6 citations · 13 across the 12 of their papers we have counts for
6 papers · 1 filter
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…
QPET: A Versatile and Portable Quantity-of-Interest-Preservation Framework for Error-Bounded Lossy Compression
Jinyang Liu, Pu Jiao, Kai Zhao +3
Error-bounded lossy compression has been widely adopted in many scientific domains because it can address the challenges in storing, transferring, and analyzing unprecedented amoun…
LCP: Enhancing Scientific Data Management with Lossy Compression for Particles
Longtao Zhang, Ruoyu Li, Congrong Ren +10
Many scientific applications opt for particles instead of meshes as their basic primitives to model complex systems composed of billions of discrete entities. Such applications spa…
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…
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…
A Survey on Error-Bounded Lossy Compression for Scientific Datasets
Sheng Di, Jinyang Liu, Kai Zhao +23
Error-bounded lossy compression has been effective in significantly reducing the data storage/transfer burden while preserving the reconstructed data fidelity very well. Many error…