Structure-Constrained Microcode Compression

E. Borin, G. Araújo, M. Breternitz, Youfeng Wu
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引用次数: 1

Abstract

Microcode enables programmability of (micro) architectural structures to enhance functionality and to apply patches to an existing design. As more features get added to a CPU core, the area and power costs associated with microcode increase. One solution to address the microcode size issue is to store the microcode in a compressed form and decompress it during execution. Furthermore, the reuse of a single hardware building block layout to implement different dictionaries in the two-level microcode compression reduces the cost and the design time of the decompression engine. However, the reuse of the hardware building block imposes structural constraints to the compression algorithm, and existing algorithms may yield poor compression. In this paper, we develop the SC2 algorithm that considers the structural constraint in its objective function and reduces the area expansion when reusing hardware building blocks to implement different dictionaries. Our experimental results show that the SC2 algorithm is able to produce similar sized dictionaries and achieves the similar compression ratio to the non-constrained algorithm.
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结构约束的微码压缩
微码允许(微)架构结构的可编程性,以增强功能并将补丁应用于现有设计。随着更多的功能被添加到CPU核心中,与微码相关的面积和功耗成本也在增加。解决微码大小问题的一种解决方案是以压缩形式存储微码,并在执行期间解压缩。此外,在二级微码压缩中重用单个硬件构建块布局来实现不同的字典,降低了解压引擎的成本和设计时间。然而,硬件构建块的重用对压缩算法施加了结构约束,现有算法可能产生较差的压缩。在本文中,我们开发了SC2算法,该算法在其目标函数中考虑了结构约束,并减少了重用硬件构建块实现不同字典时的面积扩展。实验结果表明,SC2算法能够产生与无约束算法相似大小的字典,并获得与无约束算法相似的压缩比。
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