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HyComp: A hybrid cache compression method for selection of data-type-specific compression methods

机译:HyComp:一种混合缓存压缩方法,用于选择特定于数据类型的压缩方法

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Proposed cache compression schemes make design-time assumptions on value locality to reduce decompression latency. For example, some schemes assume that common values are spatially close whereas other schemes assume that null blocks are common. Most schemes, however, assume that value locality is best exploited by fixed-size data types (e.g., 32-bit integers). This assumption falls short when other data types, such as floating-point numbers, are common. This paper makes two contributions. First, HyComp - a hybrid cache compression scheme - selects the best-performing compression scheme, based on heuristics that predict data types. Data types considered are pointers, integers, floating-point numbers and the special (and trivial) case of null blocks. Second, this paper contributes with a compression method that exploits value locality in data types with predefined semantic value fields, e.g., as in the exponent and the mantissa in floating-point numbers. We show that HyComp, augmented with the proposed floating-point-number compression method, offers superior performance in comparison with prior art.
机译:提议的缓存压缩方案对值局部性进行设计时假设,以减少解压缩延迟。例如,一些方案假定公共值在空间上接近,而其他方案假定空块是公共的。但是,大多数方案都假定值局部性最好由固定大小的数据类型(例如32位整数)利用。当其他数据类型(例如浮点数)很常见时,这种假设就不成立了。本文做出了两个贡献。首先,HyComp(一种混合缓存压缩方案)根据预测数据类型的启发式方法选择性能最佳的压缩方案。所考虑的数据类型是指针,整数,浮点数以及空块的特殊(且琐碎)情况。其次,本文提供了一种压缩方法,该方法利用具有预定义语义值字段的数据类型中的值局部性,例如浮点数中的指数和尾数。我们显示,与现有技术相比,通过提出的浮点数压缩方法增强的HyComp提供了卓越的性能。

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