Feb 4, 2024 · Our proposed methods, all combined, give the fastest MLPerf BERT training of 25.1 (22.3) seconds on 1,024 NVIDIA A100 GPUs, which is 1.33x (1.13 ...
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Feb 4, 2024 · We propose two new ideas, (1) local presorting based on dataset stratification for load balancing and (2) bucket-wise gradient clipping before ...
Feb 5, 2024 · Exciting news from SW lee. A new paper titled "Breaking MLPerf Training: A Case Study on Optimizing BERT" has been published on arXiv.
Sep 28, 2024 · Breaking MLPerf Training: A Case Study on Optimizing BERT. CoRR abs/2402.02447 (2024); 2023. [c6]. view. electronic edition via DOI ...
Jun 27, 2023 · These optimizations combined boost single-node performance on BERT by 17% compared to the H100 preview submission in MLPerf Training v2.1.
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Breaking MLPerf Training: A Case Study on Optimizing BERT ... Speeding up the large-scale distributed training is challenging in that it requires improving ...
Breaking MLPerf Training: A Case Study on Optimizing BERT. SY Yongdeok Kim, Jaehyung Ahn, Myeongwoo Kim, Changin Choi, Heejae Kim ... https://arxiv.org/abs/ ...
Breaking MLPerf Training: A Case Study on Optimizing BERT ... Speeding up the large-scale distributed training is challenging in that it requires improving ...
Nov 9, 2022 · In this round, we implemented a different version of fused multihead attention that is more efficient for BERT use case, inspired by the ...
Missing: Study | Show results with:Study
Breaking MLPerf Training: A Case Study on Optimizing BERT. SY Yongdeok Kim, Jaehyung Ahn, Myeongwoo Kim, Changin Choi, Heejae Kim ... https://arxiv.org/abs ...