Update README.md (#818)

Fix GNN dataset from IGBFull to IGBH-Full

Author: ShriyaRishab

README.md

@@ -52,7 +52,7 @@ Some these benchmarks are rather slow or take a long time to run on the referenc
 | llama2_70b_lora | [llama2_70b_lora](https://github.com/mlcommons/training/tree/master/llama2_70b_lora) | pytorch | SCROLLS GovReport | 70B
 | llama3.1_405b | [large_language_model_pretraining](https://github.com/mlcommons/training/tree/master/large_language_model_pretraining) | NeMo | C4 | 405B
 | dlrm_dcnv2 | [recommendation_v2](https://github.com/mlcommons/training/tree/master/recommendation_v2/torchrec_dlrm) | torchrec | Criteo 3.5TB multi-hot | 167M
-| rgat | [graph_neural_network](https://github.com/mlcommons/training/tree/master/graph_neural_network) | GLT | IGBFull | 25M
+| rgat | [graph_neural_network](https://github.com/mlcommons/training/tree/master/graph_neural_network) | GLT | IGBH-Full | 25M
 
 *Framework here is given for the reference implementation. Submitters are free to use their own frameworks to run the benchmark.
 
@@ -71,7 +71,7 @@ Some these benchmarks are rather slow or take a long time to run on the referenc
 | llama3.1_405b | [large_language_model_pretraining](https://github.com/mlcommons/training/tree/master/large_language_model_pretraining) | NeMo | C4 | 405B
 | llama2_70b_lora | [llama2_70b_lora](https://github.com/mlcommons/training/tree/master/llama2_70b_lora) | pytorch | SCROLLS GovReport | 70B
 | dlrm_dcnv2 | [recommendation_v2](https://github.com/mlcommons/training/tree/master/recommendation_v2/torchrec_dlrm) | torchrec | Criteo 3.5TB multi-hot | 167M
-| rgat | [graph_neural_network](https://github.com/mlcommons/training/tree/master/graph_neural_network) | GLT | IGBFull | 25M
+| rgat | [graph_neural_network](https://github.com/mlcommons/training/tree/master/graph_neural_network) | GLT | IGBH-Full | 25M
 
 # MLPerf Training v4.1 (Submission Deadline Oct 11, 2024)
 *Framework here is given for the reference implementation. Submitters are free to use their own frameworks to run the benchmark.
@@ -84,7 +84,7 @@ Some these benchmarks are rather slow or take a long time to run on the referenc
 | GPT3 | [language/llm](https://github.com/mlcommons/training/tree/master/large_language_model) | paxml,megatron-lm | C4 | 175B
 | LLama2 70B-LoRA | [language/LLM fine-tuning](https://github.com/mlcommons/training/tree/master/llama2_70b_lora) | pytorch | SCROLLS GovReport | 70B
 | DLRMv2 | [recommendation](https://github.com/mlcommons/training/tree/master/recommendation_v2/torchrec_dlrm) | torchrec | Criteo 3.5TB multi-hot | 167M
-| RGAT | [GNN](https://github.com/mlcommons/training/tree/master/graph_neural_network) | pytorch | IGBFull | 25M 
+| RGAT | [GNN](https://github.com/mlcommons/training/tree/master/graph_neural_network) | pytorch | IGBH-Full | 25M 
 
 *Note model parameter count is not the same as active parameter that are being trained in the benchmark.