We leverage highly successful prior projects sponsored by multiple NSF grants and gifts from industry: the BLAS-like Library Instantiation Software (BLIS) and the libflame efforts to lay the foundation for a new flexible framework by vertically integrating the dense linear and multi-linear (tensor) software stacks that are important to modern computing. This vertical integration will enable high-performance computations from node-level to massively-parallel, and across both CPU and GPU architectures. The effort builds on decades of experience by the research team turning fundamental research on the systematic derivation of algorithms (the NSF-sponsored FLAME project) into practical software for this domain, targeting single and multi-core (BLIS, TBLIS, and libflame), GPU-accelerated (SuperMatrix), and massively parallel (PLAPACK, Elemental, and ROTE) compute environments. This project will implement key linear algebra and tensor operations which highlight the flexibility and effectiveness of the new framework, and set the stage for further work in broadening functionality and integration into diverse scientific and machine learning software.

翻译：本文借助由多项美国国家科学基金会（NSF）资助项目及行业捐赠成功孵化的前期成果——类BLAS库实例化软件（BLIS）与libflame项目，通过垂直整合对现代计算至关重要的稠密线性与多线性（张量）软件栈，为构建新型灵活框架奠定基础。这种垂直集成将实现从单节点到大规模并行、横跨CPU与GPU架构的高性能计算。研究团队基于数十年经验，将算法系统推导的基础研究（NSF资助的FLAME项目）转化为该领域的实用软件，覆盖单核与多核（BLIS、TBLIS、libflame）、GPU加速（SuperMatrix）及大规模并行（PLAPACK、Elemental、ROTE）计算环境。本项目将实现关键线性代数与张量运算，以彰显新框架的灵活性与有效性，并为后续功能扩展及融入多样化科学计算与机器学习软件奠定基础。