QCCC-24: The Third International Workshop on Quantum Classical Cooperative Computing

       

Held in conjunction with the The 38th ACM International Conference on Supercomputing (ICS24’)

Kyoto, Japan, June 4, 2024.

Overview

The past few years have seen tremendous development in quantum computing technology, remarked by the demonstra- tion of quantum supremacy. Although many quantum algo- rithms declare exponential speedups over their classical coun- terparts, today’s quantum devices in the noisy-intermediate scale quantum (NISQ) era are very susceptible to environmen- tal noise, internal interference, manufacturing imperfection, and technology limitations. Consequently, quantum algorithms that are more robust to noise, or can be effectively decomposed into small pieces for incremental or parallel execution on NISQ devices become promising.

The purpose of this workshop is to explore innovative ways of quantum-classical cooperative computing (QCCC) to make quantum computing more effective and scalable in NISQ platforms. The workshop will focus heavily on how classical computing can improve NISQ device execution efficiency, scalability, or compensate for noise impact or technology defi- ciency, with particular emphasis on demonstrable approaches on existing NISQ platforms, such as IBM-Q, IonQ and Rigetti.

Workshop Program

13:00

Workshop Openning

Prof. Dingwen Tao

13:05

Keynote

Dr. Vincent R Pascuzzi, IBM Research

13:50- 14:10

Hybrid Quantum Solvers in Production: how to succeed in the NISQ era?

Eneko Osaba, Esther Villar-Rodriguez, Aitor Gomez-Tejedor and Izaskun Oregi

14:10-14:20

Analysis of Reconfigurable Networked Microgrids QAOA under Realistic Noise

Betis Baheri, Bo Fang, Ang Li, Yan Li and Qiang Guan

14:20-14:30

Noise-Aware Distributed Quantum Approximate Optimization Algorithm on Near-term Quantum Hardware

Kuan-Cheng Chen, Chen-Yu Liu and Xiaotian Xu

14:30-14:45

Break

14:45

Invited Talk

Prof. Shigeru Yamashita, Ritsumeikan University

15:30- 15:50

Parallel Quantum Local Search via Evolutionary Mechanism

Chen-Yu Liu and Kuan-Cheng Chen

15:50-16:10

Random Qubit Measurement to Optimize Variational Quantum Circuit Compilation Technique

Priyabrata Senapati, Vinooth Rao Kulkarni, Cheng Chang Lu, Shuai Xu, Qiang Guan and Vipin Chaudhary

16:10-16:30

ZOE: Memory Efficient High-performance Quantum Phase Estimation on GPUs

Boyuan Zhang, Fanjiang Ye, Bo Fang, Christopher Kang, Ang Li and Dingwen Tao

16:30- 16:50

Approaches to Simultaneously Solving Variational Quantum Eigensolver Problems

Adam Hutchings, Eric Yarnot, Xinpeng Li, Qiang Guan, Ning Xie, Shuai Xu and Vipin Chaudhary

16:30- 16:50Workshop Closing Comments

Keynote

Title

 Quantum-centric Supercomputing

Speaker

Dr. Vincent R Pascuzzi, IBM Research

Abstract

The rise of hardware accelerators and machine learning has led to unprecedented computational prowess. These technologies have been drivers of scientific research and discovery where the embarrassingly parallel nature of certain workloads are exploited to attain substantial improvements in time-to-solution and output quality across many fields of science. Despite the successes, there still exist an array of problems that appear to be manifestly intractable with classical computation alone; for which classical computation provides only approximate solutions or are otherwise computationally inefficient with respect to scalability.

An emerging technology that shows promise to address such problems is quantum computing, wherein algorithms exploiting quantum mechanical phenomena can achieve exponential gains in time and space for certain classes of problems. However, quantum workloads require significant classical computing support for preprocessing, including optimization and compilation, and postprocessing. This naturally leads to the concept of Quantum-centric Supercomputing (QCSC): the integration of quantum computational devices and high performance computing (HPC) resources. QCSC will leverage quantum and classical computing devices to enable execution of parallel and asynchronous workloads, unlocking capabilities for computations beyond what is currently possible.

In this talk, we will give an overview of our development roadmap and show how QCSC naturally fits this vision. We will explore ways in which the community can benefit from QCSC systems through detailed use cases suitable for such platforms that will play a central role in novel supercomputing systems of the future.

Speaker Bio

Dr. Pascuzzi received his PhD in Physics from the University of Toronto, Canada in 2019. Following graduation, he joined the Lawrence Berkeley National Laboratory’s Physics Division as a postdoctoral research fellow, working on performance portability for high energy physics applications and quantum error mitigation. In 2021, Dr. Pascuzzi moved to Brookhaven National Laboratory as Assistant Computational Scientist, where he focused on workflow systems and performance portability for high performance computing. He was a co- recipient of a Department of Energy Office of Science Advanced Scientific Computing Research Exploratory Research for Extreme-Scale Science award for “Novel Quantum Algorithms from Fast Classical Transforms.” Dr. Pascuzzi joined IBM Research as a Quantum Compilation Engineer in 2022. In addition to compiler development, his research includes quantum simulations for high energy physics and programming models targeting Quantum-centric Supercomputing systems.

Invited Talk

Title

Design Methods for Quantum Boolean Circuits

Abstract

Even for quantum computation, it is very important to design quantum circuits which calculate classical Boolean functions; we call such quantum circuits quantum Boolean circuits. First, we will explain a naive method to design quantum Boolean circuits by using Mixed Polarity Multiple-Control Toffoli（MPMCT）gates. This method may not be able to treat large circuits, and thus there proposed a scalable design method based on LUT network synthesis. We review this method, and then introduce some resent extension of the method by using “relative phase gates.”

Speaker

       

Prof. Shigeru Yamashita, Ritsumeikan University

Speaker Bio

Shigeru Yamashita is a professor of College of Information Science and Engineering, Ritsumeikan University. He received his B. E., M. E. and Ph.D. degrees in information science from Kyoto University, Kyoto, Japan, in 1993, 1995 and 2001, respectively. In 1995, he joined NTT Communication Science Laboratories, where he engaged in research of computer aided design of digital systems and new type of computer architectures. During 2000 to 2003, he was also a researcher at Quantum Computation and Information, ERATO, Japan Science and Technology Corporation. During 2003 to 2009, he was an associate professor of Graduate School of Information Science, Nara Institute of Science and Technology. He also served a Visiting Professor at National Institute of Informatics from 2012 to 2017. He received the 2000 IEEE Circuits and Systems Society Transactions on Computer-Aided Design of Integrated Circuits and Systems Best Paper Award, SASIMI 2010 Best Paper Award, 2010 IPSJ Yamashita SIG Research Award, SASIMI 2018 Outstanding Paper Award, SASIMI 2022 Outstanding Paper Award, Marubun Academic Achievement Award of the Marubun Research Promotion Foundation. He is a senior member of IEEE and IEICE, and a member of ACM and IPSJ.

Topics

Topics of interest for this workshop include, but not limited to:

Topics that are not relevant include pure quantum or pure classical algorithm/hardware design, benchmarking of quantum algorithm/devices.

Venue

This workshop is part of ACM ICS 2024: the 38th ACM International Conference on Supercomputing (ICS) Kyoto, Japan on June 4-7, 2024.

Important Dates

Submissions

Authors are invited to submit original 2-page (double-column, up to 4 pages) extended abstracts. The deadline is Friday, March 22, 2024.

Accepted papers will be given 15 mins to present in the workshop.

Papers are to be submitted electronically through Easychair at Here.

PC Members

Workshop Co-Chairs

Program Co-Chairs

Steering Committee

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