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Hua Huang

4 papers hereh-index 115 citations5 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.DC3
  • cs.LG1
same name
  • Hua Huang — 15 papers, h 8
  • Hua Huang — 8 papers, h 3
  • Hua Huang — 8 papers, h 4
  • Hua Huang — 7 papers, h 34
  • Hua Huang — 4 papers, h 6
  • Hua Huang — 4 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedA Systematic Literature Survey of Sparse Matrix-Vector Multiplication

8 citations · 8 across the 4 of their papers we have counts for

collaborators

4 papers

cs.LG2026

How Much Orthogonalization Does Muon Need?

Hua Huang

Muon optimizers improve neural-network training by replacing ill-conditioned momentum updates with approximately semi-orthogonal updates. This motivates a practical question: how m…

cs.DC2024

Cascaded Prediction and Asynchronous Execution of Iterative Algorithms on Heterogeneous Platforms

Jianhua Gao, Bingjie Liu, Yizhuo Wang +2

Owing to the diverse scales and varying distributions of sparse matrices arising from practical problems, a multitude of choices are present in the design and implementation of spa…

cs.DC2024

Precision-Aware Iterative Algorithms Based on Group-Shared Exponents of Floating-Point Numbers

Jianhua Gao, Jiayuan Shen, Yuxiang Zhang +2

Iterative solvers are frequently used in scientific applications and engineering computations. However, the memory-bound Sparse Matrix-Vector (SpMV) kernel computation hinders the…

cs.DC2024★ 8 cited

A Systematic Literature Survey of Sparse Matrix-Vector Multiplication

Jianhua Gao, Bingjie Liu, Weixing Ji +1

Sparse matrix-vector multiplication (SpMV) is a crucial computing kernel with widespread applications in iterative algorithms. Over the past decades, research on SpMV optimization…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.