21 citations · 50 across the 18 of their papers we have counts for
18 papers
IAAT: A Input-Aware Adaptive Tuning framework for Small GEMM
Jianyu Yao, Boqian Shi, Chunyang Xiang +4
GEMM with the small size of input matrices is becoming widely used in many fields like HPC and machine learning. Although many famous BLAS libraries already supported small GEMM, t…
AutoTSMM: An Auto-tuning Framework for Building High-Performance Tall-and-Skinny Matrix-Matrix Multiplication on CPUs
Chendi Li, Haipeng Jia, Hang Cao +6
In recent years, general matrix-matrix multiplication with non-regular-shaped input matrices has been widely used in many applications like deep learning and has drawn more and mor…
Large-Scale Simulation of Quantum Computational Chemistry on a New Sunway Supercomputer
Honghui Shang, Li Shen, Yi Fan +11
Quantum computational chemistry (QCC) is the use of quantum computers to solve problems in computational quantum chemistry. We develop a high performance variational quantum eigens…
An Accurate and Efficient Large-scale Regression Method through Best Friend Clustering
Kun Li, Liang Yuan, Yunquan Zhang +1
As the data size in Machine Learning fields grows exponentially, it is inevitable to accelerate the computation by utilizing the ever-growing large number of available cores provid…
An Efficient Vectorization Scheme for Stencil Computation
Kun Li, Liang Yuan, Yunquan Zhang +3
Stencil computation is one of the most important kernels in various scientific and engineering applications. A variety of work has focused on vectorization and tiling techniques, a…
Reducing Redundancy in Data Organization and Arithmetic Calculation for Stencil Computations
Kun Li, Liang Yuan, Yunquan Zhang +3
Stencil computation is one of the most important kernels in various scientific and engineering applications. A variety of work has focused on vectorization techniques, aiming at ex…
AutoFlow: Hotspot-Aware, Dynamic Load Balancing for Distributed Stream Processing
Pengqi Lu, Liang Yuan, Yunquan Zhang +2
Stream applications are widely deployed on the cloud. While modern distributed streaming systems like Flink and Spark Streaming can schedule and execute them efficiently, streaming…
AGCM-3DLF: Accelerating Atmospheric General Circulation Model via 3D Parallelization and Leap-Format
Hang Cao, Liang Yuan, He Zhang +1
The Atmospheric General Circulation Model (AGCM) has been an important research tool in the study of climate change for decades. As the demand for high-resolution simulation is bec…
Temporal Vectorization for Stencils
Liang Yuan, Hang Cao, Yunquan Zhang +3
Stencil computations represent a very common class of nested loops in scientific and engineering applications. Exploiting vector units in modern CPUs is crucial to achieving peak p…
The static parallel distribution algorithms for hybrid density-functional calculations in HONPAS package
Xinming Qin, Honghui Shang, Lei Xu +4
Hybrid density-functional calculation is one of the most commonly adopted electronic structure theory used in computational chemistry and materials science because of its balance b…
The dynamic parallel distribution algorithm for hybrid density-functional calculations in HONPAS package
Honghui Shang, Lei Xu, Baodong Wu +3
This work presents a dynamic parallel distribution scheme for the Hartree-Fock exchange~(HFX) calculations based on the real-space NAO2GTO framework. The most time-consuming electr…
Efficient Parallel Linear Scaling Method to get the Response Density Matrix in All-Electron Real-Space Density-Functional Perturbation Theory
Honghui Shang, Wanzhen Liang, Yunquan Zhang +1
The real-space density-functional perturbation theory (DFPT) for the computations of the response properties with respect to the atomic displacement and homogeneous electric field…
The Scalability for Parallel Machine Learning Training Algorithm: Dataset Matters
Daning Cheng, Hanping Zhang, Fen Xia +2
To gain a better performance, many researchers put more computing resource into an application. However, in the AI area, there is still a lack of a successful large-scale machine l…
HPC AI500: A Benchmark Suite for HPC AI Systems
Zihan Jiang, Wanling Gao, Lei Wang +10
In recent years, with the trend of applying deep learning (DL) in high performance scientific computing, the unique characteristics of emerging DL workloads in HPC raise great chal…
Using Known Information to Accelerate HyperParameters Optimization Based on SMBO
Cheng Daning, Zhang Hanping, Xia Fen +2
Automl is the key technology for machine learning problem. Current state of art hyperparameter optimization methods are based on traditional black-box optimization methods like SMB…
A Measurement Theory of Locality
Liang Yuan, Chen Ding, Peter Denning +1
Locality is a fundamental principle used extensively in program and system optimization. It can be measured in many ways. This paper formalizes the metrics of locality into a measu…
Asynchronous COMID: the theoretic basis for transmitted data sparsification tricks on Parameter Server
Daning Cheng, Shigang Li, Yunquan Zhang
Asynchronous FTRL-proximal and L2 norm done at server are two widely used tricks in Parameters Server which is an implement of delayed SGD. Their commonness is leaving parts of upd…
Optimized Password Recovery for Encrypted RAR on GPUs
Xiaojing An, Haojun Zhao, Lulu Ding +2
RAR uses classic symmetric encryption algorithm SHA-1 hashing and AES algorithm for encryption, and the only method of password recovery is brute force, which is very time-consumin…