103 citations · 141 across the 17 of their papers we have counts for
17 papers
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…
ZCCL: Significantly Improving Collective Communication With Error-Bounded Lossy Compression
Jiajun Huang, Sheng Di, Xiaodong Yu +12
With the ever-increasing computing power of supercomputers and the growing scale of scientific applications, the efficiency of MPI collective communication turns out to be a critic…
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…
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…
gZCCL: Compression-Accelerated Collective Communication Framework for GPU Clusters
Jiajun Huang, Sheng Di, Xiaodong Yu +11
GPU-aware collective communication has become a major bottleneck for modern computing platforms as GPU computing power rapidly rises. A traditional approach is to directly integrat…
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…
An Optimized Error-controlled MPI Collective Framework Integrated with Lossy Compression
Jiajun Huang, Sheng Di, Xiaodong Yu +11
With the ever-increasing computing power of supercomputers and the growing scale of scientific applications, the efficiency of MPI collective communications turns out to be a criti…
ByteTransformer: A High-Performance Transformer Boosted for Variable-Length Inputs
Yujia Zhai, Chengquan Jiang, Leyuan Wang +5
Transformers have become keystone models in natural language processing over the past decade. They have achieved great popularity in deep learning applications, but the increasing…
An Efficient and Accurate Rough Set for Feature Selection, Classification and Knowledge Representation
Shuyin Xia, Xinyu Bai, Guoyin Wang +4
This paper present a strong data mining method based on rough set, which can realize feature selection, classification and knowledge representation at the same time. Rough set has…
A Unified Granular-ball Learning Model of Pawlak Rough Set and Neighborhood Rough Set
Shuyin Xia, Cheng Wang, Guoyin Wang +5
Pawlak rough set and neighborhood rough set are the two most common rough set theoretical models. Pawlak can use equivalence classes to represent knowledge, but it cannot process c…
Accelerating Encrypted Computing on Intel GPUs
Yujia Zhai, Mohannad Ibrahim, Yiqin Qiu +4
Homomorphic Encryption (HE) is an emerging encryption scheme that allows computations to be performed directly on encrypted messages. This property provides promising applications…
FT-BLAS: A High Performance BLAS Implementation With Online Fault Tolerance
Yujia Zhai, Elisabeth Giem, Quan Fan +3
Basic Linear Algebra Subprograms (BLAS) is a core library in scientific computing and machine learning. This paper presents FT-BLAS, a new implementation of BLAS routines that not…
FT-CNN: Algorithm-Based Fault Tolerance for Convolutional Neural Networks
Kai Zhao, Sheng Di, Sihuan Li +6
Convolutional neural networks (CNNs) are becoming more and more important for solving challenging and critical problems in many fields. CNN inference applications have been deploye…
Normalization of Input-output Shared Embeddings in Text Generation Models
Jinyang Liu, Yujia Zhai, Zizhong Chen
Neural Network based models have been state-of-the-art models for various Natural Language Processing tasks, however, the input and output dimension problem in the networks has sti…