Improving Productivity of Algorithm and System Implementation in Scaled up Applications

提高劳动密集型高性能软件的生产率和可靠性是一个重要的科学问题，具有明显的经济后果。 这项研究正在测试一种全新的编译和元编译方法的可行性，以提高C编程语言中高性能算法软件的生产力和可靠性。 该研究结合了部分评估的深度嵌套SETL数据结构，数据结构和算法选择技术，以及转换技术从关系查询优化。 这导致了SETL的静态类型变体，预计可以以高翻译率生成大规模C程序。

Improving productivity and reliability of labor-intensive high-performance software is an important scientific problem with obvious economic ramifications. This research is testing the feasibility of a radically new compilation and meta-compilation methodology to improve productivity and reliability for high-performance algorithmic software in the C programming language. The research combines partial evaluation for deeply-nested SETL data structures, data structure and algorithm selection techniques, and transformational techniques from relational query optimization. This is leading to a statically typed variant of SETL from which it is expected large-scale C programs can be generated at a high translation rate.***