**Benchmarking with dim = 2, nodes = 1, 2, gpus = 8, batch_size = 128 can be used for node health check.**
- The expected throughput for dim = 2, nodes = 1, gpus = 8, batch_size = 128 would be 4700 ± 500 (TF32).
- The expected throughput for dim = 2, nodes = 1, gpus = 1, batch_size = 256 would be 670 ± 10 (TF32).
- The expected throughput for dim = 2, nodes = 1, gpus = 4, batch_size = 256 would be 2600 ± 100 (TF32).
- The expected throughput for dim = 2, nodes = 1, gpus = 8, batch_size = 256 would be 5150 ± 150 (TF32).
- The expected throughput for dim = 2, nodes = 2, gpus = 16, batch_size = 128 would be 9250 ± 150 (TF32).
**Observation 3**: Ideally, the improvement of throughput would be linear when batch_size increases. In practice, throughtput stays below the ideal curve when batch_size > 16.
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@@ -118,4 +119,4 @@ when batch_size is large (16, 32, 64, 128), throughput_amp > throughput_tf32.
- For multi-node benchmarking, we need to use "srun" command; also, the line "#SBATCH --ntasks-per-node=8" has to been added. Otherwise the process will hang.
- Benchmarking with dim = 2, nodes = 1, gpus = 8, batch_size = 128 takes ~2mins.
If we want to finish it within a minute, we can change the number of batches from 150 (the default value) to a smaller number. Or we can try some smaller datasets.
-On single node, max batch_size is 256; on multi-node, max batch_size is 128.
-Use as large batch_size as possible for a more stable benchmark result.
