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, Zhong-Hai Zhang et al.· Proceedings of the Internati...· 0 citations
Sparse tensor contraction (SpTC) is a critical operation in high-performance applications. However, the high dimensionality and inherent sparsity of tensors make the performance improvement of SpTC a fundamentally challenging problem. In this paper, we propose Bullseye Hash, a novel hash table designed to efficiently s...
Guo-Feng Feng, Ze-Cheng Li, Ming-Zhen Li et al.· ACM Transactions on Architec...· 0 citations
Accurately predicting the outcomes of chemical reactions is of great significance for many applications ranging from drug discovery to catalyst design, yet the development of generative machine-learning models for materials science and chemical processes remains at an early stage. Current mainstream approaches typicall...
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
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