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20232025
most citedAnatomy of High-Performance GEMM with Online Fault Tolerance on GPUs

13 citations · 30 across the 11 of their papers we have counts for

collaborators

12 papers

astro-ph.IM2025

cuHPX: GPU-Accelerated Differentiable Spherical Harmonic Transforms on HEALPix Grids

Xiaopo Cheng, Akshay Subramaniam, Shixun Wu +1

HEALPix (Hierarchical Equal Area isoLatitude Pixelization) is a widely adopted spherical grid system in astrophysics, cosmology, and Earth sciences. Its equal-area, iso-latitude st…

cs.DC2025★ 6 cited

Boosting Scientific Error-Bounded Lossy Compression through Optimized Synergistic Lossy-Lossless Orchestration

Shixun Wu, Jinwen Pan, Jinyang Liu +8

As high-performance computing architectures evolve, more scientific computing workflows are being deployed on advanced computing platforms such as GPUs. These workflows can produce…

cs.DC2025

TurboFNO: High-Performance Fourier Neural Operator with Fused FFT-GEMM-iFFT on GPU

Shixun Wu, Yujia Zhai, Huangliang Dai +4

Fourier Neural Operators (FNO) are widely used for learning partial differential equation solution operators. However, FNO lacks architecture-aware optimizations,with its Fourier l…

cs.DC2025★ 1 cited

FT-Transformer: Resilient and Reliable Transformer with End-to-End Fault Tolerant Attention

Huangliang Dai, Shixun Wu, Jiajun Huang +4

Transformer models rely on High-Performance Computing (HPC) resources for inference, where soft errors are inevitable in large-scale systems, making the reliability of the model pa…

cs.DC2024★ 1 cited

TurboFFT: Co-Designed High-Performance and Fault-Tolerant Fast Fourier Transform on GPUs

Shixun Wu, Yujia Zhai, Jinyang Liu +6

GPU-based fast Fourier transform (FFT) is extremely important for scientific computing and signal processing. However, we find the inefficiency of existing FFT libraries and the ab…

cs.DC2024★ 1 cited

DGRO: Diameter-Guided Ring Optimization for Integrated Research Infrastructure Membership

Shixun Wu, Krishnan Raghavan, Sheng Di +2

Logical ring is a core component in membership protocol. However, the logic ring fails to consider the underlying physical latency, resulting in a high diameter. To address this is…

cs.DC2024

FT K-means: A High-Performance K-means on GPU with Fault Tolerance

Shixun Wu, Yitong Ding, Yujia Zhai +8

K-means is a widely used algorithm in clustering, however, its efficiency is primarily constrained by the computational cost of distance computing. Existing implementations suffer…

cs.DC2024★ 2 cited

TurboFFT: A High-Performance Fast Fourier Transform with Fault Tolerance on GPU

Shixun Wu, Yujia Zhai, Jinyang Liu +6

The Fast Fourier Transform (FFT), as a core computation in a wide range of scientific applications, is increasingly threatened by reliability issues. In this paper, we introduce Tu…

cs.DC2023★ 1 cited

cuSZ-: High-Ratio Scientific Lossy Compression on GPUs with Optimized Multi-Level Interpolation

Jinyang Liu, Jiannan Tian, Shixun Wu +10

Error-bounded lossy compression is a critical technique for significantly reducing scientific data volumes. Compared to CPU-based compressors, GPU-based compressors exhibit substan…

cs.DC2023

High-performance Effective Scientific Error-bounded Lossy Compression with Auto-tuned Multi-component Interpolation

Jinyang Liu, Sheng Di, Kai Zhao +7

Error-bounded lossy compression has been identified as a promising solution for significantly reducing scientific data volumes upon users' requirements on data distortion. For the…

cs.DC2023★ 5 cited

FT-GEMM: A Fault Tolerant High Performance GEMM Implementation on x86 CPUs

Shixun Wu, Yujia Zhai, Jiajun Huang +2

General matrix/matrix multiplication (GEMM) is crucial for scientific computing and machine learning. However, the increased scale of the computing platforms raises concerns about…

cs.DC2023★ 13 cited

Anatomy of High-Performance GEMM with Online Fault Tolerance on GPUs

Shixun Wu, Yujia Zhai, Jinyang Liu +4

General Matrix Multiplication (GEMM) is a crucial algorithm for various applications such as machine learning and scientific computing, and an efficient GEMM implementation is esse…