Xin-Chuan (Ryan) Wu

I am a research scientist at Intel Labs. As a scientist with over 15 years of experience in the fields of software development and hardware/software co-design, I have a wide range of research interests, including quantum computing, quantum compiler, high-performance computing, computer architecture, embedded systems, and security. I received my PhD from University of Chicago, advised by Prof. Fred Chong. Prior to joining University of Chicago, I worked on multiple mobile device and IoT projects in Linux kernel driver development as a senior software engineer at ASUS Computer. I received my M.S. in Computer Science from National Taiwan University and B.S. in Computer Science from National Chiao Tung University.

E-mail: xin-chuan.wu@intel.com

Curriculum Vitae

Research Interests:

Quantum Computing, Supercomputing, Compiler, Computer Architecture


Recent Talks:

  • Scalable Quantum Circuit Optimization Using Automated Synthesis, Conference talk at APS March Meeting, Mar 2021

  • TILT:Achieving Higher Fidelity on a Trapped-Ion Linear-Tape Quantum Computing Architecture, Conference talk at HPCA, Feb 2021

  • Design, Optimization, and Simulation of Scalable Quantum Computing Systems, invited talk at IonQ, Jan 2021

  • Quantum Circuit Optimization by Using Scalable Quantum Synthesis, invited seminar talk at AQT, Lawrence Berkeley National Laboratory, CA, Oct 2020

  • Full-State Quantum Circuit Simulation by Using Data Compression, conference talk at SC19, Denver, CO, Nov 2019

  • ILP-Based Scheduling for Linear-Tape Model Trapped-Ion Quantum Computers, QIS student workshop, Argonne National Laboratory, IL, Aug 2019

  • Protecting Page Tables from RowHammer Attacks using Monotonic Pointers in DRAM True-Cells, conference talk at ASPLOS, Providence, RI, Apr 2019

  • Intermediate-Scale Full State Quantum Circuit Simulation by Using Lossy Data Compression, APS March Meeting, Boston, MA, Mar 2019

  • Memory-Efficient Quantum Circuit Simulation by Using Lossy Data Compression, PMES, Dallas, TX, Nov 2018

  • Amplitude-Aware Lossy Compression for Quantum Circuit Simulation, DRBSD-4, Dallas, TX, Nov 2018


Professional Experience:

  • Research Scientist, Intel Labs, Santa Clara, CA, May 2021 - Present

- Quantum Architecture Research and Development

- LLVM Development for Quantum Computing


  • Grad Student Summer Intern, Lawrence Berkeley National Laboratory, Berkeley, CA, June-Sep. 2020.

- Quantum Circuit Optimization by Using Synthesis


  • Research Aide, Argonne National Laboratory, Lemont, IL, July-September 2019.

- ILP-Based Scheduling for Linear-Tape Model Trapped-Ion Quantum Computers

- Achieving Higher Fidelity on a Trapped-Ion Linear-Tape Quantum Computing Architecture


  • Research Aide, Argonne National Laboratory, Lemont, IL, June-September 2018.

- Full State Quantum Circuit Simulation by Using Data Compression


  • R&D Specialist, ASUS Computer International, Fremont, CA, 2013-2016.

- Led a team to develop Linux kernel driver for Android systems such as IoT and mobile devices.

- Products: Google Nexus Player, Google Nexus 7 (2013), ASUS ZenFone Series


  • Senior Software Engineer, ASUS Computer Inc., Taipei, Taiwan, 2011-2013.

- Linux kernel driver development

- Products: Google Nexus Player (2012), ASUS Transformer Pad Series


  • Software Engineer, ASUS Computer Inc., Taipei, Taiwan, 2009-2011.

- Board support package (BSP) development and board bring-up

- Products: Garmin-ASUS Smart Phone (A50/A10) Series


Publications:

  • Xin-Chuan Wu, Dripto M. Debroy, Yongshan Ding, Jonathan M. Baker, Yuri Alexeev, Kenneth R. Brown, Frederic T. Chong, "TILT: Achieving Higher Fidelity on a Trapped-Ion Linear-Tape Quantum Computing Architecture", to appear in the Proceedings of 27th IEEE Symposium on High Performance Computer Architecture (HPCA). Feb 2021. [paper]

  • Yongshan Ding, Xin-Chuan Wu, Adam Holmes, Ash Wiseth, Diana Franklin, Margaret Martonosi, Frederic T. Chong, "SQUARE: Strategic Quantum Ancilla Reuse for Modular Quantum Programs via Cost-Effective Uncomputation", in proc. of 47th Intl. Symposium on Computer Architecture (ISCA). May 2020. Award: Honorable Mention for IEEE Micro Top Picks [paper]

  • Xin-Chuan Wu, Yongshan Ding, Yunong Shi, Yuri Alexeev, Hal Finkel, Kibaek Kim, Frederic T. Chong, "ILP-Based Scheduling for Linear-Tape Model Trapped-Ion Quantum Computers", in IEEE/ACM 30th The International Conference for High Performance Computing, Networking, Storage and Analysis (SC). November 2019. Denver, CO. [poster]

  • Franck Cappello, Sheng Di, Sihuan Li, Xin Liang, Ali M. Gok, Dingwen Tao, Chun Hong Yoon , Xin-Chuan Wu, Yuri Alexeev, Federic T. Chong, "Use cases of lossy compression for floating-point data in scientific datasets", in The International Journal of High Performance Computing Applications (IJHPCA), 2019. [paper]

  • Xin-Chuan Wu, Sheng Di, Emma Maitreyee Dasgupta, Franck Cappello, Yuri Alexeev, Hal Finkel, Frederic T. Chong, "Full State Quantum Circuit Simulation by Using Data Compression", in IEEE/ACM 30th The International Conference for High Performance Computing, Networking, Storage and Analysis (SC). November 2019. Denver, CO. [paper]

  • Xin-Chuan Wu, Timothy Sherwood, Frederic T. Chong and Yanjing Li, "Protecting Page Tables from RowHammer Attacks using Monotonic Pointers in DRAM True-Cells", International Symposium on Architectural Support for Programming Languages and Operating Systems (ASPLOS). April 2019. Providence, RI. [paper]

  • Xin-Chuan Wu, Sheng Di, Franck Cappello, Hal Finkel, Yuri Alexeev , Frederic T. Chong, "Memory-Efficient Quantum Circuit Simulation by Using Lossy Data Compression", The 3rd International Workshop on Post-Moore Era Supercomputing (PMES) in conjunction with IEEE/ACM 29th The International Conference for High Performance Computing, Networking, Storage and Analysis (SC). November 2018. Dallas, TX. [paper]

  • Xin-Chuan Wu, Sheng Di, Franck Cappello, Hal Finkel, Yuri Alexeev, Frederic T. Chong, "Amplitude-Aware Lossy Compression for Quantum Circuit Simulation", The 4th International Workshop on Data Reduction for Big Scientific Data (DRBSD-4) in conjunction with IEEE/ACM 29th The International Conference for High Performance Computing, Networking, Storage and Analysis (SC). November 2018. Dallas, TX. [paper]

  • Xin-Chuan Wu, Sheng Di, Franck Cappello, Hal Finkel, Yuri Alexeev, Frederic T. Chong, "Full State Quantum Circuit Simulation by Using Data Compression", in IEEE/ACM 29th The International Conference for High Performance Computing, Networking, Storage and Analysis (SC). November 2018. Dallas, TX. [poster]

  • Ali Javadi-Abhari, Adam Holmes, Shruti Patil, Jeff Heckey, Daniel Kudrow, Pranav Gokhale, David Noursi, Lee Ehudin, Yongshan Ding, Xin-Chuan Wu, Yunong Shi. ScaffCC: Scaffold Compiler Collection. Jun 2018.

  • Xin-Chuan Wu, Ye-Jyun Lin, Pao-Jui Huang, Tay-Jyi Lin, and Chia-Lin Yang, "Instruction-level power estimation for embedded VLIW digital signal processors," VLSI Design/CAD Symposium, Hualien, Aug. 2009

  • Xin-Chuan Wu, "System-level Power Estimation for Digital Signal Processor," National Taiwan University, Aug. 2009