Performance Impact Applying Compression Format to Sparse Matrix on Kernel Polynomial Method Using GPU. - Shixun Zhang; Shinichi Yamagiwa; Masahiko Okumura; Seiji Yunoki (ICNC, 2011)

Performance Acceleration of Kernel Polynomial Method Applying Graphics Processing Units. - Shixun Zhang; Shinichi Yamagiwa; Masahiko Okumura; Seiji Yunoki (IPDPS Workshops, 2011)

GPU-Based Parallelization of Kernel Polynomial Method for Solving LDOS. - Shixun Zhang; Shinichi Yamagiwa; Seiji Yunoki (SC Companion, 2012)

Parallelizing Kernel Polynomial Method Applying Graphics Processing Units. - Shixun Zhang; Shinichi Yamagiwa; Masahiko Okumura; Seiji Yunoki (Int. J. Netw. Comput., 2012)

CarSh: A Commandline Execution Support for Stream-Based Acceleration Environment. - Shinichi Yamagiwa; Shixun Zhang (ICCS, 2013)

Exploiting Execution Order and Parallelism from Processing Flow Applying Pipeline-Based Programming Method on Manycore Accelerators. - Shinichi Yamagiwa; Ryo Jozaki; Shixun Zhang; Ryo Zaizen; Dewen Xu (ICPP, 2013)

Scenario-Based Execution Method for Massively Parallel Accelerators. - Shinichi Yamagiwa; Shixun Zhang (TrustCom/ISPA/IUCC, 2013)

Kernel Polynomial Method on GPU. - Shixun Zhang; Shinichi Yamagiwa; Masahiko Okumura; Seiji Yunoki (Int. J. Parallel Program., 2013)

FMore: An Incentive Scheme of Multi-dimensional Auction for Federated Learning in MEC. - Rongfei Zeng; Shixun Zhang; Jiaqi Wang; Xiaowen Chu 001 (ICDCS, 2020)

Tidal Flat Extraction and Change Analysis Based on the RF-W Model: A Case Study of Jiaozhou Bay, East China. - Jinfeng Yan; Shiyi Zhao; Fenzhen Su; Jiaxue Du; Pengfei Feng; Shixun Zhang (Remote. Sens., 2021)

A High Efficiency 14-28 Gb/s Tunable Receiver Analog Front-End in 65 nm CMOS Technology. - Shunyu Li; Guangyong Chu; Kezhen Zhu; Pengfei Niu; Shixun Zhang; Guofeng Yang (J. Circuits Syst. Comput., 2024)

A 0.16 pJ/bit 32 Gb/s NRZ Equalizer with Fixed Peak Frequency and Tunable Gain in 65 nm CMOS. - Wenye Lin; Guang Yong Chu; Zhenjiang Sun; Shunyu Li; Chaoqun Ma; Shixun Zhang (J. Circuits Syst. Comput., 2025)