CAREER: Unifying Heterogeneity of Extreme-Scale Cyberinfrastructures for Higher Productivity and Performance Portability

职业：统一超大规模网络基础设施的异构性，以提高生产力和性能可移植性

• 批准号: 1942973
• 负责人: Esam El-Araby
• 金额: $ 55.04万
• 依托单位: University of Kansas Center for Research Inc
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1942973&HistoricalAwards=false
• 关键词: CAREER; Unifying; Heterogeneity; Extreme; Scale

The goal of this project is to improve the performance portability and productivity (ease-of-use) of application development for extreme-scale heterogeneous reconfigurable architectures. This goal is in the scope of NSF's 10 Big Ideas, i.e., "Harnessing the Data Revolution", and a recent national report, i.e., "Extreme Heterogeneity 2018". The project will enable scientists in domains such as quantum simulation, experimental High-Energy Physics (HEP), and Fossil Energy (FE) to focus on the inherent characteristics, e.g., parallelism, of their applications rather than be burdened by the technological details of the underlying hardware. The project also significantly increases the longevity of domain scientists' legacy code. This project integrates the PI's research and teaching activities. The outcome from the project will produce undergraduate and graduate students who can contribute to solving problems in large-scale cyberinfrastructure. The project aims to include women and minority groups, through The Office of Diversity, Equity and Inclusion at the University of Kansas (KU), to receive training and engage in research collaboration with our group. This project will enable higher productivity in post-exascale (extreme-scale) heterogeneous architectures, advancing the PI's long-term research goals. These project goals align with: (1) the mission of the Office of Advanced Cyberinfrastructure (OAC) of NSF and the mission of NSF at large in promoting the progress of science and advancing the national prosperity and welfare, and (2) key strategies in the Kansas Building an Environment for Science and Technology (B.E.S.T.) for Innovation report. In addition, this project contributes to improving Kansas cyberinfrastructure, with a focus on building a workforce that will improve the state economy through STEM education.The project tackles three barriers to the efficient and wide spread deployment of extreme-scale high-performance reconfigurable computing (HPRC) systems: (1) the imbalance in processing heterogeneity where processing resources are integrated in different ways and proportions, (2) lack of hierarchical parallel programming models and/or insufficiency of existing models, and (3) lack of accurate formal models that are capable of describing the instantaneous and transient behaviors of HPRCs rather than only describing average behaviors. These challenges, especially the first two, have hindered wide adoption of HPRC by a broad range of HPC users and more specifically scientists in domains such as quantum simulation, experimental High-Energy Physics (HEP), and Fossil Energy (FE). Three research activities are proposed in this project: (1) development of a portable node-level abstraction layer and run-time libraries that will manage and transparently provide to the end-user a unified view of the hardware resources independent of their type (virtualized hardware), while exploiting inherent features of FPGAs, (2) creation of a new parallel domain-specific language (DSL) derived from Partitioned Global Address Space (PGAS) models using a multi-layered C-to-hardware compilation that supports a system-wide multi-level hierarchy of granularity and parallelism while also providing application portability, and (3) formulation and implementation of formal models and discrete-event simulation tools for design space exploration based on stochastic Markov chains and queueing networks. The proposed concepts and techniques will be implemented and evaluated to demonstrate their portability on three distinct heterogeneous large-scale HPC systems: (1) an experimental multi-node HPC cluster populated with Xilinx FPGA accelerators, (2) an Intel Hardware Accelerator Research Program (HARP) system, and (3) a DS8 state-of-the-art OS-less HPRC system from DirectStream.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个项目的目标是提高性能的可移植性和生产力（易用性）的应用程序开发的极端规模异构可重构体系结构。这一目标属于NSF的10大理念的范围，即，“驾驭数据革命”，以及最近的一份国家报告，2018年《极端异教徒》该项目将使量子模拟、实验高能物理（HEP）和化石能源（FE）等领域的科学家能够专注于固有特性，例如，并行性，而不是由底层硬件的技术细节负担。该项目还显著延长了领域科学家遗留代码的寿命。该项目整合了PI的研究和教学活动。该项目的成果将培养出能够为解决大规模网络基础设施问题做出贡献的本科生和研究生。该项目旨在通过堪萨斯大学（KU）的多样性，公平和包容办公室，将妇女和少数群体纳入其中，接受培训并与我们的团队进行研究合作。该项目将提高后exascale（极端规模）异构架构的生产力，推进PI的长期研究目标。这些项目目标符合：（1）NSF高级网络基础设施办公室（OAC）的使命和NSF在促进科学进步和促进国家繁荣和福利方面的使命，以及（2）堪萨斯建设科学技术环境（B.E.S.T.）的关键战略。创新报告。此外，该项目还有助于改善堪萨斯州的网络基础设施，重点是通过STEM教育建立一支能够改善该州经济的劳动力队伍。该项目解决了高效和广泛部署超大规模高性能可重构计算（HPRC）系统的三个障碍：（1）处理异质性的不平衡，其中处理资源以不同的方式和比例被整合，（2）缺乏分层并行编程模型和/或现有模型的不足，以及（3）缺乏能够描述HPRC的瞬时和瞬态行为而不是仅描述平均行为的精确形式模型。这些挑战，特别是前两个，阻碍了广泛的HPC用户，更具体地说是量子模拟，实验高能物理（HEP）和化石能源（FE）等领域的科学家广泛采用HPRC。本项目拟开展三项研究活动：（1）开发可移植的节点级抽象层和运行时库，这些库将管理并透明地向最终用户提供硬件资源的统一视图，而与其类型无关（虚拟化硬件），同时利用FPGA的固有特性，（2）创建一种新的并行域特定语言（DSL），该DSL使用支持系统范围的多个层次结构的粒度和并行性，同时也提供了应用程序的可移植性，和（3）制定和实施的形式化模型和离散事件仿真工具的设计空间探索的基础上随机马尔可夫链和嵌套网络。 将实施和评估所提出的概念和技术，以证明它们在三个不同的异构大型HPC系统上的可移植性：（1）采用Xilinx FPGA加速器的实验性多节点HPC集群，（2）英特尔硬件加速器研究计划（HARP）系统，以及（3）DS 8最先进的操作系统-该奖项反映了NSF的法定使命，并通过使用基金会的智力价值进行评估而被认为值得支持和更广泛的影响审查标准。

项目成果

Quantum Dimension Reduction for Pattern Recognition in High-Resolution Spatio-Spectral Data

高分辨率时空光谱数据中模式识别的量子降维

• DOI: 10.1109/tc.2020.3034883
• 发表时间: 2022
• 期刊: IEEE Transactions on Computers
• 影响因子: 3.7
• 作者: Mahmud, Naveed;Haase-Divine, Bennett;MacGillivray, Andrew;El-Araby, Esam
• 通讯作者: El-Araby, Esam

Efficient Data Encoding and Decoding for Quantum Computing

• DOI: 10.1109/qce53715.2022.00110
• 发表时间: 2022-09
• 期刊: 2022 IEEE International Conference on Quantum Computing and Engineering (QCE)
• 作者: Naveed Mahmud;M. Jeng;Md. Alvir Islam Nobel;Manu Chaudhary;S. Islam;David Levy;E. El-Araby

Efficient Computation Techniques and Hardware Architectures for Unitary Transformations in Support of Quantum Algorithm Emulation

• DOI: 10.1007/s11265-020-01569-4
• 发表时间: 2020-07
• 期刊: Journal of Signal Processing Systems
• 作者: Naveed Mahmud;Bennett Haase-Divine;Annika Kuhnke;Apurva Rai;A. MacGillivray;E. El-Araby

Towards Complete Emulation of Quantum Algorithms using High-Performance Reconfigurable Computing

使用高性能可重构计算实现量子算法的完整仿真

• 发表时间: 2021
• 期刊: and Analysis (SC’21
• 作者: Mahmud, Naveed;El-Araby, Esam
• 通讯作者: El-Araby, Esam

Combining quantum key distribution with chaotic systems for free-space optical communications

• DOI: 10.1007/s11128-021-03299-3
• 发表时间: 2021-10
• 期刊: Quantum Information Processing
• 影响因子: 2.5
• 作者: Naveed Mahmud;A. MacGillivray;Apurva Rai;Jenna Patterson;Adam Gharaibeh;E. El-Araby;H. Shaw