[REVIEW] Add Pure DGL Dataloading benchmark

[VibhuJawa]

This PR adds the DGL data loading benchmark:

Arguments supported:

• dataset_path: path to the dataset
• replication_factors: replication factors for number of edges
• fanouts: fanouts
• batch_sizes: batch sizes

python3 dgl_dataloading.py --dataset_path "/datasets/abarghi/ogbn_papers100M" \
--replication_factors "1,2,4" \
--fanouts "25_25,10_10_10,5_10_20" \
--batch_sizes "512,1024"

This produces the following results on a V100:

Fanout	Batch Size	Data Loading Time per Epoch	Data Loading Time per Batch	Number of Edges	Number of Batches	Replication Factor
[25, 25]	512	9.48	0.0031	1615685872	3022	1
[25, 25]	1024	6.39	0.0042	1615685872	1511	1
[10, 10, 10]	512	15.91	0.0053	1615685872	3022	1
[10, 10, 10]	1024	11.64	0.0077	1615685872	1511	1
[5, 10, 20]	512	17.73	0.0059	1615685872	3022	1
[5, 10, 20]	1024	13.52	0.0089	1615685872	1511	1
[25, 25]	512	19.44	0.0032	3231371744	6043	2
[25, 25]	1024	12.98	0.0043	3231371744	3022	2
[10, 10, 10]	512	32.88	0.0054	3231371744	6043	2
[10, 10, 10]	1024	24.35	0.0081	3231371744	3022	2
[5, 10, 20]	512	38.35	0.0063	3231371744	6043	2
[5, 10, 20]	1024	28.93	0.0096	3231371744	3022	2
[25, 25]	512	37.31	0.0031	6462743488	12085	4
[25, 25]	1024	25.15	0.0042	6462743488	6043	4
[10, 10, 10]	512	64.29	0.0053	6462743488	12085	4
[10, 10, 10]	1024	47.13	0.0078	6462743488	6043	4
[5, 10, 20]	512	72.90	0.0060	6462743488	12085	4
[5, 10, 20]	1024	56.70	0.0094	6462743488	6043	4
[25, 25]	512	80.99	0.0034	12925486976	24169	8
[25, 25]	1024	50.89	0.0042	12925486976	12085	8
[10, 10, 10]	512	129.49	0.0054	12925486976	24169	8
[10, 10, 10]	1024	93.66	0.0078	12925486976	12085	8
[5, 10, 20]	512	143.45	0.0059	12925486976	24169	8
[5, 10, 20]	1024	110.22	0.0091	12925486976	12085	8

[alexbarghi-nv]

👍

[VibhuJawa]

I would like to get a look from @tingyu66 here too

[tingyu66]

Looks good to me. If being nitpicking, I'd like to fix random seed (with dgl.seed() and torch.manual_seed()) for all benchmarks.

[VibhuJawa]

@tingyu66 , Added seed with commit: f99a518

@alexbarghi-nv , I think we should be good to merge.

[VibhuJawa]

Just dropping updated numbers for awareness as we use this in comparisons.

 python3 dgl_benchmark.py --dataset_path "/datasets/abarghi/ogbn_papers100M" --replication_factors "2,4" --fanouts "10_10_10" --batch_sizes "512,1024"

Running dgl dataloading benchmark with the following parameters:
Dataset path = /datasets/abarghi/ogbn_papers100M
Replication factors = [2, 4]
Fanouts = [[10, 10, 10]]
Batch sizes = [512, 1024]
Use UVA = True
==============================================
Loading edge index for edge type paper__cites__paperfor replication factor = 2
Graph Data compiled
Replication factor = 2
G has 3231371744 edges and took  47.45 seconds to load
Creating dataloader
Time to create dataloader = 112.72 seconds
Dataloading completed
Fanout = [10, 10, 10], batch_size = 512
Time taken 23.96  seconds for num batches 6043
==============================================
Creating dataloader
Time to create dataloader = 0.01 seconds
Dataloading completed
Fanout = [10, 10, 10], batch_size = 1024
Time taken 16.75  seconds for num batches 3022
==============================================
Benchmark completed for replication factor =  2
==============================================
Loading edge index for edge type paper__cites__paperfor replication factor = 4
Graph Data compiled
Replication factor = 4
G has 6462743488 edges and took  126.01 seconds to load
Creating dataloader
Time to create dataloader = 213.80 seconds
Dataloading completed
Fanout = [10, 10, 10], batch_size = 512
Time taken 48.75  seconds for num batches 12085
==============================================
Creating dataloader
Time to create dataloader = 0.01 seconds
Dataloading completed
Fanout = [10, 10, 10], batch_size = 1024
Time taken 33.81  seconds for num batches 6043
==============================================
Benchmark completed for replication factor =  4
==============================================
Benchmark completed for all replication factors
==============================================

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[alexbarghi-nv]

/ok to test

[BradReesWork]

/ok to test

[BradReesWork]

/okay to test

[BradReesWork]

/merge