13 citations · 21 across the 6 of their papers we have counts for
5 papers
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…
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…
Accelerating MPI Collectives with Process-in-Process-based Multi-object Techniques
Jiajun Huang, Kaiming Ouyang, Yujia Zhai +8
In the exascale computing era, optimizing MPI collective performance in high-performance computing (HPC) applications is critical. Current algorithms face performance degradation d…
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…
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…