[DistGB] enable graphbolt for homograph distDGL (dmlc#7182)

examples/distributed/graphsage/README.md

@@ -138,3 +138,63 @@ python3 ~/workspace/dgl/tools/launch.py \
 --ip_config ip_config.txt \
 "python3 node_classification.py --graph_name ogbn-products --ip_config ip_config.txt --num_epochs 30 --batch_size 1000 --num_gpus 4"
 ```
+
+### Running with GraphBolt
+
+In order to run with `GraphBolt`, we need to partition graph into `GraphBolt` data formats.Please note that both `DGL` and `GraphBolt` partitions are saved together.
+
+```
+python3 partition_graph.py --dataset ogbn-products --num_parts 2 --balance_train --balance_edges --use_graphbolt
+```
+
+#### Partition sizes compared to DGL
+
+Compared to `DGL`, `GraphBolt` partitions are much smaller(reduced to **16%** and **19%** for `ogbn-products` and `ogbn-papers100M` respectively).
+
+`ogbn-products`
+
+| Data Formats |         File Name            | Part 0 | Part 1 |
+| ------------ | ---------------------------- | ------ | ------ |
+| DGL          | graph.dgl                    | 1.5GB  | 1.6GB  |
+| GraphBolt    | fused_csc_sampling_graph.pt  | 255MB  | 265MB  |
+
+`ogbn-papers100M`
+
+| Data Formats |         File Name            | Part 0 | Part 1 |
+| ------------ | ---------------------------- | ------ | ------ |
+| DGL          | graph.dgl                    | 23GB   | 22GB   |
+| GraphBolt    | fused_csc_sampling_graph.pt  | 4.4GB  | 4.1GB  |
+
+Then run example with `--use_graphbolt`.
+
+```
+python3 ~/workspace/dgl/tools/launch.py \
+--workspace ~/workspace/dgl/examples/pytorch/graphsage/dist/ \
+--num_trainers 4 \
+--num_samplers 0 \
+--num_servers 2 \
+--part_config data/ogbn-products.json \
+--ip_config ip_config.txt \
+"python3 node_classification.py --graph_name ogbn-products --ip_config ip_config.txt --num_epochs 10 --use_graphbolt"
+```
+
+#### Performance compared to `DGL`
+
+Compared to `DGL`, `GraphBolt`'s sampler works faster(reduced to **80%** and **77%** for `ogbn-products` and `ogbn-papers100M` respectively). `Min` and `Max` are statistics of all trainers on all nodes(machines).
+
+As for RAM usage, the shared memory(measured by **shared** field of `free` command) usage is decreased due to smaller graph partitions in `GraphBolt` though the peak memory used by processes(measured by **used** field of `free` command) does not decrease.
+
+`ogbn-products`
+
+| Data Formats | Sample Time Per Epoch (CPU) |      Test Accuracy (10 epochs)   |  shared | used (peak) |
+| ------------ | --------------------------- | -------------------------------- |  -----  | ---- |
+|     DGL      | Min: 1.2884s, Max: 1.4159s  | Min: 64.38%, Max: 70.42%         |  2.4GB  | 7.8GB|
+|   GraphBolt  | Min: 1.0589s, Max: 1.1400s  | Min: 61.68%, Max: 71.23%         |  1.1GB  | 7.8GB|
+
+
+`ogbn-papers100M`
+
+| Data Formats | Sample Time Per Epoch (CPU) |      Test Accuracy (10 epochs)   |  shared | used (peak) |
+| ------------ | --------------------------- | -------------------------------- |  -----  | ---- |
+|     DGL      | Min: 5.5570s, Max: 6.1900s  | Min: 29.12%, Max: 34.33%         |  84GB   | 43GB |
+|   GraphBolt  | Min: 4.5046s, Max: 4.7718s  | Min: 29.11%, Max: 33.49%         |  67GB   | 43GB |

examples/distributed/graphsage/node_classification.py

@@ -340,7 +340,7 @@ def main(args):
     """
     host_name = socket.gethostname()
     print(f"{host_name}: Initializing DistDGL.")
-    dgl.distributed.initialize(args.ip_config)
+    dgl.distributed.initialize(args.ip_config, use_graphbolt=args.use_graphbolt)
     print(f"{host_name}: Initializing PyTorch process group.")
     th.distributed.init_process_group(backend=args.backend)
     print(f"{host_name}: Initializing DistGraph.")
@@ -457,6 +457,11 @@ def main(args):
         help="Pad train nid to the same length across machine, to ensure num "
         "of batches to be the same.",
     )
+    parser.add_argument(
+        "--use_graphbolt",
+        action="store_true",
+        help="Use GraphBolt for distributed train.",
+    )
     args = parser.parse_args()
     print(f"Arguments: {args}")
     main(args)

examples/distributed/graphsage/partition_graph.py

@@ -87,6 +87,11 @@ def load_ogb(name, root="dataset"):
         default="data",
         help="Output path of partitioned graph.",
     )
+    argparser.add_argument(
+        "--use_graphbolt",
+        action="store_true",
+        help="Use GraphBolt for distributed train.",
+    )
     args = argparser.parse_args()
 
     start = time.time()
@@ -127,4 +132,5 @@ def load_ogb(name, root="dataset"):
         balance_ntypes=balance_ntypes,
         balance_edges=args.balance_edges,
         num_trainers_per_machine=args.num_trainers_per_machine,
+        use_graphbolt=args.use_graphbolt,
     )

python/dgl/distributed/dist_context.py

@@ -241,6 +241,9 @@ def initialize(
     distributed API. For example, when used with Pytorch, users have to invoke this function
     before Pytorch's `pytorch.distributed.init_process_group`.
     """
+    print(
+        f"Initialize the distributed services with graphbolt: {use_graphbolt}"
+    )
     if net_type is not None:
         dgl_warning(
             "net_type is deprecated and will be removed in future release."