Automatic vector instruction selection for dynamic compilation

R. Barik, Jisheng Zhao, Vivek Sarkar
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引用次数: 6

Abstract

Accelerating program performance via short SIMD vector units is very common in modern processors, as evidenced by the use of SSE, MMX, and AltiVec SIMD instructions in multimedia, scientific, and embedded applications. To take full advantage of the vector capabilities, a compiler needs to generate efficient vector code automatically. However, most commercial and open-source compilers still fall short of using the full potential of vector units, and only generate vector code for simple loop nests. In this poster, we present the design and implementation of an auto-vectorization framework in the back-end of a dynamic compiler that not only generates optimized vector code but is also well integrated with the instruction scheduler and register allocator. Additionally, we describe a vector instruction selection algorithm based on dynamic programming. Our results obtained in JikesRVM dynamic compilation environment show performance improvement of up to 57.71% on an Intel Xeon processor, compared to non-vectorized execution.
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动态编译的自动矢量指令选择
通过短SIMD矢量单元加速程序性能在现代处理器中非常常见,多媒体、科学和嵌入式应用程序中使用SSE、MMX和AltiVec SIMD指令证明了这一点。为了充分利用矢量功能,编译器需要自动生成高效的矢量代码。然而,大多数商业和开源编译器仍然不能充分利用向量单元的潜力,并且只能为简单的循环巢生成向量代码。在这张海报中,我们展示了动态编译器后端的自动矢量化框架的设计和实现,该框架不仅生成优化的矢量代码,而且还与指令调度程序和寄存器分配器很好地集成在一起。此外,我们还描述了一种基于动态规划的矢量指令选择算法。我们在JikesRVM动态编译环境中获得的结果显示,与非矢量化执行相比,在Intel Xeon处理器上的性能提高高达57.71%。
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