Fortress provides a nice set of abstractions used widely in scientific computing. The use of such abstractions enhances the productivity of programmers/users. Also, in scientific computations, boilerplate code has extensive usage. Keeping this in view, we embed Fortress abstractions in an X10 environment so that we can get better productivity without losing performance. In this paper, we transform Fortress into X10 through a transcompilation system. We describe compilation strategies for a few important constructs and discuss the performance of the generated X10 code with respect to the original Fortress code. The translated X10 code outperforms the original Fortress code with a maximum of 206x speedup achieved in the best case. The system also supports the multiresolution language approach that simplifies parallel programming by allowing domain scientists to write programs in the Fortress syntax that is closer to the mathematical notation. The translated X10 code, which can further be compiled to either C++ or Java, implicitly assures performance and may further be optimized for performance by utilizing the low-level features of X10 (or C++/Java).

Fortress 提供了一组在科学计算中广泛使用的很好的抽象。此类抽象的使用提高了程序员/用户的生产力。此外，在科学计算中，样板代码具有广泛的用途。考虑到这一点，我们将 Fortress 抽象嵌入到 X10 环境中，以便在不损失性能的情况下获得更高的生产力。在本文中，我们通过转编译系统将 Fortress 转换为 X10。我们描述了一些重要结构的编译策略，并讨论了生成的 X10 代码相对于原始 Fortress 代码的性能。翻译后的 X10 代码优于原始 Fortress 代码，在最佳情况下最高可实现 206 倍的加速。该系统还支持多分辨率语言方法，该方法允许领域科学家以更接近数学符号的 Fortress 语法编写程序，从而简化并行编程。翻译后的 X10 代码可以进一步编译为 C++ 或 Java，隐含地保证了性能，并且可以通过利用 X10（或 C++/Java）的低级特性进一步优化性能。