0",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 2000.0, 1),
+                        ),
+                ),
+                createTestTask(
+                    name = "1",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 2000.0, 1),
+                        ),
+                ),
+                createTestTask(
+                    name = "2",
+                    fragments =
+                        arrayListOf(
+                            TraceFragment(10 * 60 * 1000, 0.0, 0, 1500.0, 1),
+                        ),
+                ),
+            )
+
+        val topology = createTopology("DistributionPolicies/firstFit/multi_gpu_host.json")
+        val monitor = runTest(topology, workload)
+
+        // With First Fit policy and total demand (5500.0) > total capacity (4000.0),
+        // only tasks that can fit on individual GPUs should be satisfied
+        assertAll(
+            // Task demands should remain as requested
+            { assertEquals(2000.0, monitor.taskGpuDemands["0"]?.get(1), "Task 0 GPU demand should be 2000.0") },
+            { assertEquals(2000.0, monitor.taskGpuDemands["1"]?.get(1), "Task 1 GPU demand should be 2000.0") },
+            { assertEquals(1500.0, monitor.taskGpuDemands["2"]?.get(1), "Task 2 GPU demand should be 1500.0") },
+            // First two tasks should be satisfied (each fits on one GPU)
+            { assertEquals(2000.0, monitor.taskGpuSupplied["0"]?.get(1), "Task 0 should be fully satisfied") },
+            { assertEquals(2000.0, monitor.taskGpuSupplied["1"]?.get(1), "Task 1 should be fully satisfied") },
+            // Third task should receive no supply as no single GPU can satisfy it after first two are allocated
+            { assertEquals(0.0, monitor.taskGpuSupplied["2"]?.get(1), "Task 2 should receive no supply") },
+            // Both GPUs should be fully utilized by the first two tasks
+            { assertEquals(2000.0, monitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(0), "GPU 0 should have 2000.0 demand") },
+            { assertEquals(2000.0, monitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(0), "GPU 0 should supply 2000.0") },
+            { assertEquals(2000.0, monitor.hostGpuDemands["DualGpuHost"]?.get(1)?.get(1), "GPU 1 should have 2000.0 demand") },
+            { assertEquals(2000.0, monitor.hostGpuSupplied["DualGpuHost"]?.get(1)?.get(1), "GPU 1 should supply 2000.0") },
+        )
+    }
+}
diff --git a/opendc-experiments/opendc-experiments-base/src/test/kotlin/org/opendc/experiments/base/SchedulerTest.kt b/opendc-experiments/opendc-experiments-base/src/test/kotlin/org/opendc/experiments/base/SchedulerTest.kt
index 8f71b7e7..efb83814 100644
--- a/opendc-experiments/opendc-experiments-base/src/test/kotlin/org/opendc/experiments/base/SchedulerTest.kt
+++ b/opendc-experiments/opendc-experiments-base/src/test/kotlin/org/opendc/experiments/base/SchedulerTest.kt
@@ -109,7 +109,7 @@ class SchedulerTest {
             )
 
         // Topology with 1 host having 2 GPUs (both tasks can fit on one host)
-        val fittingTopology = createTopology("Gpus/dual_gpu_host.json")
+        val fittingTopology = createTopology("Gpus/dual_core_gpu_host.json")
 
         // Topology with 2 hosts each having 1 GPU (tasks must be distributed)
         val nonFittingTopology = createTopology("Gpus/single_gpu_hosts.json")
diff --git a/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/bestEffort/dual_core_gpu_host.json b/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/bestEffort/dual_core_gpu_host.json
new file mode 100644
index 00000000..a2758fd1
--- /dev/null
+++ b/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/bestEffort/dual_core_gpu_host.json
@@ -0,0 +1,42 @@
+{
+    "clusters": [
+        {
+            "name": "C01",
+            "hosts": [
+                {
+                    "name": "DualGpuHost",
+                    "cpu": {
+                        "coreCount": 4,
+                        "coreSpeed": 2000
+                    },
+                    "memory": {
+                        "memorySize": 140457600000
+                    },
+                    "cpuPowerModel": {
+                        "modelType": "linear",
+                        "power": 400.0,
+                        "idlePower": 100.0,
+                        "maxPower": 200.0
+                    },
+                    "cpuDistributionPolicy": {
+                        "type": "MAX_MIN_FAIRNESS"
+                    },
+                    "gpu": {
+                        "coreCount": 2,
+                        "coreSpeed": 2000
+                    },
+                    "gpuPowerModel": {
+                        "modelType": "linear",
+                        "power": 400.0,
+                        "idlePower": 100.0,
+                        "maxPower": 200.0
+                    },
+                    "gpuDistributionPolicy": {
+                        "type": "BEST_EFFORT",
+                        "updateIntervalLength": 60000
+                    }
+                }
+            ]
+        }
+    ]
+}
diff --git a/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/bestEffort/multi_gpu_host.json b/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/bestEffort/multi_gpu_host.json
new file mode 100644
index 00000000..8169793d
--- /dev/null
+++ b/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/bestEffort/multi_gpu_host.json
@@ -0,0 +1,40 @@
+{
+    "clusters": [
+        {
+            "name": "C01",
+            "hosts": [
+                {
+                    "name": "DualGpuHost",
+                    "cpu": {
+                        "coreCount": 4,
+                        "coreSpeed": 2000
+                    },
+                    "memory": {
+                        "memorySize": 140457600000
+                    },
+                    "cpuPowerModel": {
+                        "modelType": "linear",
+                        "power": 400.0,
+                        "idlePower": 100.0,
+                        "maxPower": 200.0
+                    },
+                    "gpu": {
+                        "count": 2,
+                        "coreCount": 1,
+                        "coreSpeed": 2000
+                    },
+                    "gpuPowerModel": {
+                        "modelType": "linear",
+                        "power": 400.0,
+                        "idlePower": 100.0,
+                        "maxPower": 200.0
+                    },
+                    "gpuDistributionPolicy": {
+                        "type": "BEST_EFFORT",
+                        "updateIntervalLength": 60000
+                    }
+                }
+            ]
+        }
+    ]
+}
diff --git a/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/equalShare/dual_core_gpu_host.json b/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/equalShare/dual_core_gpu_host.json
new file mode 100644
index 00000000..aa128cba
--- /dev/null
+++ b/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/equalShare/dual_core_gpu_host.json
@@ -0,0 +1,41 @@
+{
+    "clusters": [
+        {
+            "name": "C01",
+            "hosts": [
+                {
+                    "name": "DualGpuHost",
+                    "cpu": {
+                        "coreCount": 4,
+                        "coreSpeed": 2000
+                    },
+                    "memory": {
+                        "memorySize": 140457600000
+                    },
+                    "cpuPowerModel": {
+                        "modelType": "linear",
+                        "power": 400.0,
+                        "idlePower": 100.0,
+                        "maxPower": 200.0
+                    },
+                    "cpuDistributionPolicy": {
+                        "type": "MAX_MIN_FAIRNESS"
+                    },
+                    "gpu": {
+                        "coreCount": 2,
+                        "coreSpeed": 2000
+                    },
+                    "gpuPowerModel": {
+                        "modelType": "linear",
+                        "power": 400.0,
+                        "idlePower": 100.0,
+                        "maxPower": 200.0
+                    },
+                    "gpuDistributionPolicy": {
+                        "type": "EQUAL_SHARE"
+                    }
+                }
+            ]
+        }
+    ]
+}
diff --git a/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/equalShare/multi_gpu_host.json b/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/equalShare/multi_gpu_host.json
new file mode 100644
index 00000000..59b0dbd2
--- /dev/null
+++ b/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/equalShare/multi_gpu_host.json
@@ -0,0 +1,42 @@
+{
+    "clusters": [
+        {
+            "name": "C01",
+            "hosts": [
+                {
+                    "name": "DualGpuHost",
+                    "cpu": {
+                        "coreCount": 4,
+                        "coreSpeed": 2000
+                    },
+                    "memory": {
+                        "memorySize": 140457600000
+                    },
+                    "cpuPowerModel": {
+                        "modelType": "linear",
+                        "power": 400.0,
+                        "idlePower": 100.0,
+                        "maxPower": 200.0
+                    },
+                    "cpuDistributionPolicy": {
+                        "type": "MAX_MIN_FAIRNESS"
+                    },
+                    "gpu": {
+                        "count": 2,
+                        "coreCount": 1,
+                        "coreSpeed": 2000
+                    },
+                    "gpuPowerModel": {
+                        "modelType": "linear",
+                        "power": 400.0,
+                        "idlePower": 100.0,
+                        "maxPower": 200.0
+                    },
+                    "gpuDistributionPolicy": {
+                        "type": "EQUAL_SHARE"
+                    }
+                }
+            ]
+        }
+    ]
+}
diff --git a/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/firstFit/multi_gpu_host.json b/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/firstFit/multi_gpu_host.json
new file mode 100644
index 00000000..306431ca
--- /dev/null
+++ b/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/firstFit/multi_gpu_host.json
@@ -0,0 +1,40 @@
+{
+    "clusters": [
+        {
+            "name": "C01",
+            "hosts": [
+                {
+                    "name": "DualGpuHost",
+                    "cpu": {
+                        "coreCount": 4,
+                        "coreSpeed": 2000
+                    },
+                    "memory": {
+                        "memorySize": 140457600000
+                    },
+                    "cpuPowerModel": {
+                        "modelType": "linear",
+                        "power": 400.0,
+                        "idlePower": 100.0,
+                        "maxPower": 200.0
+                    },
+                    "gpu": {
+                        "count": 2,
+                        "coreCount": 1,
+                        "coreSpeed": 2000
+                    },
+                    "gpuPowerModel": {
+                        "modelType": "linear",
+                        "power": 400.0,
+                        "idlePower": 100.0,
+                        "maxPower": 200.0
+                    },
+                    "gpuDistributionPolicy": {
+                        "type": "FIRST_FIT"
+                    }
+                }
+            ]
+        }
+    ]
+}
+
diff --git a/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/fixedShare/multi_gpu_host.json b/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/fixedShare/multi_gpu_host.json
new file mode 100644
index 00000000..2aa3a057
--- /dev/null
+++ b/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/fixedShare/multi_gpu_host.json
@@ -0,0 +1,40 @@
+{
+    "clusters": [
+        {
+            "name": "C01",
+            "hosts": [
+                {
+                    "name": "DualGpuHost",
+                    "cpu": {
+                        "coreCount": 4,
+                        "coreSpeed": 2000
+                    },
+                    "memory": {
+                        "memorySize": 140457600000
+                    },
+                    "cpuPowerModel": {
+                        "modelType": "linear",
+                        "power": 400.0,
+                        "idlePower": 100.0,
+                        "maxPower": 200.0
+                    },
+                    "gpu": {
+                        "count": 2,
+                        "coreCount": 1,
+                        "coreSpeed": 2000
+                    },
+                    "gpuPowerModel": {
+                        "modelType": "linear",
+                        "power": 400.0,
+                        "idlePower": 100.0,
+                        "maxPower": 200.0
+                    },
+                    "gpuDistributionPolicy": {
+                        "type": "FIXED_SHARE",
+                        "shareRatio": 0.5
+                    }
+                }
+            ]
+        }
+    ]
+}
diff --git a/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/maxMinFairness/multi_gpu_host.json b/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/maxMinFairness/multi_gpu_host.json
new file mode 100644
index 00000000..74df2f8c
--- /dev/null
+++ b/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/DistributionPolicies/maxMinFairness/multi_gpu_host.json
@@ -0,0 +1,39 @@
+{
+    "clusters": [
+        {
+            "name": "C01",
+            "hosts": [
+                {
+                    "name": "DualGpuHost",
+                    "cpu": {
+                        "coreCount": 4,
+                        "coreSpeed": 2000
+                    },
+                    "memory": {
+                        "memorySize": 140457600000
+                    },
+                    "cpuPowerModel": {
+                        "modelType": "linear",
+                        "power": 400.0,
+                        "idlePower": 100.0,
+                        "maxPower": 200.0
+                    },
+                    "gpu": {
+                        "count": 2,
+                        "coreCount": 1,
+                        "coreSpeed": 2000
+                    },
+                    "gpuPowerModel": {
+                        "modelType": "linear",
+                        "power": 400.0,
+                        "idlePower": 100.0,
+                        "maxPower": 200.0
+                    },
+                    "gpuDistributionPolicy": {
+                        "type": "MAX_MIN_FAIRNESS"
+                    }
+                }
+            ]
+        }
+    ]
+}
diff --git a/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/Gpus/dual_gpu_host.json b/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/Gpus/dual_core_gpu_host.json
index c5271ff8..c5271ff8 100644
--- a/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/Gpus/dual_gpu_host.json
+++ b/opendc-experiments/opendc-experiments-base/src/test/resources/topologies/Gpus/dual_core_gpu_host.json