张为华 - 复旦大学 - 计算机科学技术学院

个人简介

张为华，教授，博导。2007年复旦大学获博士学位，博士论文获“计算机学会优秀博士论文优秀奖”。作为项目负责人承担国家自然科学基金项目、科技支撑项目，上海市科委重点项目和863课题等项目。在TC、TPDS、MICRO等高水平国际会议和期刊发表论文60余篇。研究工作获得ICPP 2015和 ACA 2014 最佳论文奖。奖项 2015 ICPP最佳论文 2014 ACA最佳论文 2007 计算机学会优秀博士论文奖

研究领域

体系结构、系统软件和编译优化等

近期论文

查看导师新发文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

Jinhu Jiang, Chaoyi Liang, Rongchao Dong, Zhaohui Yang, Zhongjun Zhou, Wenwen Wang, Pen-Chung Yew, Weihua Zhang. A System-Level Dynamic Binary Translator Using Automatically-Learned Translation Rules. To appear in IEEE/ACM International Symposium on Code Generation and Optimization (CGO 2024, CCF B) YiJing Song, HuaSheng Dai, JinHu Jiang and WeiHua Zhang. Multikernel: Operating System Solution to Generalized Functional Safety. Security and Safety 2023; 2: 2023007. Chenyang Jiao, Weihua Zhang, Li Shen. Communication Optimizations for State-vector Quantum Simulator on CPU+GPU Clusters. To appear on the Proceedings of the 52th International Conference on Parallel Processing. (ICPP 2023) Weihua Zhang, Chuanlei Zhao, Lu Peng, Yuzhe Lin, Fengzhe Zhang, Yunping Lu. Boosting Performance and QoS for Concurrent GPU B+trees by Combining-based Synchronization. Proceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming (PPoPP), 2023, pp. 1-13, doi: 10.1145/3572848.3577474 J. Jiang et al., More with Less – Deriving More Translation Rules with Less Training Data for DBTs Using Parameterization, 2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO), 2020, pp. 415-426, doi: 10.1109/MICRO50266.2020.00043. S. Chen, L. Liu, W. Zhang and L. Peng, Architectural Support for NVRAM Persistence in GPUs, in IEEE Transactions on Parallel and Distributed Systems, vol. 31, no. 5, pp. 1107-1120, 1 May 2020, doi: 10.1109/TPDS.2019.2960233. W. Zhang, Z. Yan, Y. Lin, C. Zhao and L. Peng, A High Throughput B+tree for SIMD Architectures, in IEEE Transactions on Parallel and Distributed Systems, vol. 31, no. 3, pp. 707-720, 1 March 2020, doi: 10.1109/TPDS.2019.2942918. Changheng Song, Wenwen Wang, Pen-Chung Yew, Antonia Zhai, and Weihua Zhang. 2019. Unleashing the power of learning: an enhanced learning-based approach for dynamic binary translation. In Proceedings of the 2019 USENIX Conference on Usenix Annual Technical Conference (USENIX ATC '19). USENIX Association, USA, 77–89. Zhaofeng Yan, Yuzhe Lin, Lu Peng, and Weihua Zhang. 2019. Harmonia: a high throughput B+tree for GPUs. In Proceedings of the 24th Symposium on Principles and Practice of Parallel Programming (PPoPP '19). Association for Computing Machinery, New York, NY, USA, 133–144. https://doi.org/10.1145/3293883.3295704