Shallow embedding of DSLs via online partial evaluation
Shallow embedding of DSLs via online partial evaluation
复制标题
DOI：
10.1145/2814204.2814208
复制
发表时间：
2015-10
期刊：
影响因子：
--
通讯作者：
Roland Leißa;Klaas Boesche;Sebastian Hack;Richard Membarth;P. Slusallek
中科院分区：
文献类型：
--
作者：
Roland Leißa;Klaas Boesche;Sebastian Hack;Richard Membarth;P. Slusallek
本文通过在线部分评估调查了DSL的浅嵌入。为此，我们介绍了一个新颖的在线局部评估者，用于延续通过的风格语言。我们认为，与先前的工作相反，它具有可预测的终止政策，在实践中效果很好。我们使用PCF的持续通过变体正式介绍我们的方法，并证明其终止属性。我们在视觉和高性能计算领域通过实验评估我们的技术，并表明我们的评估器为CPU以及与手工调整的专家代码的性能相匹配的GPU生成了高度专业化和有效的代码。
This paper investigates shallow embedding of DSLs by means of online partial evaluation. To this end, we present a novel online partial evaluator for continuation-passing style languages. We argue that it has, in contrast to prior work, a predictable termination policy that works well in practice. We present our approach formally using a continuation-passing variant of PCF and prove its termination properties. We evaluate our technique experimentally in the field of visual and high-performance computing and show that our evaluator produces highly specialized and efficient code for CPUs as well as GPUs that matches the performance of hand-tuned expert code.