Award 2024
ACM/IEEE DAC'24 Outstanding TPC Members sponsored by ACM/IEEE Design Automation Conference (DAC), Rate: 6.7% (26/390)
Biobraphy
Chun-Feng Wu(吳俊峯) is an assistant professor at National Yang Ming Chiao Tung University. He was a postdoctoral scholar in Department of Computer Science, Harvard University from 2021 to 2022. During his postdoc, he worked with Meta and Samsung on the topics of deep recommendation systems and computation-in-memory, respectively. He received his M.S. and Ph.D. degree in Department of Computer Science from National Tsing Hua University, Hsinchu, Taiwan, in 2016 and in Department of Computer Science and Information Engineering from National Taiwan University, Taipei, Taiwan, in 2021 respectively. He served in R&D alternative service at Institute of Information Science, Academia Sinica, Taipei, Taiwan. His primary research interests include memory/storage systems, embedded systems, operating systems and the next-generation memory/storage architecture.
Hi, I joined the Department of Computer Science at National Yang Ming Chiao Tung University as an assistant professor in August 2022. I am looking for motivated B.S., M.S. and Ph.D. students, also welcome PostDoc. Our research topic will focus on memory/storage co-design with a variety of popular applications (e.g., deep learning systems, recommendataion systems, graph processing systems, key-value databases, and various machine learning systems). Our lab will work closely with Harvard University, Academia Sinica, The Chinese University of Hong Kong, National Taiwan University, National Cheng Kung University and National Tsing Hua University. If you are interested in my research or plan to study abroad, please do not hesitate to email (cfwu417@cs.nycu.edu.tw) me with a copy of your CV to start a conversation. (Welcome guys interested in working with Harvard University.)
嗨，我於2022年八月加入陽明交大資工系。我們實驗室致力於整合應用程式與記憶體/儲存裝置以打造次世代運算系統，歡迎喜愛挑戰、樂於貢獻開源社群的同學加入，無論是碩士、專題、博士生、博士後都非常歡迎來聊聊。 底下三個是我比較熟悉的研究方向，也很歡迎其他不同的想法一起來Brainstorm新的方向。
- 應用程式與記憶體/儲存裝置整合設計：探索不同應用程式設計(e.g., 神經網路、深度推薦系統、圖形處理系統、Key-Value資料庫、機器學習系統及Tiny ML系統設計)，如何有效操作記憶體及儲存裝置。
- 次世代計算機架構：許多新的記憶體與儲存裝置開始支援在裝置內部做運算。探索有哪些運算又或者應用適合在裝置裡面做運算，該如何利用這樣新型的裝置加速應用程式。(除了模擬平台外，這個主題也可以跑在真實系統上。如果想玩玩看這種新的裝置，歡迎一起來研究)(此研究方向將與哈佛大學Harvard Architecture, Circuits, and Compilers團隊共同研究從應用、系統至晶片之垂直整合)
- 作業系統的挑戰：隨著儲存裝置效能不斷提升，記憶體與儲存裝置的速度差異逐漸拉近。在這樣的趨勢下，檔案系統與記憶體管理也漸漸面臨改變的需要。我們將一起探討現在的作業系統有哪些不合時宜的地方，以及可以如何優化現今作業系統以符合未來硬體與應用程式的發展趨勢。(此研究可以提升對於作業系統的理解，很適合未來想去發哥、螃蟹發展的同學)
Operating System & Applications
Memory System
1. ReRAM2. SCM3. Optane DIMM
Storage System
1. Flash SSDs2. SMR Drives3. ULL devices
NextGen System
1. Near Data Computing2. Unified Mem
Publications
Journal Papers
- Wen-Yi Wang, Chun-Feng Wu, Yun-Chih Chen, Tei-Wei Kuo and Yuan-Hao Chang, "GEAR: Graph-Evolving Aware Data ArrangeR to Enhance the Performance of Traversing Evolving Graphs on SCM," accepted and to appear in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD). (Integrated with ACM/IEEE CODES+ISSS'24)
- Yu-Pang Wang, Wei-Chen Wang, Yuan-Hao Chang, Chieh-Lin Tsai, Tei-Wei Kuo, Chun-Feng Wu, Chien-Chung Ho, and Han-Wen Hu, "TCAM-GNN: A TCAM-based Data Processing Strategy for GNN over Sparse Graphs," accepted and to appear in IEEE Transactions on Emerging Topics in Computing (TETC).
- Yun-Chih Chen, Chun-Feng Wu, Yuan-Hao Chang, and Tei-Wei Kuo, "ZoneLife: How to Utilize Data Lifetime Semantics to Make SSDs Smarter," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 42, no. 8, pp. 2488-2499, Aug. 2023.
- Camelia Slimani, Chun-Feng Wu, Stephane Rubini, Yuan-Hao Chang, and Jalil Boukhobza, "Accelerating Random Forest on Memory-Constrained Devices through Data Storage Optimization," IEEE Transactions on Computers (TC), vol. 72, no. 6, pp. 1595-1609, Jun. 2023.
- Yi-Shen Chen, Chun-Feng Wu, Yuan-Hao Chang, and Tei-Wei Kuo, "Energy Efficiency Enhancement of SCM-based Systems: A Write-friendly Coding," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 42, no. 5, pp. 1425-1437, May 2023.
- Gaddisa Olani Ganfure, Chun-Feng Wu, Yuan-Hao Chang, and Wei-Kuan Shih, "DeepWare: Imaging Performance Counters with Deep Learning to Detect Ransomware," IEEE Transactions on Computers (TC), vol. 72, no. 3, pp. 600-613, Mar. 2023.
- Gaddisa Olani Ganfure, Chun-Feng Wu, Yuan-Hao Chang, and Wei-Kuan Shih, "RTrap: Trapping and Containing Ransomware with Machine Learning," IEEE Transactions on Information Forensics and Security (TIFS), vol. 18, pp. 1433-1448, Jan. 2023.
- Yin-Chiuan Chen, Chun-Feng Wu, Yuan-Hao Chang, and Tei-Wei Kuo, "Exploring Synchronous Page Fault Handling," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 41, no. 11, pp. 3791-3802, Nov. 2022. (Integrated with ACM/IEEE CODES+ISSS'22)
- Chun-Feng Wu, Martin Kuo, Ming-Chang Yang, and Yuan-Hao Chang, "Performance Enhancement of SMR-based Deduplication Systems," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 41, no. 9, pp. 1835-2848, Sep. 2022.
- Shuo-Han Chen, Chun-Feng Wu, Ming-Chang Yang, and Yuan-Hao Chang, "A File-Oriented Fast Secure Deletion Strategy for Shingled Magnetic Recording Drives," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 41, no. 8, pp. 2463-2476, Aug. 2022.
- Tse-Yuan Wang, Chun-Feng Wu, Che-Wei Tsao, Yuan-Hao Chang, Tei-Wei Kuo, and Xue Liu, "Rethinking the Interactivity of OS and Device Layers in Memory Management," ACM Transactions on Embedded Computing Systems (TECS), vol. 21, no. 4, pp. 42:1-42:21, Jul. 2022.
- Che-Wei Chang, Chun-Feng Wu, Yuan-Hao Chang, Ming-Chang Yang, and Chieh-Fu Chang, "Leveraging Write Heterogeneity of Phase Change Memory on Supporting Self-balancing Binary Tree," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 41, no. 6, pp. 1757-1770, Jun. 2022.
- Dharamjeet, Tseng-Yi Chen, Yuan-Hao Chang, Chun-Feng Wu, Chi-Heng Lee, Wei-Kuan Shih, "Beyond Write-reduction Consideration: A Wear-leveling-enabled B+-tree Indexing Scheme over an NVRAM-based Architecture," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 40, no. 12, pp. 2455-2466, Dec. 2021.
- Wen Sheng Lim, Chia-Heng Tu, Chun-Feng Wu, and Yuan-Hao Chang, "iCheck: Progressive Checkpointing for Intermittent Systems," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 40, no. 11, pp. 2224-2236, Nov. 2021.
- Ming-Chang Yang, Chun-Feng Wu, Shuo-Han Chen, Yi-Ling Lin, Che-Wei Chang, and Yuan-Hao Chang, "On Minimizing Internal Data Migrations of Flash Devices via Lifetime-Retention Harmonization," IEEE Transactions on Computers (TC), vol. 70, no. 3, pp. 428-439, Mar. 2021.
- Chun-Feng Wu, Yuan-Hao Chang, Ming-Chang Yang, and Tei-Wei Kuo, "When Storage Response Time Catches Up with Overall Context Switch Overhead, What is Next?," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 39, no. 11, pp. 4266-4277, Nov. 2020. (Integrated with ACM/IEEE CODES+ISSS'20).
- Yao-Wen Kang, Chun-Feng Wu, Yuan-Hao Chang, Tei-Wei Kuo and Shu-Yin Ho, "On Minimizing Analog Variation Errors to Resolve the Scalability Issue of ReRAM-based Crossbar Accelerator," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 39, no. 11, pp. 3856-3867, Nov. 2020. (Integrated with ACM/IEEE EMSOFT'20).
- Gaddisa Olani Ganfure, Chun-Feng Wu, Yuan-Hao Chang, and Wei-Kuan Shih, "DeepPrefetcher: A Deep Learning Framework for Data Prefetching in Flash Storage Devices," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 39, no. 11, pp. 3311-3322, Nov. 2020. (Integrated with ACM/IEEE CASES'20).
- Ming-Chang Yang, Yuan-Hao Chang, Tei-Wei Kuo, and Chun-Feng Wu, "Request Flow Coordination for Growing-Scale Solid-State Drives," IEEE Transactions on Computers (TC), vol. 69, no. 6, pp. 832-843, Jun. 2020.
- Chun-Feng Wu, Yuan-Hao Chang, Ming-Chang Yang, and Tei-Wei Kuo, "Joint Management of CPU and NVDIMM for Breaking Down the Great Memory Wall," IEEE Transactions on Computers (TC), vol. 69, no. 5, pp. 722-733, May. 2020.
- Chun-Feng Wu, Ming-Chang Yang, Yuan-Hao Chang, and Tei-Wei Kuo, "Hot-Spot Suppression for Resource-Constrained Image Recognition Devices with Non-Volatile Memory," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 37, no. 11, pp. 2567-2577, Nov. 2018. (Integrated with ACM/IEEE EMSOFT 2018)
Conference Papers
- Che-Wei Lin, and Chun-Feng Wu, "ALISA: An Adaptive Learned Index Structure for Spatial Data on Solid-State Drives," ACM/IEEE International Conference on Computer-Aided Design (ICCAD), New Jersey, NJ, USA, Oct. 27-31, 2024.
Top-ConferenceAcceptance rate: 24% - Wen-Yi Wang, Chun-Feng Wu, Yun-Chih Chen, Tei-Wei Kuo, and Yuan-Hao Chang, "GEAR: Graph-Evolving Aware Data ArrangeR to Enhance the Performance of Traversing Evolving Graphs on SCM," ACM/IEEE International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS), Raleigh, NC, USA, Sep. 29 - Oct. 4, 2024. (Journal Track, Integrated with IEEE TCAD)
Top-Conference - Chun-Feng Wu, Yuan-Hao Chang, Ming-Chang Yang, and Tei-Wei Kuo, "How to Steal CPU Idle Time When Synchronous I/O Mode Becomes Promising," ACM/IEEE Design Automation Conference (DAC), San Francisco, CA, USA, Jun. 23-27, 2024.
Top-ConferenceAcceptance rate: 23% - Yunho Jin, Chun-Feng Wu, David Brooks, and Gu-Yeon Wei, "S3: Increasing GPU Utilization during Generative Inference for Higher Throughput," Conference on Neural Information Processing Systems (NeurIPS), New Orleans, LA, USA, Dec. 10-16, 2023.
Top-ConferenceAcceptance rate: 26.1% (3222/12343) - Chieh-Lin Tsai, Chun-Feng Wu, Yuan-Hao Chang, Han-Wen Hu, Yung-Chun Lee, Hsiang-Pang Li, and Tei-Wei Kuo, "A Digital 3D TCAM Accelerator for the Inference Phase of Random Forest," ACM/IEEE Design Automation Conference (DAC), San Francisco, CA, USA, Jul. 9-13, 2023.
Top-ConferenceAcceptance rate: 23% - Hao-Jan Huang, Wen Sheng Lim, Chia-Heng Tu, Chun-Feng Wu, and Yuan-Hao Chang, "Data Freshness Optimization on Networked Intermittent Systems," ACM/IEEE Design, Automation and Test in Europe (DATE), Antwerp, Belgium, Apr. 17-19, 2023.
- Wei Cheng, Chun-Feng Wu, Yuan-Hao Chang, and Ing-Chao Lin, "GraphRC: Accelerating Graph Processing on Dual-addressing Memory with Vertex Merging," ACM/IEEE International Conference on Computer-Aided Design (ICCAD), San Diego, California, USA, Oct. 30 - Nov. 3, 2022.
Top-ConferenceAcceptance rate: 22.5% (132/586) - Yin-Chiuan Chen, Chun-Feng Wu, Yuan-Hao Chang, and Tei-Wei Kuo, "Exploring Synchronous Page Fault Handling," ACM/IEEE International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS), Hybrid-Shanghai, Oct. 7-14, 2022. (Jounral Track, Integrated with IEEE TCAD)
Top-ConferenceAcceptance rate: 17.4% (31/178)Best Paper Award (1/178) - Chun-Feng Wu, Carole-Jean Wu, Gu-Yeon Wei, and David Brooks, "A Joint Management Middleware to Improve Training Performance of Deep Recommendation Systems with SSDs," ACM/IEEE Design Automation Conference (DAC), San Francisco, CA, USA, Jul. 10-14, 2022.
Top-ConferenceAcceptance rate: 23% - Tse-Yuan Wang, Chun-Feng Wu, Che-Wei Tsao, Yuan-Hao Chang, and Tei-Wei Kuo, "Scheduling-Aware Prefetching: Enabling the PCIe SSD to Extend the Global Memory of GPU Device," IEEE Nonvolatile Memory Systems and Applications Symposium (NVMSA), Virtual Conference, August 18-20, 2021.
- Ting-Hsuan Lo, Chun-Feng Wu, Yuan-Hao Chang, Tei-Wei Kuo and Wei-Chen Wang, "Space-efficient Graph Data Placement to Save Energy of ReRAM Crossbar," ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED), Virtual, Jul. 26-28, 2021.
Top-ConferenceAcceptance rate: ~24% - Yun-Chih Chen, Chun-Feng Wu, Yuan-Hao Chang, and Tei-Wei Kuo, "Reptail: Cutting Storage Tail Latency with Inherent Redundancy," ACM/IEEE Design Automation Conference (DAC), San Francisco, CA, USA, Dec. 5-9, 2021.
Top-ConferenceAcceptance rate: 23% - Camelia Slimani, Chun-Feng Wu, Yuan-Hao Chang, Stephane Rubini, and Jalil Boukhobza, "RaFIO: A Random Forest I/O-Aware Algorithm," ACM Symposium on Applied Computing (SAC), Gwangju, South Korea, Mar. 22-26, 2021.
- Hsiang-Yun Cheng, Chun-Feng Wu, Christian Hakert, Kuan-Hsun Chen, Yuan-Hao Chang, Jian-Jia Chen, Chia-Lin Yang and Tei-Wei Kuo, "Future Computing Platform Design: A Cross-Layer Design Approach," ACM/IEEE Design Automation and Test in Europe (DATE), Virtual Conference, Feb. 1-5, 2021.
- Yi-Shen Chen, Chun-Feng Wu, Yuan-Hao Chang, and Tei-Wei Kuo, "A Write-friendly Arithmetic Coding Scheme for Achieving Energy-Efficient Non-Volatile Memory Systems," ACM/IEEE Asia and South Pacific Design Automation Conference (ASP-DAC), Tokyo, Japan, Jan. 18-21, 2021.
- Gaddisa Olani Ganfure, Chun-Feng Wu, Yuan-Hao Chang, and Wei-Kuan Shih, "DeepGuard: Deep Generative User-behavior Analytics for Ransomware Detection,"IEEE International Conference on Intelligence and Security Informatics (ISI), Nov. 9-10, 2020.
- Yun-Sheng Chang, Yao Hsiao, Tzu-Chi Lin, Che-Wei Tsao, Chun-Feng Wu, Yuan-Hao Chang, Hsiang-Shang Ko, and Yu-Fang Chen, "Determinizing Crash Behavior with a Verified Snapshot-Consistent Flash Translation Layer," USENIX Symposium on Operating Systems Design and Implementation (OSDI), Banff, Alberta, Canada, Nov. 4-6, 2020.
Top-ConferenceAcceptance rate: 17.6% (70/398) - Chun-Feng Wu, Yuan-Hao Chang, Ming-Chang Yang, and Tei-Wei Kuo, "When Storage Response Time Catches Up with Overall Context Switch Overhead, What is Next?," ACM/IEEE International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS), Germany, Sep. 20 - 25, 2020. (Journal Track, Integrated with IEEE TCAD)
Top-ConferenceAcceptance rate: 21.9%(28/128) - Yao-Wen Kang, Chun-Feng Wu, Yuan-Hao Chang, Tei-Wei Kuo and Shu-Yin Ho, "On Minimizing Analog Variation Errors to Resolve the Scalability Issue of ReRAM-based Crossbar Accelerator," ACM/IEEE International Conference on Embedded Software (EMSOFT), Germany, Sep. 20 - 25, 2020. (Journal Track, Integrated with IEEE TCAD)
Top-Conference - Gaddisa Olani Ganfure, Chun-Feng Wu, Yuan-Hao Chang, and Wei-Kuan Shih, "DeepPrefetcher: A Deep Learning Framework for Data Prefetching in Flash Storage Devices," ACM/IEEE International Conference on Compilers, Architecture, and Synthesis for Embedded Systems (CASES), Germany, Sep. 20 - 25, 2020. (Journal Track, Integrated with IEEE TCAD)
Top-Conference - Shuo-Han Chen, Yu-Pei Liang, Yuan-Hao Chang, Yun-Fei Liu, Chun-Feng Wu, Hsin-Wen Wei, and Wei-Kuan Shih, "Reinforcing the Energy Efficiency of Cyber-Physical Systems via Direct and Split Cache Consolidation on MLC STT-RAM," ACM Symposium on Applied Computing (SAC), Brno, Czech Republic, Mar. 30 - Apr. 3, 2020.
- Yu Ting Ho, Chun-Feng Wu, Ming-Chang Yang, and Yuan-Hao Chang, "Replanting Your Forest: NVM-friendly Bagging Strategy for Random Forest," IEEE Nonvolatile Memory Systems and Applications Symposium (NVMSA), Hangzhou, China, August 18-21, 2019.
Best Paper Award - Shuo-Han Chen, Ming-Chang Yang, Yuan-Hao Chang, and Chun-Feng Wu, "Enabling File-Oriented Fast Secure Deletion on Shingled Magnetic Recording Drives," ACM/IEEE Design Automation Conference (DAC), Las Vegas, Nevada, USA, Jun. 2-6, 2019.
Top-ConferenceAcceptance rate: 24.8%(202/815) - Chun-Feng Wu, Ming-Chang Yang, Yuan-Hao Chang, and Tei-Wei Kuo, "Hot-Spot Suppression for Resource-Constrained Image Recognition Devices with Non-Volatile Memory," ACM/IEEE International Conference on Embedded Software (EMSOFT), Torino, Italy, Sep. 30-Oct. 5, 2018. (Journal Track, Integrated with IEEE TCAD)
Top-Conference - Chun-Feng Wu, Ming-Chang Yang, and Yuan-Hao Chang, "Improving Runtime Performance of Deduplication System with Host-Managed SMR Storage Drives," ACM/IEEE Design Automation Conference (DAC), San Francisco, USA, Jun. 24-28, 2018.
Top-ConferenceAcceptance rate: 24.3%(168/691) - Chun-Feng Wu, Tse-Chuan Hsu, Hongji Yang, and Yeh-Ching Chung, "File Placement Mechanisms for Improving Write Throughputs of Cloud Storage Services Based on Ceph and HDFS," Proceedings of IEEE International Conference on Applied System Innovation (ICASI), Sapporo, Japan, May 2017.
The First Prize Paper Award - Su-Shien Ho, Chun-Feng Wu, Jiazheng Zhou, Wenguang Chen, Ching-Hsien Hsu, Hung-Chang Hsiao, and Yeh-Ching Chung. "Distributed Metaserver Mechanism and Recovery Mechanism Support in Quantcast File System," IEEE Computer Software and Applications Conference (COMPSAC), pages 758 - 763, Taichung, Taiwan, July. 2015.
US Patents
- Wei-Chen Wang, Ting-Hsuan Lo, Chun-Feng Wu, Yuan-Hao Chang, Tei-Wei Kuo, "Memory Device And Operation Method Thereof," Patent No.: US 11,640,255, Date of Patent: May 2, 2023.
- Shu-Yin Ho, Hsiang-Pang Li, Yao-Wen Kang, Chun-Feng Wu, Yuan-Hao Chang, Tei-Wei Kuo, "Neural Network Computation Method Using Adaptive Data Representation," Patent No.: US 11,594,277, Date of Patent: Feb. 28, 2023.
- Shu-Yin Ho, Hsiang-Pang Li, Yao-Wen Kang, Chun-Feng Wu, Yuan-Hao Chang, Tei-Wei Kuo, "Neural Network Computation Method And Apparatus Using Adaptive Data Representation," Patent No.: US 11,443,797, Date of Patent: Sep. 13, 2022.
Transactions
Top Conferences
Journals
Conferences
Awards
Award 2022
IEEE PhD Thesis Award sponsored by IEEE Taipei Section. (IEEE 2021 碩博士論文獎)
Award 2022
Excellence Award of PhD Thesis Award sponsored by Institute of Information & Computing Machinery (IICM). (中華民國資訊學會博士論文優等獎)
Award 2021
One of the Finalist of Open Innovation Contest for AXDIMM Technology hosted by Samsung.
Award 2021
The 1st Prize of PhD Thesis Award sponsored by Lam Research. (科林論文獎博士論文頭等獎)
Award 2021
PhD Thesis Award sponsored by Taiwan Information Storage Association (TISA). (台灣資訊儲存學生論文獎)
Scholarship 2021
CTCI Research Scholarship sponsored by China Technical Consultants Inc (CTCI) Foundation. (中技社研究獎學金)
Award 2021
TSIA Semiconductor Award sponsored by Taiwan Semiconductor Industry Association (TSIA). (台灣半導體產業協會半導體獎)
Scholarship 2020
Pan Wen Yuan Scholarship sponsored by Pan Wen Yuan Foundation. (財團法人潘文淵文教基金會)
Scholarship 2020
Elite Scholarship sponsored by Elite-Well Education Foundation. (財團法人平安菁教育英基金會)
Scholarship 2018
Student Travel Grants sponsored by Embedded Systems Week (ESWEEK).
Scholarship 2018
Outstanding Students Conference Travel Grants sponsored by Foundation for the Advancement of Outstanding Scholarship (FAOS). (傑出人才發展基金會)
Scholarship 2018
The International Conference Scholarship For Young Researchers sponsored by Academia Sinica. (中央研究院年輕學者出國報告)
Projects
Government Project 2024
2030 Cross-Generation Young Scholars Program: Emerging Young Scholars sponsored by National Science and Technology Council (NSTC). (國科會跨世代年輕學者方案:新秀學者)
Government Project 2022
Yushan Young Fellow Program sponsored by Ministry of Education (MOE). (教育部玉山青年計畫)
Government Project 2020
Postdoctoral Research Study Abroad Program sponsored by Ministry of Science and Technology (MOST). (科技部博士後研究千里馬計畫)
Talks
Seminar Talk Speaker 2022
Seminar Talk Speaker of NTU DS, Taipei, 2023.
Seminar Talk Speaker 2022
Seminar Talk Speaker of NCKU CSIE, Tainan, 2023.
Seminar Talk Speaker 2022
Seminar Talk Speaker of NTHU ISA, Hsinchu, 2022.
Invited Talk Speaker 2022
Invited Talk Speaker of Meta, Boston, 2022.
Tutorial Speaker 2021
Tutorial Speaker of The 24th Design, Automation and Test in Europe Conference (DATE), 2021.
Student Research Forum Speaker 2021
Student Research Forum Speaker of The 26th Asia and South Pacific Design Automation Conference(ASP-DAC), 2021.
Invited Talk Speaker 2020
Forum Speaker of The CCF China Test Conference (CTC), 2020.
Forum Speaker 2019
PhD Forum Speaker of The 30th VLSI Design/CAD Symposium, 2019.
Invited Talk Speaker 2019
Invited Talk Speaker of The 8th IEEE Non-Volatile Memory Systems and Applications Symposium (NVMSA), 2019.
Experiences
Researchers from Meta (or Facebook previously) point out that data preprocessing is becoming a critical performance bottleneck for training their recommendation systems. We observed that, one of the reasons of the bottleneck is that unused training data may still be read and filtered out during data preprocessing. Besides, these unused data movements is because of the access behavior gap between recommendation systems and SSDs. To avoid these unused data movements, We proposed a joint management middleware to bridge the access behavior gap and periodically re-organize the training data inside SSDs. With using our middleware, systems can save 24%-47% of the overall read time compared with the LSM-based strategy, which is now currently applied by Meta and Baidu.
We come up with a proposal targeting on integrating the GNN-based recommendation system with AxDIMM. We are now working on the architecture analysis of AxDIMM and the behavior analysis of GNN-based recommendation system.
Conduct researches, experiments, or implementations related to computer systems such as storage systems, memory systems, embedded systems, computer architecture, energy-efficient designs, multi-core/many-core systems, and neuromorphic computing.
This project aims to provide a private cloud storage for users. Our team designs a distributed storage system, SSBox, with high accessibility and reliability. We provide PaaS layer services for programmers to access our SSBox by RESTful API. In addition, SSBox could endure hundred of thousand of users to access simultaneously.
This project aims to provide Virtual Desktops to cost down the hardware price for schools. We apply a real-time virtual desktop based on OpenStack and Docker. Users just need a browser and stable Internet so that users can access different Operating System. We also design a client side by OpenStack APIs and the design makes users to create virtual desktops eaiser.
English TOEFL (95)
Programming (Python, C++)
Frameworks (OpenStack, Ceph)
Analysis Tools(Intel Pin, Valgrind)
Contact
cfwu@seas.harvard.edu
cfwu417@cs.nycu.edu.tw
Office: Room 416, Engineering Building 3, No. 1001, Daxue Rd. East Dist., Hsinchu City 300, Taiwan
Lab: Room 119, Engineering Building 3, No. 1001, Daxue Rd. East Dist., Hsinchu City 300, Taiwan