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334 results on '"Bayraktar, Harun"'

1. Hardware Trends Impacting Floating-Point Computations In Scientific Applications

Author

Dongarra, Jack, Gunnels, John, Bayraktar, Harun, Haidar, Azzam, and Ernst, Dan

Subjects
Mathematics - Numerical Analysis, 90C10, 65F99, 65G30, 65G99, G.1.3, G.4, B.2.m, D.3.4
Abstract

The evolution of floating-point computation has been shaped by algorithmic advancements, architectural innovations, and the increasing computational demands of modern technologies, such as artificial intelligence (AI) and high-performance computing (HPC). This paper examines the historical progression of floating-point computation in scientific applications and contextualizes recent trends driven by AI, particularly the adoption of reduced-precision floating-point types. The challenges posed by these trends, including the trade-offs between performance, efficiency, and precision, are discussed, as are innovations in mixed-precision computing and emulation algorithms that offer solutions to these challenges. This paper also explores architectural shifts, including the role of specialized and general-purpose hardware, and how these trends will influence future advancements in scientific computing, energy efficiency, and system design.

Published
2024

2. cuQuantum SDK: A High-Performance Library for Accelerating Quantum Science

Author

Bayraktar, Harun, Charara, Ali, Clark, David, Cohen, Saul, Costa, Timothy, Fang, Yao-Lung L., Gao, Yang, Guan, Jack, Gunnels, John, Haidar, Azzam, Hehn, Andreas, Hohnerbach, Markus, Jones, Matthew, Lubowe, Tom, Lyakh, Dmitry, Morino, Shinya, Springer, Paul, Stanwyck, Sam, Terentyev, Igor, Varadhan, Satya, Wong, Jonathan, and Yamaguchi, Takuma

Subjects
Quantum Physics, Computer Science - Performance, Computer Science - Software Engineering, 68Q12, 68Q09, 81P68
Abstract

We present the NVIDIA cuQuantum SDK, a state-of-the-art library of composable primitives for GPU-accelerated quantum circuit simulations. As the size of quantum devices continues to increase, making their classical simulation progressively more difficult, the availability of fast and scalable quantum circuit simulators becomes vital for quantum algorithm developers, as well as quantum hardware engineers focused on the validation and optimization of quantum devices. The cuQuantum SDK was created to accelerate and scale up quantum circuit simulators developed by the quantum information science community by enabling them to utilize efficient scalable software building blocks optimized for NVIDIA GPU platforms. The functional building blocks provided cover the needs of both state vector- and tensor network- based simulators, including approximate tensor network simulation methods based on matrix product state, projected entangled pair state, and other factorized tensor representations. By leveraging the enormous computing power of the latest NVIDIA GPU architectures, quantum circuit simulators that have adopted the cuQuantum SDK demonstrate significant acceleration, compared to CPU-only execution, for both the state vector and tensor network simulation methods. Furthermore, by utilizing the parallel primitives available in the cuQuantum SDK, one can easily transition to distributed GPU-accelerated platforms, including those furnished by cloud service providers and high-performance computing systems deployed by supercomputing centers, extending the scale of possible quantum circuit simulations. The rich capabilities provided by the SDK are conveniently made available via both Python and C application programming interfaces, where the former is directly targeting a broad Python quantum community and the latter allows tight integration with simulators written in any programming language., Comment: paper accepted at QCE 2023, journal reference will be updated whenever available

Published
2023

47. Reactions of Short, Intermediate and Long Day Onion Genotypes in Turkish National Onion Breeding Program to Fusarium Basal Rot Disease.

Author

Polat, Zühtü, Beşirli, Gülay, Sönmez, İbrahim, and Bayraktar, Harun

Abstract

Copyright of International Journal of Agriculture & Wildlife Science is the property of International Journal of Agriculture & Wildlife Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2023
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