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Preliminary Results of the MLPerf BERT Inference Benchmark on AMD Instinct GPUs
Published in PEARC 2024, 2024
MLPerf BERT Inference Benchmark results on AMD Instinct GPUs
Recommended citation: Z. Wang, K. Vu, M. Hodak, A. Mehrotra, F. Gutierrez, K. Smith, G. Seo, et al. "Preliminary Results of the MLPerf BERT Inference Benchmark on AMD Instinct GPUs." Practice and Experience in Advanced Research Computing 2024: Human Powered Computing.
Omniwise: Predicting GPU Kernels Performance with LLMs
Published in arXiv preprint, 2025
Using large language models to predict GPU kernel performance
Recommended citation: Z. Wang, C. Ramos, M. A. Awad, K. Lowery. "Omniwise: Predicting GPU Kernels Performance with LLMs." arXiv preprint arXiv:2506.20886.
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Quiet Feature Learning in Algorithmic Tasks
Published in AAAI 2026 (Oral), 2026
AAAI 2026 (Oral).
Recommended citation: P. Naidu, Z. Wang, L. Bergen, R. Paturi. "Quiet Feature Learning in Algorithmic Tasks." AAAI Conference on Artificial Intelligence (AAAI), 2026. Oral.
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The Surprising Soupability of Documents in State Space Models
Published in COLM 2026, 2026
Accepted to COLM 2026. Encoding documents independently and pooling their states in Mamba2 models.
Recommended citation: Y. Jafari*, Z. Wang*, L. Bergen, T. Berg-Kirkpatrick. "The Surprising Soupability of Documents in State Space Models." Conference on Language Modeling (COLM), 2026.
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X-MoE-4D: Breaking the Scaling Barrier for Trillion Parameter MoEs on Hierarchical HPC Systems
Published in SC 2026, 2026
Accepted to SC26. Scaling trillion-parameter Mixture-of-Experts training on hierarchical HPC systems.
Recommended citation: Z. Wang, L. Jing, E. Herron, S. Dash, F. Wang, M. Zhang. "X-MoE-4D: Breaking the Scaling Barrier for Trillion Parameter MoEs on Hierarchical HPC Systems." The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC26), 2026.