activity
20162022
most citedCharacterizing Scalability of Sparse Matrix-Vector Multiplications on Phytium FT-2000+ Many-cores

12 citations · 14 across the 3 of their papers we have counts for

collaborators

8 papers

cs.PL2022

Programming Bare-Metal Accelerators with Heterogeneous Threading Models: A Case Study of Matrix-3000

Jianbin Fang, Peng Zhang, Chun Huang +4

As the hardware industry moves towards using specialized heterogeneous many-cores to avoid the effects of the power wall, software developers are finding it hard to deal with the c…

cs.DC20202 cited

Parallel Programming Models for Heterogeneous Many-Cores : A Survey

Jianbin Fang, Chun Huang, Tao Tang +1

Heterogeneous many-cores are now an integral part of modern computing systems ranging from embedding systems to supercomputers. While heterogeneous many-core design offers the pote…

cs.DC2020

Optimizing Streaming Parallelism on Heterogeneous Many-Core Architectures: A Machine Learning Based Approach

Peng Zhang, Jianbin Fang, Canqun Yang +3

This article presents an automatic approach to quickly derive a good solution for hardware resource partition and task granularity for task-based parallel applications on heterogen…

cs.DC201912 cited

Characterizing Scalability of Sparse Matrix-Vector Multiplications on Phytium FT-2000+ Many-cores

Donglin Chen, Jianbin Fang, Chuanfu Xu +2

Understanding the scalability of parallel programs is crucial for software optimization and hardware architecture design. As HPC hardware is moving towards many-core design, it bec…

cs.LG2018

To Compress, or Not to Compress: Characterizing Deep Learning Model Compression for Embedded Inference

Qing Qin, Jie Ren, Jialong Yu +6

The recent advances in deep neural networks (DNNs) make them attractive for embedded systems. However, it can take a long time for DNNs to make an inference on resource-constrained…

cs.MS2018

Optimizing Sparse Matrix-Vector Multiplication on Emerging Many-Core Architectures

Shizhao Chen, Jianbin Fang, Donglin Chen +2

Sparse matrix vector multiplication (SpMV) is one of the most common operations in scientific and high-performance applications, and is often responsible for the application perfor…