Xin-Chuan (Ryan) Wu
I am a research scientist in quantum computer architecture at Intel Labs. My research interest is in the field of quantum computing, supercomputing systems, quantum compiler, and computer architecture. I received my PhD from the University of Chicago, advised by Prof. Fred Chong. Before my PhD, I had 7 years of experience in Linux kernel driver development for mobile devices as a senior software engineer at ASUS Computer. Prior to that, I received my M.S. degree from National Taiwan University and B.S. degree from National Chiao Tung University.
E-mail: xin-chuan.wu@intel.com
Research Interests:
Quantum Computing, Supercomputing, Compiler, Computer Architecture, HW/SW Co-Design
Recent Talks:
Advances in Quantum Computing and Intro to the Intel® Quantum SDK, Session talk at Intel Innovation Taipei, Taipei, Taiwan, Nov. 2023.
Introduction to Hybrid Quantum-Classical Programming Using C++ Quantum Extension, Tutorial Talk at International Conference on Computer-Aided Design (ICCAD), San Francisco, CA, Oct. 2023.
Intel Quantum SDK: An Open-Source Quantum Compiler Using the LLVM Framework, Lightning Talk at LLVM Developers' Meeting, Santa Clara, CA, Oct. 2023.
Introduction to Intel Quantum SDK Version 1.0, Tutorial Talk at IEEE International Conference on Quantum Computing and Engineering (QCE), Seattle, WA, Sep. 2023.
Introduction to Hybrid Quantum-Classical Programming Using C++ Quantum Extension, Tutorial Talk at HPDC, Orlando, FL, June, 2023.
Intel Quantum SDK Version 1.0: Extended C++ Compiler, Runtime and Quantum Hardware Simulators for Hybrid Quantum-Classical Applications, APS March Meeting, March 2023.
Introduction to Intel Quantum SDK, Invited Talk at UPenn CIS7000 Topics on Quantum Computing System, Virtual, February, 2023.
Intel Quantum SDK: A Platform for Efficient Execution of Variational Algorithms, Intel Labs Talks, Virtual, December 2022.
Introduction to Quantum Computing and System Stack, SC22 Tutorial, Dallas, Texas, November 2022.
Main Components of the Intel Quantum SDK and What You Need before You Start Programming, Intel Innovation, San Jose, September, 2022.
Intel Quantum SDK: A Platform for Efficient Execution of Variational Algorithms, IEEE International Conference on Quantum Computing and Engineering (QCE), Broomfield, Colorado, September, 2022.
Intel Quantum Computing Architecture and Software Stack, Workshop on Software Stack Design for Quantum Computing at DAC, San Francisco, Jul 2022.
LLVM-based C++ Compiler Toolchain for Quantum Computing, Intel IDP Tech Forum, Virtual, July 2022.
Panel: Quantum Software Toolchain, Panel discussion at Design, Automation and Test in Europe (DATE) Conference, Virtual conference, Mar 2022.
An Intel Quantum Software Development Kit for Efficient Execution of Variational Algorithms, Conference talk at APS March Meeting, Chicago, IL, Mar 2022.
Reoptimization of Quantum Circuits via Hierarchical Synthesis, Conference talk at IEEE International Conference on Rebooting Computing (ICRC), Nov 2021
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
- Conducted extensive research and development in quantum architecture, advancing Intel's capabilities in the field of quantum computing.
- Lead an LLVM-based quantum compiler open-source project.
- Developed a C++ full-stack system for quantum programming.
- Bridged the software system to the hardware controller.
- Contributed to the development of the Intel Quantum SDK, enhancing functionality, reliability, and user experience.
- Implemented runtime calibration library for qubit chips.
- Managed and maintained comprehensive documentation for developers and users of the Intel Quantum SDK
- Present the SDK and organize multiple tutorials at conferences.
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.
- Software lead for Linux kernel driver development and system integration for Android systems.
- Managed international specialized team working on system stability issues in North America, analyzed technical reports for system adoption, and reported findings to clients.
- Managed projects in North America and collaborated with Google, Verizon, T-Mobile, and AT&T.
- Scouted for innovative ideas to further develop ASUS's mobile devices and evaluate adoption of new products to expand company's project profiles internationally.
- 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
- Integrated Android system, Linux kernel low-level debugging, and embedded system software development.
- Implemented Linux kernel i2c driver for touch screen, touch pad, and keyboard.
- Designed embedded system software, focusing on bootloader GPIOs configuration and Linux 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
- Analyzed system stability and performance.
- Lead engineer for developing embedded system battery driver.
- Products: Garmin-ASUS Smart Phone (A50/A10) Series
Publications:
Xin-Chuan Wu, Shavindra P. Premaratne, Kevin Rasch, "Invited Paper: Introduction to Hybrid Quantum-Classical Programming Using C++ Quantum Extension", in Proceedings of the 42st IEEE/ACM International Conference on Computer-Aided Design (ICCAD), Oct 2023.
Albert T. Schmitz, Mohannad Ibrahim, Nicolas P. D. Sawaya, Gian Giacomo Guerreschi, Jennifer Paykin, Xin-Chuan Wu, A. Y. Matsuura, "Optimization at the Interface of Unitary and Non-unitary Quantum Operations in PCOAST", IEEE International Conference on Quantum Computing and Engineering (QCE), Sep 2023.
Jennifer Paykin, Albert T. Schmitz, Mohannad Ibrahim, Xin-Chuan Wu, A. Y. Matsuura, "PCOAST: A Pauli-based Quantum Circuit Optimization Framework", IEEE International Conference on Quantum Computing and Engineering (QCE), Sep 2023.
Xin-Chuan Wu, Shavindra P. Premaratne, Kevin Rasch, "A Comprehensive Introduction to the Intel Quantum SDK", Proceedings of the 2023 Introduction on Hybrid Quantum-Classical Programming Using C++ Quantum Extension in conjunction with HPDC, June 2023.
Xin-Chuan Wu, Albert Schmitz, Pradnya Khalate, Anne Y. Matsuura, "An LLVM-Based Compiler for Quantum-Classical Applications.", LLVM Developers' Meeting, Nov 2022. [poster]
Pradnya Khalate, Xin-Chuan Wu, Shavindra Premaratne, Justin Hogaboam, Adam Holmes, Albert Schmitz, Gian Giacomo Guerreschi, Xiang Zou, AY Matsuura, "An LLVM-Based C++ Compiler Toolchain for Variational Hybrid Quantum-Classical Algorithms and Quantum Accelerators", arXiv preprint arXiv:2202.11142, March 2022.
Teague Tomesh, Pranav Gokhale, Victory Omole, Gokul Ravi, Kaitlin Smith, Joshua Viszlai, Xin-Chuan Wu, Nikos Hardavellas, Margaret R. Martonosi, Frederic T. Chong, "SupermarQ: A Scalable Quantum Benchmark Suite", in the Proceedings of 28th IEEE Symposium on High Performance Computer Architecture (HPCA). April, 2022. Best Paper Award
Xin-Chuan Wu, Marc Grau Davis, Frederic T. Chong, Costin Iancu, "Reoptimization of Quantum Circuits via Hierarchical Synthesis", in the Proceedings of IEEE International Conference on Rebooting Computing (ICRC). Nov, 2021.
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", 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
Program Committees/Reviewers:
IEEE International Conference on Quantum Computing and Engineering (QCE) 2023
ACM Transactions on Quantum Computing 2023
Quantum Journal 2023
Design Automation Conference (DAC) 2023
IEEE Transactions on Quantum Engineering 2023
Quantum Journal 2022
IEEE Transactions on Quantum Engineering 2022
IEEE Micro 2022
IEEE Transactions on Computers 2022
IEEE International Conference on Quantum Computing and Engineering (QCE) 2022
IEEE Computer Architecture Letters 2022
ACM Transactions on Quantum Computing 2022
IEEE Transactions on Emerging Topics in Computing 2022
IEEE International Conference on Quantum Computing and Engineering (QCE) 2021
ACM Transactions on Quantum Computing 2021
IEEE Transactions on Quantum Engineering 2021