Make Larger Vector Register Sizes New Challenges?: Lessons Learned from the Area of Vectorized Lightweight Compression Algorithms
Make Larger Vector Register Sizes New Challenges?: Lessons Learned from the Area of Vectorized Lightweight Compression Algorithms
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使更大的矢量寄存器尺寸成为新的挑战？：从矢量化轻量级压缩算法领域汲取的经验教训
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Wolfgang Lehner
中科院分区：
文献类型：
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作者：
Dirk Habich;Patrick Damme;A. Ungethüm;Wolfgang Lehner
数据和硬件属性的利用是高效数据管理的核心方面。这尤其适用于存储器内数据处理的领域。除了增加主内存容量外，内存中数据处理还受益于基于轻量级压缩数据的新处理概念。为了加速压缩和解压缩，一个活跃的研究领域涉及这些算法的硬件功能的专业化，如使用SIMD指令的矢量化。大多数矢量化实现都是针对128位矢量寄存器提出的。然而，硬件供应商仍然增加向量寄存器大小，由此在大多数情况下可以直接转换到这些更宽的向量大小。因此，我们系统地研究了具有更宽向量大小的不同SIMD指令集扩展对直接转换实现的行为的影响。在本文中，我们将描述我们的评估方法，并提出我们的详尽评估的选择性结果。特别是，我们将强调一些挑战，并提出应对这些挑战的初步方法。
The exploitation of data as well as hardware properties is a core aspect for efficient data management. This holds in particular for the field of in-memory data processing. Aside from increasing main memory capacities, in-memory data processing also benefits from novel processing concepts based on lightweight compressed data. To speed up compression as well as decompression, an active research field deals with the specialization of these algorithms to hardware features such as vectorization using SIMD instructions. Most of the vectorized implementations have been proposed for 128 bit vector registers. However, hardware vendors still increase the vector register sizes, whereby a straightforward transformation to these wider vector sizes is possible in most-cases. Thus, we systematically investigated the impact of different SIMD instruction set extensions with wider vector sizes on the behavior of straightforward transformed implementations. In this paper, we will describe our evaluation methodology and present selective results of our exhaustive evaluation. In particular, we will highlight some challenges and present first approaches to tackle them.
DOI：
10.1007/978-3-319-31409-9_6
发表时间：
2015
期刊：
影响因子：
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作者：
Patrick Damme;Dirk Habich;Wolfgang Lehner
通讯作者：
Wolfgang Lehner
轻量级数据压缩算法：实验调查（实验和分析）
DOI：
10.5441/002/edbt.2017.08
发表时间：
2017
期刊：
影响因子：
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作者：
Patrick Damme;Dirk Habich;Juliana Hildebrandt;Wolfgang Lehner
通讯作者：
Wolfgang Lehner