BAG (Basis Alternative Matrix Multiplication on GPUs), a GPU-oriented implementation of ABMM for the NVIDIA Ampere architecture is presented, designed to shrink workspace and eliminate redundant global-memory traffic, and introduce a cost-model-based recursion policy together with a Roofline-guided blocking strategy to...
Yao Liu, Ye-Wen Li, Zhong-Hai Zhang et al.· Proceedings of the Internati...· 0 citations
This work proposes Bullseye Hash, a novel hash table designed to efficiently support SpTC computations and provides guidance on configuring data object representations based on their specific characteristics, considering both algorithmic complexity and cache efficiency.
Guo-Feng Feng, Ze-Cheng Li, Ming-Zhen Li et al.· ACM Transactions on Architec...· 0 citations
The results demonstrate that the flow-matching generative paradigm based on 3D molecular structure evolution can ensure the physical plausibility of reactions and provide directly verifiable predictions for tasks such as drug design and catalystdesign that rely on accurate 3D structures.
En-Ji Li, Si-Yu Hu, Xiao Tian et al.· AI for Science· 0 citations
Matrix multiplication is a fundamental computation kernel in many parallel and sequential scientific applications. We target FP32 matrix multiplication on GPUs, a setting required by numerous HPC and scientific workloads. Alternative Basis Matrix Multiplication (ABMM) is a practical Strassen-like algorithm that reduces...
Yao Liu, Ye-Wen Li, Zhonghai Zhang et al.· Proceedings of the Internati...· 0 citations
This paper proposes AtomFlow, a holistic acceleration for a representative GNN-based MD model on the Fugaku supercomputer, and redesigns the inference workflow with a framework-free implementation to avoid the overhead of the PyTorch framework on Fugaku.
Yi-Ming Du, Ming-Zhen Li, Li-Jun Liu et al.· Proceedings of the Internati...· 0 citations
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