diff --git a/notebooks/cugraph_benchmarks/synth_release_single_node_multi_gpu.ipynb b/notebooks/cugraph_benchmarks/synth_release_single_node_multi_gpu.ipynb
index 1796bc489d3..727bcd84efd 100644
--- a/notebooks/cugraph_benchmarks/synth_release_single_node_multi_gpu.ipynb
+++ b/notebooks/cugraph_benchmarks/synth_release_single_node_multi_gpu.ipynb
@@ -40,7 +40,8 @@
     "| Author        |    Date    |  Update             | cuGraph Version |  Test Hardware         |\n",
     "| --------------|------------|---------------------|-----------------|------------------------|\n",
     "| Don Acosta    | 1/12/2023  | Created             | 23.02 nightly   | RTX A6000, CUDA 11.7   |\n",
-    "| Brad Rees     | 1/27/2023  | Modified            | 23.02 nightly   | RTX A6000, CUDA 11.7   |\n"
+    "| Brad Rees     | 1/27/2023  | Modified            | 23.02 nightly   | RTX A6000, CUDA 11.7   |\n",
+    "| Naim, Md      | 2/08/2024  | Modified            | 24.04 nightly   | RTX A6000, CUDA 12.0   |\n"
    ]
   },
   {
@@ -124,21 +125,18 @@
     "import gc\n",
     "import os\n",
     "from time import perf_counter\n",
-    "import numpy as np\n",
-    "import math\n",
     "import pandas as pd\n",
     "from collections import defaultdict\n",
     "\n",
     "# rapids\n",
     "import cugraph\n",
-    "import cudf\n",
     "\n",
     "# to parallelize with dask\n",
     "import dask_cudf\n",
     "from cugraph.dask.common.mg_utils import get_visible_devices\n",
     "\n",
     "# liblibraries to setup dask cluster and client\n",
-    "from dask.distributed import Client, wait\n",
+    "from dask.distributed import Client\n",
     "from dask_cuda import LocalCUDACluster\n",
     "from cugraph.dask.comms import comms as Comms\n",
     "\n",
@@ -308,10 +306,7 @@
     "    _g = cugraph.Graph(directed=directed)\n",
     "\n",
     "    if mg:\n",
-    "        # Set the number of partition to #GPUs\n",
-    "        npartitions = 3 * len(get_visible_devices())\n",
-    "        _ddf = dask_cudf.from_cudf(_df.compute(), npartitions=npartitions)\n",
-    "        _g.from_dask_cudf_edgelist(_ddf, source=\"src\", destination=\"dst\", edge_attr=None)\n",
+    "        _g.from_dask_cudf_edgelist(_df, source=\"src\", destination=\"dst\", edge_attr=None)\n",
     "    else:\n",
     "        _g.from_cudf_edgelist(_df,\n",
     "                            source='src',\n",
@@ -695,12 +690,14 @@
     "        pdf = pd.concat([pdf, computed_df], ignore_index=True, sort=False)\n",
     "\n",
     "    print(f\"\\tdata in gdf {len(gdf)} and data in pandas {len(pdf)}\")\n",
-    "    # create the graphs\n",
+    "    \n",
+    "    # create cuGraph and NX graphs\n",
     "    g_cu, tcu = create_cu_graph(gdf, mg=True)\n",
     "    g_nx, tnx = create_nx_graph(pdf)\n",
     "    cugraph_graph_creation_times[dataset] = tcu\n",
     "    nx_graph_creation_times[dataset] = tnx\n",
     "    del gdf, pdf\n",
+    "\n",
     "    # prep\n",
     "    deg = g_cu.degree()\n",
     "    deg_max = deg['degree'].max().compute()\n",
@@ -753,7 +750,6 @@
     "    perf_algos[dataset][algorithm] = tx/tc \n",
     "    perf[dataset][algorithm] = (tx + tnx) / (tc + tcu)\n",
     "\n",
-    "    \n",
     "    #-- TC\n",
     "    algorithm = \"TC\"\n",
     "    print(f\"\\t{algorithm}  \", end = '')\n",
@@ -782,7 +778,6 @@
     "    perf_algos[dataset][algorithm] = tx/tc \n",
     "    perf[dataset][algorithm] = (tx + tnx) / (tc + tcu)\n",
     "\n",
-    "\n",
     "    #-- PageRank\n",
     "    algorithm = \"PageRank\"\n",
     "    print(f\"\\t{algorithm}  \", end = '')\n",
@@ -797,7 +792,6 @@
     "    perf_algos[dataset][algorithm] = tx/tc \n",
     "    perf[dataset][algorithm] = (tx + tnx) / (tc + tcu)\n",
     "\n",
-    "\n",
     "    #-- Jaccard\n",
     "    algorithm = \"Jaccard\"\n",
     "    print(f\"\\t{algorithm}  \", end = '')\n",
@@ -826,8 +820,6 @@
     "    tc = cu_bfs(g_cu, seed = cu_seed, mg=True)\n",
     "    print(\" \")\n",
     "\n",
-    "    \n",
-    "\n",
     "    nx_algo_run_times[dataset][algorithm] = tx\n",
     "    cugraph_algo_run_times[dataset][algorithm] = tc\n",
     "    perf_algos[dataset][algorithm] = tx/tc \n",