26 citations · 92 across the 11 of their papers we have counts for
11 papers
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…
HEAT: A Highly Efficient and Affordable Training System for Collaborative Filtering Based Recommendation on CPUs
Chengming Zhang, Shaden Smith, Baixi Sun +6
Collaborative filtering (CF) has been proven to be one of the most effective techniques for recommendation. Among all CF approaches, SimpleX is the state-of-the-art method that ado…
FZ-GPU: A Fast and High-Ratio Lossy Compressor for Scientific Computing Applications on GPUs
Boyuan Zhang, Jiannan Tian, Sheng Di +5
Today's large-scale scientific applications running on high-performance computing (HPC) systems generate vast data volumes. Thus, data compression is becoming a critical technique…
GPULZ: Optimizing LZSS Lossless Compression for Multi-byte Data on Modern GPUs
Boyuan Zhang, Jiannan Tian, Sheng Di +4
Today's graphics processing unit (GPU) applications produce vast volumes of data, which are challenging to store and transfer efficiently. Thus, data compression is becoming a crit…
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…
SOLAR: A Highly Optimized Data Loading Framework for Distributed Training of CNN-based Scientific Surrogates
Baixi Sun, Xiaodong Yu, Chengming Zhang +7
CNN-based surrogates have become prevalent in scientific applications to replace conventional time-consuming physical approaches. Although these surrogates can yield satisfactory r…
SZx: an Ultra-fast Error-bounded Lossy Compressor for Scientific Datasets
Xiaodong Yu, Sheng Di, Kai Zhao +4
Today's scientific high performance computing (HPC) applications or advanced instruments are producing vast volumes of data across a wide range of domains, which introduces a serio…
Optimizing Huffman Decoding for Error-Bounded Lossy Compression on GPUs
Cody Rivera, Sheng Di, Jiannan Tian +3
More and more HPC applications require fast and effective compression techniques to handle large volumes of data in storage and transmission. Not only do these applications need to…
High-Performance Ptychographic Reconstruction with Federated Facilities
Tekin Bicer, Xiaodong Yu, Daniel J. Ching +5
Beamlines at synchrotron light source facilities are powerful scientific instruments used to image samples and observe phenomena at high spatial and temporal resolutions. Typically…
Scalable and accurate multi-GPU based image reconstruction of large-scale ptychography data
Xiaodong Yu, Viktor Nikitin, Daniel J. Ching +3
While the advances in synchrotron light sources, together with the development of focusing optics and detectors, allow nanoscale ptychographic imaging of materials and biological s…
Optimizing Error-Bounded Lossy Compression for Scientific Data on GPUs
Jiannan Tian, Sheng Di, Xiaodong Yu +7
Error-bounded lossy compression is a critical technique for significantly reducing scientific data volumes. With ever-emerging heterogeneous high-performance computing (HPC) archit…