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Quantum Register Machine: Efficient Implementation of Quantum Recursive Programs

proceedings of the ACM on Programming Languages 2025年第PLDI期9卷 822-847页

作者： Zhicheng Zhang Mingsheng Ying University of Technology Sydney Sydney Australia

Quantum recursive programming has been recently introduced for describing sophisticated and complicated quantum algorithms in a compact and elegant way. However, implementation of quantum recursion involves intricate interplay between quantum control flow and recursive procedure calls. In this paper, we aim at resolving this fundamental challenge and develop a series of techniques to efficiently implement quantum recursive programs. Our main contributions include:1. We propose a notion of quantum register machine, the first quantum architecture (including an instruction set) that provides instruction-level support for quantum control flow and recursive procedure calls at the same time.2. Based on quantum register machine, we describe the first comprehensive implementation process of quantum recursive programs, including the compilation, the partial evaluation of quantum control flow, and the execution on the quantum register machine.3. As a bonus, our efficient implementation of quantum recursive programs also offers automatic parallelisation of quantum algorithms. For implementing certain quantum algorithmic subroutine, like the widely used quantum multiplexor, we can even obtain exponential parallel speed-up (over the straightforward implementation) from this automatic parallelisation. This demonstrates that quantum recursive programming can be win-win for both modularity of programs and efficiency of their implementation.

关键词： automatic parallelisation compilation partial evaluation quantum architectures quantum programming languages recursive definition

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14th International conference on parallel Processing and Applied Mathematics, PPAM 2022

14th International Conference on Parallel Processing and App...

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14th International conference on parallel Processing and Applied Mathematics, PPAM 2022

ISBN: (纸本)9783031304446

The proceedings contain 77 papers. The special focus in this conference is on parallel Processing and Applied Mathematics. The topics include: Neural Nets with a Newton Conjugate Gradient Method on Multiple GPUs;Exploring techniques for the Analysis of Spontaneous Asynchronicity in MPI-parallel Applications;Cost and Performance Analysis of MPI-Based SaaS on the Private Cloud Infrastructure;building a Fine-Grained Analytical Performance Model for Complex Scientific Simulations;evaluation of Machine Learning techniques for Predicting Run Times of Scientific Workflow Jobs;Smart Clustering of HPC Applications Using Similar Job Detection Methods;distributed Work Stealing in a Task-Based Dataflow Runtime;task Scheduler for Heterogeneous Data Centres Based on Deep Reinforcement Learning;Shisha: Online Scheduling of CNN Pipelines on Heterogeneous architectures;General Framework for Deriving Reproducible Krylov Subspace Algorithms: BiCGStab Case;proactive Task Offloading for Load Balancing in Iterative Applications;language Agnostic Approach for Unification of Implementation Variants for Different Computing Devices;high Performance Dataframes from parallel Processing Patterns;global Access to Legacy Data-Sets in Multi-cloud Applications with Onedata;MD-Bench: A Generic Proxy-App Toolbox for State-of-the-Art Molecular Dynamics Algorithms;Breaking Down the parallel Performance of GROMACS, a High-Performance Molecular Dynamics Software;GPU-Based Molecular Dynamics of Turbulent Liquid Flows with OpenMM;a Novel parallel Approach for Modeling the Dynamics of Aerodynamically Interacting Particles in Turbulent Flows;reliable Energy Measurement on Heterogeneous Systems–on–Chip Based Environments;distributed Objective Function Evaluation for Optimization of Radiation Therapy Treatment Plans;a Generalized parallel Prefix Sums Algorithm for Arbitrary Size Arrays;GPU4SNN: GPU-Based Acceleration for Spiking Neural Network Simulations;Ant System Inspired Heuristic Optimization of UAVs Depl

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14th International conference on parallel Processing and Applied Mathematics, PPAM 2022

14th International Conference on Parallel Processing and App...

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14th International conference on parallel Processing and Applied Mathematics, PPAM 2022

ISBN: (纸本)9783031304415

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2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms 22

2QAN: A quantum compiler for 2-local qubit Hamiltonian simul...

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49th IEEE/ACM Annual International Symposium on Computer Architecture (ISCA)

作者： Lao, Lingling Browne, Dan E. UCL Dept Phys & Astron London England

ISBN: (纸本)9781450386104

Simulating quantum systems is one of the most important potential applications of quantum computers. The high-level circuit defining the simulation needs to be compiled into one that complies with hardware limitations such as qubit architecture (connectivity) and instruction (gate) set. General-purpose quantum compilers work at the gate level and have little knowledge of the mathematical properties of quantum applications, missing further optimization opportunities. Existing application-specific compilers only apply advanced optimizations in the scheduling procedure and are restricted to the CNOT or CZ gate set. In this work, we develop a compiler, named 2QAN, to optimize quantum circuits for 2-local qubit Hamiltonian simulation problems, a framework which includes the important quantum approximate optimization algorithm (QAOA). In particular, we exploit the flexibility of permuting different operators in the Hamiltonian (no matter whether they commute) and propose permutation-aware techniques for qubit routing, gate optimization and scheduling to minimize compilation overhead. 2QAN can target different architectures and different instruction sets. compilation results on four applications (up to 50 qubits) and three quantum computers (namely, Google Sycamore, IBMQ Montreal and Rigetti Aspen) show that 2QAN outperforms state-of-the-art general-purpose compilers and application-specific compilers. Specifically, 2QAN can reduce the number of inserted SWAP gates by 11.5X, reduce overhead in hardware gate count by 68.5X, and reduce overhead in circuit depth by 21X. Experimental results on the Montreal device demonstrate that benchmarks compiled by 2QAN achieve the highest fidelity.

关键词： Quantum computing quantum simulation quantum compilation

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Unfair Scheduling Patterns in NUMA architectures 19

Unfair Scheduling Patterns in NUMA Architectures

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proceedings of the International conference on parallel architectures and compilation techniques

作者： Naama Ben-David Ziv Scully Guy E. Blelloch Carnegie Mellon University

ISBN: (纸本)9781728136134

Lock-free algorithms are typically designed and analyzed with adversarial scheduling in mind. However, on real hardware, lock-free algorithms perform much better than the adversarial assumption predicts, suggesting that adversarial scheduling is unrealistic. In pursuit of more realistic analyses, recent work has studied lock-free algorithms under gentler scheduling models. This begs the question: what concurrent scheduling models are realistic? This issue is complicated by the intricacies of modern hardware, such as cache coherence protocols and non-uniform memory access (NUMA).In this paper, we thoroughly investigate concurrent scheduling on real hardware. To do so, we introduce Severus, a new benchmarking tool that allows the user to specify a lock-free workload in terms of the locations accessed and the cores participating. Severus measures the performance of the workload and logs enough information to reconstruct an execution *** demonstrate Severus's capabilities by uncovering the scheduling details of two NUMA machines with different microarchitectures: one AMD Opteron 6278 machine, and one Intel Xeon CPU E7-8867 v4 machine. We show that the two architectures yield very different schedules, but both exhibit unfair executions that skew toward remote nodes in contended workloads.

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A Novel Approach to Grover's Quantum Algorithm Simulation: Cloud-Based parallel Computing Enhancements 4

A Novel Approach to Grover's Quantum Algorithm Simulation: C...

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4th International conference on Smart Electronics and Communication, ICOSEC 2023

作者： Gejea, Adugna Mekonnen Mayakannan, S. Palacios, Rosana Marianela Hamad, Abdulsattar Abdullah Sundaram, Barani Alghamdi, Wajdi Bule Hora University Department of Computer Science Ethiopia Vidyaa Vikas College of Engineering and Technology Department of Mechanical Engineering Tamilnadu Namakkal India Department of Marketing Engineering Riobamba060155 Ecuador Dijlah University College Department of Medical Laboratory Techniques Baghdad Iraq King Abdulaziz University Faculty of Computing and Information Technology Department of Information Technology Jeddah21589 Saudi Arabia

ISBN: (纸本)9798350300888

A truly universal quantum computer is still on the small scale at the present. There has been no transition from the laboratory use of quantum computers to more widespread use of the technology. As a result, quantum simulation has emerged as the accepted norm for supporting the validation of quantum algorithms. Many conventional algorithms benefit from grover's quantum search method because it accelerates their usage of search heuristics. For better multi-core load balancing, memory utilization, and simulation efficiency, this research presented a high-performance grover method simulation that combines the benefits of grover's technique with the parallel of cloud computing. This study also suggests and experimentally compares five distinct cloud-based computing architectures that are well-suited to quantum simulation. Through research and testing, this study also verifies the optimization's efficiency. Depending on the size of the current configuration, the experimental results reveal that the simulation can reach 31 bits. © 2023 IEEE.

关键词： Cloud computing

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PIM-DL: Boosting DNN Inference on Digital Processing In-Memory architectures via Data Layout Optimizations 21

PIM-DL: Boosting DNN Inference on Digital Processing In-Memo...

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proceedings of the 30th International conference on parallel architectures and compilation techniques

作者： Minxuan Zhou Guoyang Clien Mohsen Imani Saransh Gupta Weifeng Zhang Tajana Rosing Department of Computer Science and Engineering University of California San Diego Alibaba Group Department of Computer Science University of California Irvine

ISBN: (纸本)9781665442787

Digital processing in-memory (DPIM) provides very low overhead, highly parallel computation in conventional memory, which significantly accelerates data-intensive workloads like deep neural networks (DNNs). DPIM-based DNN accelerators require that data be properly laid out to make the best use of the available in-memory operations. However, existing DPIM accelerators tend to optimize for a particular DNN dataflow, neglecting the large design space of data layout. This work systematically investigates the data layout for DPIM DNN acceleration. We propose a mapping framework to represent the whole design space of DPIM data layout for general DNN models. Our investigation shows that an exhaustive exploration on the whole design space for mapping a DNN application to DPIM architecture is not computationally tractable. Therefore, we propose a compiler-level optimization, PIM-DL, that finds highly efficient data layouts for DPIM DNN acceleration using a two-level dynamic programming algorithm and a heuristic-based search. Our experiments show that DNN DPIM solutions created by our PIM-DL provide 3.7× and 4.3× better performance and energy efficiency as compared to the state of the art under the same hardware constraints.

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Assessing the Lakehouse: Analysis, Requirements and Definition 25

Assessing the Lakehouse: Analysis, Requirements and Definiti...

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25th International conference on Enterprise Information Systems, ICEIS 2023

作者： Schneider, Jan Gröger, Christoph Lutsch, Arnold Schwarz, Holger Mitschang, Bernhard Institute of Parallel and Distributed Systems University of Stuttgart Universitätsstraße 38 Stuttgart70569 Germany Robert Bosch GmbH Borsigstraße 4 Stuttgart70469 Germany

ISBN: (纸本)9789897586484

The digital transformation opens new opportunities for enterprises to optimize their business processes by applying data-driven analysis techniques. For storing and organizing the required huge amounts of data, different types of data platforms have been employed in the past, with data warehouses and data lakes being the most prominent ones. Since they possess rather contrary characteristics and address different types of analytics, companies typically utilize both of them, leading to complex architectures with replicated data and slow analytical processes. To counter these issues, vendors have recently been making efforts to break the boundaries and to combine features of both worlds into integrated data platforms. Such systems are commonly called lakehouses and promise to simplify enterprise analytics architectures by serving all kinds of analytical workloads from a single platform. However, it remains unclear how lakehouses can be characterized, since existing definitions focus almost arbitrarily on individual architectural or functional aspects and are often driven by marketing. In this paper, we assess prevalent definitions for lakehouses and finally propose a new definition, from which several technical requirements for lakehouses are derived. We apply these requirements to several popular data management tools, such as Delta Lake, Snowflake and Dremio in order to evaluate whether they enable the construction of lakehouses. Copyright © 2023 by SCITEPRESS - Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

关键词： Data warehouses

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Massively parallel Open Modification Spectral Library Searching with Hyperdimensional Computing 22

Massively Parallel Open Modification Spectral Library Search...

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proceedings of the International conference on parallel architectures and compilation techniques

作者： Jaeyoung Kang Weihong Xu Wout Bittremieux Tajana Rosing University of California

ISBN: (纸本)9781450398688

Mass spectrometry, for protein identification, generates a massive number of spectra that need to be matched against a large database. In reality, most spectra remain mismatched due to unexpected post-translational modifications. Open modification search (OMS) improves the identification rate by considering every possible change in spectra, but it expands the search space exponentially. We propose HyperOMS, which redesigns OMS based on hyperdimensional computing to cope with such challenges. HyperOMS encodes floating-point spectral data with high-dimensional binary vectors, enabling the massive parallelism in OMS. Experimental results show that HyperOMS on GPU is up to 17× faster and 6.4× more energy efficient than the state-of-the-art GPU-based OMS tool [2] while providing comparable search quality.

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Reconfiguration Cost for Reconfigurable Computing architectures 23

Reconfiguration Cost for Reconfigurable Computing Architectu...

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23rd ACIS International Summer Virtual conference on Software Engineering, Artificial Intelligence, Networking and parallel/Distributed Computing, SNPD-Summer 2022

作者： Takano, Shigeyuki Amano, Hideharu Keio University Dept. of Informatics and Computer Science Kanagawa Japan

ISBN: (纸本)9798350396379

Reconfigurable computing systems show the advantage of high flexibility and high-performance or low-power relative to traditional computing systems. Reconfiguration can change user logic statically or dynamically. The reconfiguration is a key feature in the reconfigurable computing system, however, the reconfiguration techniques are not considered enough. One of the reconfiguration techniques must be chosen for usage target characteristics of reconfiguration. This article shows the cost of typical reconfiguration techniques which can be applied to not only field-programmable gate arrays (FPGAs) but also coarse-grained reconfigurable arrays (CGRAs). We call these microarchitectures, field-programmable logic (FPL). We focus on three device classes;traditional configurable FPL (ex. FPGA), a partially reconfigurable FPL and a multi-context FPL. We investigate how the size and frequency of reconfiguration can be taken care of and how much speed-up is theoretically expected from a perspective of reconfiguration cost. In addition, the investigation introduces temporal and spatial configuration cache techniques. © 2022 IEEE.

关键词： Reconfigurable architectures

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