Hardware Acceleration Technologies Enabling Polynomial System Solving

支持多项式系统求解的硬件加速技术

• 批准号: 262137-2013
• 负责人: MorenoMaza, Marc
• 金额: $ 1.46万
• 依托单位: University of Western Ontario
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=571243
• 关键词: Hardware; Acceleration; Technologies; Enabling; Polynomial

Hardware acceleration technologies (multicore processors, graphics processing units, field-programmable gate arrays) provide vast opportunities for innovation in scientific computing. For instance, general- -purpose computation on graphics hardware now allows several types of calculations (simulation, data analysis, etc.) to satisfy the constraints of real time computing. At the same time, the pervasive ubiquity and diversity of parallel architectures creates major challenges for scientists and engineers. On the scientific side, this situation leads to a quest for algorithms and software capable of exploiting the various levels of parallelism, from hardware acceleration technologies to clusters. On the software engineering side, techniques for adapting legacy code and supporting the new hardware are in demand. This proposal aims at developing techniques that will permit mathematical software to take the best advantage of parallel architectures and hierarchical memories. Our focus is on graphics processing units and their support to polynomial system solvers for which specific features (intermediate expression swell, irregular data patterns) make this proposal even more challenging. The proposed research program comprises three projects which cover theoretical aspects, algorithms, software implementation and applications of those.

硬件加速技术（多层处理器，图形处理单元，现场编程 门阵列）为科学计算中的创新提供了巨大的机会。例如，一般 - - 图形硬件上的可使用计算现在允许几种类型的计算（仿真，数据 分析等）以满足实时计算的限制。同时，普遍 平行体系结构的普遍性和多样性为科学家和工程师带来了重大挑战。 从科学方面来说，这种情况导致寻求能够利用的算法和软件 从硬件加速技术到集群的各种并行性级别。在软件上 工程方面，适应旧版代码的技术和支持新硬件的技术。 该建议旨在开发将允许数学软件采取最佳状态的技术 平行体系结构和分层记忆的优势。我们的重点是图形处理单元 以及它们对特定特征的多项式系统求解器的支持（中间表达膨胀， 不规则的数据模式）使该建议更具挑战性。拟议的研究计划 包括三个涵盖理论方面，算法，软件实施和的项目 这些申请。