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A preliminary study on data allocation of on-chip dual memory banks

机译:芯片双记忆库数据分配的初步研究

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Efficient utilization of memory space is extremely important in embedded applications. Many DSP vendors provide a dual memory bank system that allows the applications to access two memory banks simultaneously. Unfortunately we have found that existing vendor-provided compilers cannot generate highly efficient code for dual memory space because current compiler technology is unable to fully exploit this DSP hardware feature. Thus, software developers for an embedded processor have hard time developing software by hand in assembly to exploit the hardware feature efficiently In this paper, we present a preliminary study of a memory allocation technique for dual memory space. Through there has been some work done for dual memory banks, efficient code was generated but it required so long compilation time. Although the compilation speed is relatively of less importance for embedded-processors, it still should have a reasonable upper bound particularly for industry compilers due to ever increasing demands on faster time-to-market embedded software design and implementation. To achieve such reasonable compilation speed, we simplified the dual memory bank allocation problem by decoupling our code generation into five phases: register class allocation, code compaction, memory bank assignment, register assignment and memory offset assignment. The experimental results show that our generated codes perform as good as previous work, yet reducing the compilation time dramatically.
机译:在嵌入式应用程序中有效利用内存空间非常重要。许多DSP供应商提供了一个双存储体系,允许应用程序同时访问两个存储体。遗憾的是,我们发现现有的供应商提供的编译器不能为双记忆空间生成高效的代码,因为当前编译器技术无法充分利用此DSP硬件功能。因此,软件开发者的嵌入式处理器具有很难用手组件开发软件来有效地利用硬件特征在本文中,我们提出了双存储空间的存储器分配技术的初步研究。通过有一些工作为双内存银行完成,生成有效的代码,但需要这么长的编译时间。虽然编译速度对嵌入式处理器的重要性相对较小,但由于在更快的上市时间嵌入式软件设计和实现上,它仍应适用于行业编制者的合理上限。为了实现如此合理的编译速度,我们通过将代码生成解耦为五个阶段:寄存器类分配,代码压缩,内存银行分配,寄存器分配和内存偏移分配来简化双内存银行分配问题。实验结果表明,我们所生成的代码与以前的工作一样好,但大大降低了编译时间。

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