296 citations · 963 across the 52 of their papers we have counts for
10 papers · 1 filter
LCFI: A Fault Injection Tool for Studying Lossy Compression Error Propagation in HPC Programs
Baodi Shan, Aabid Shamji, Jiannan Tian +2
Error-bounded lossy compression is becoming more and more important to today's extreme-scale HPC applications because of the ever-increasing volume of data generated because it has…
A Novel Memory-Efficient Deep Learning Training Framework via Error-Bounded Lossy Compression
Sian Jin, Guanpeng Li, Shuaiwen Leon Song +1
Deep neural networks (DNNs) are becoming increasingly deeper, wider, and non-linear due to the growing demands on prediction accuracy and analysis quality. When training a DNN mode…
MGARD+: Optimizing Multilevel Methods for Error-bounded Scientific Data Reduction
Xin Liang, Ben Whitney, Jieyang Chen +8
Data management is becoming increasingly important in dealing with the large amounts of data produced by large-scale scientific simulations and instruments. Existing multilevel com…
ClickTrain: Efficient and Accurate End-to-End Deep Learning Training via Fine-Grained Architecture-Preserving Pruning
Chengming Zhang, Geng Yuan, Wei Niu +8
Convolutional neural networks (CNNs) are becoming increasingly deeper, wider, and non-linear because of the growing demand on prediction accuracy and analysis quality. The wide and…
Speculative Container Scheduling for Deep Learning Applications in a Kubernetes Cluster
Ying Mao, Yuqi Fu, Wenjia Zheng +3
In the past decade, we have witnessed a dramatically increasing volume of data collected from varied sources. The explosion of data has transformed the world as more information is…
Revisiting Huffman Coding: Toward Extreme Performance on Modern GPU Architectures
Jiannan Tian, Cody Rivera, Sheng Di +4
Today's high-performance computing (HPC) applications are producing vast volumes of data, which are challenging to store and transfer efficiently during the execution, such that da…
cuSZ: An Efficient GPU-Based Error-Bounded Lossy Compression Framework for Scientific Data
Jiannan Tian, Sheng Di, Kai Zhao +8
Error-bounded lossy compression is a state-of-the-art data reduction technique for HPC applications because it not only significantly reduces storage overhead but also can retain h…
Understanding GPU-Based Lossy Compression for Extreme-Scale Cosmological Simulations
Sian Jin, Pascal Grosset, Christopher M. Biwer +4
To help understand our universe better, researchers and scientists currently run extreme-scale cosmology simulations on leadership supercomputers. However, such simulations can gen…
RTMobile: Beyond Real-Time Mobile Acceleration of RNNs for Speech Recognition
Peiyan Dong, Siyue Wang, Wei Niu +8
Recurrent neural networks (RNNs) based automatic speech recognition has nowadays become prevalent on mobile devices such as smart phones. However, previous RNN compression techniqu…
TSM2X: High-Performance Tall-and-Skinny Matrix-Matrix Multiplication on GPUs
Cody Rivera, Jieyang Chen, Nan Xiong +2
Linear algebra operations have been widely used in big data analytics and scientific computations. Many works have been done on optimizing linear algebra operations on GPUs with re…