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The use of large-scale machine learning methods is becoming ubiquitous in many applications ranging from business intelligence to self-driving cars. These methods require a complex computation pipeline consisting of various types of…

Databases · Computer Science 2021-11-10 Yongyang Yu , Mingjie Tang , Walid G. Aref

Planning energy production is a challenging task due to its cost-sensitivity, fast-moving energy markets, uncertainties in demand, and technical constraints of power plants. Thus, more complex models of this so-called \emph{unit commitment…

Quantum Physics · Physics 2024-03-07 Pascal Halffmann , Patrick Holzer , Kai Plociennik , Michael Trebing

The rapid evolution of artificial intelligence (AI) is leading to a new generation of hardware accelerators optimized for deep learning. Some of the designs of these accelerators are general enough to allow their use for other…

Computational Engineering, Finance, and Science · Computer Science 2019-12-18 Fantine Huot , Yi-Fan Chen , Robert Clapp , Carlos Boneti , John Anderson

We have repurposed Google Tensor Processing Units (TPUs), application-specific chips developed for machine learning, into large-scale dense linear algebra supercomputers. The TPUs' fast inter-core interconnects (ICI)s, physically…

Computational Physics · Physics 2022-09-14 Adam G. M. Lewis , Jackson Beall , Martin Ganahl , Markus Hauru , Shrestha Basu Mallick , Guifre Vidal

Database systems encompass several performance-critical optimization tasks, such as join ordering and index tuning. As data volumes grow and workloads become more complex, these problems have become exponentially harder to solve…

Databases · Computer Science 2026-01-21 Hanwen Liu , Ibrahim Sabek

A processor's memory hierarchy has a major impact on the performance of running code. However, computing platforms, where the actual hardware characteristics are hidden from both the end user and the tools that mediate execution, such as a…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-07-10 Keith Cooper , Xiaoran Xu

The combination of machine learning and quantum computing has emerged as a promising approach for addressing previously untenable problems. Reservoir computing is an efficient learning paradigm that utilizes nonlinear dynamical systems for…

Quantum Physics · Physics 2020-08-26 Jiayin Chen , Hendra I. Nurdin , Naoki Yamamoto

Quantum computing proposes a revolutionary paradigm that can radically transform numerous scientific and industrial application domains. To realize this promise, these new capabilities need software solutions that are able to effectively…

Quantum Physics · Physics 2025-07-11 Otso Kinanen , Andrés D. Muñoz-Moller , Vlad Stirbu , Tommi Mikkonen

Over the most recent years, quantized graph neural network (QGNN) attracts lots of research and industry attention due to its high robustness and low computation and memory overhead. Unfortunately, the performance gains of QGNN have never…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-01-03 Yuke Wang , Boyuan Feng , Yufei Ding

Deep learning (DL) compilers rely on cost models and auto-tuning to optimize tensor programs for target hardware. However, existing approaches depend on large offline datasets, incurring high collection costs and offering suboptimal…

Machine Learning · Computer Science 2026-04-15 Chaoyao Shen , Linfeng Jiang , Yixian Shen , Tao Xu , Guoqing Li , Anuj Pathania , Andy D. Pimentel , Meng Zhang

Relational database management systems (RDBMSes) can process general-purpose queries, but often have lower performance compared to custom-built solutions for specific queries. For example, consider a group-by query over a few known groups…

Databases · Computer Science 2026-05-01 Geoffrey X. Yu , Ryan Marcus , Tim Kraska

The use of trusted hardware has become a promising solution to enable privacy-preserving machine learning. In particular, users can upload their private data and models to a hardware-enforced trusted execution environment (e.g. an enclave…

Hardware Architecture · Computer Science 2020-11-13 Peichen Xie , Xuanle Ren , Guangyu Sun

High-performance computing (HPC) has evolved over decades through multiple architectural transitions, from vector supercomputers to massively parallel CPU clusters and GPU-accelerated systems, continuously expanding the frontier of…

Quantum Physics · Physics 2026-04-23 Suman Raj , Siva Sai , Yogesh Simmhan , Kyle Chard , Rajkumar Buyya

The increasing interest in the usage of Artificial Intelligence techniques (AI) from the research community and industry to tackle "real world" problems, requires High Performance Computing (HPC) resources to efficiently compute and scale…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-01-14 David Brayford , Sofia Vallecorsa , Atanas Atanasov , Fabio Baruffa , Walter Riviera

Quantum computing and neural networks show great promise for the future of information processing. In this paper we study a quantum reservoir computer (QRC), a framework harnessing quantum dynamics and designed for fast and efficient…

Disordered Systems and Neural Networks · Physics 2020-06-29 Aki Kutvonen , Takahiro Sagawa , Keisuke Fujii

Quantum reservoir computing is a computing approach which aims at utilising the complexity and high-dimensionality of small quantum systems, together with the fast trainability of reservoir computing, in order to solve complex tasks. The…

Quantum Physics · Physics 2024-01-19 Saud Čindrak , Brecht Donvil , Kathy Lüdge , Lina Jaurigue

As the popularity of quantum computing continues to grow, efficient quantum machine access over the cloud is critical to both academic and industry researchers across the globe. And as cloud quantum computing demands increase exponentially,…

Quantum Physics · Physics 2022-03-28 Gokul Subramanian Ravi , Kaitlin N. Smith , Prakash Murali , Frederic T. Chong

For the past two decades, the DB community has devoted substantial research to take advantage of cheap clusters of machines for distributed data analytics -- we believe that we are at the beginning of a paradigm shift. The scaling laws and…

Databases · Computer Science 2025-08-05 Bowen Wu , Wei Cui , Carlo Curino , Matteo Interlandi , Rathijit Sen

Simulation is essential for developing quantum hardware and algorithms. However, simulating quantum circuits on classical hardware is challenging due to the exponential scaling of quantum state space. While factorized tensors can greatly…

Quantum Physics · Physics 2021-12-21 Taylor L. Patti , Jean Kossaifi , Susanne F. Yelin , Anima Anandkumar

Data-intensive applications impact many domains, and their steadily increasing size and complexity demands high-performance, highly usable environments. We integrate a set of ideas developed in various data science and data engineering…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-08-02 Supun Kamburugamuve , Chathura Widanage , Niranda Perera , Vibhatha Abeykoon , Ahmet Uyar , Thejaka Amila Kanewala , Gregor von Laszewski , Geoffrey Fox