Vector-Reduction Techniques for Arithmetic Pipelines
Vector-Reduction Techniques for Arithmetic Pipelines
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DOI：
10.1109/tc.1985.1676580
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发表时间：
1985-05
影响因子：
3.7
通讯作者：
L. Ni;K. Hwang
中科院分区：
文献类型：
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作者：
L. Ni;K. Hwang
向量归约算法接受向量作为输入，并产生标量作为输出。这类向量运算形成了许多科学计算的基础，例如内积和求向量分量的最大值。流水线处理器上的向量归约需要围绕流水线的反馈连接。由于这种流水线的输出取决于先前的输出，因此反馈输入的不适当控制可能会破坏流水线的益处。本文提出了两种新的矢量约简技术。除了节省约简时间和消除中间存储（与Kuck方法和Kogge方法相比），新方法将大大简化实现向量约简操作所需的机器级编程工作。介绍了一种使用同一算术流水线将多个向量减少为相应标量的交织技术。可以通过交错多个向量归约过程来充分利用流水线。所提出的技术可以应用于提高科学超级计算机中的向量算术流水线的性能。
Vector-reduction arithmetic accepts vectors as inputs and produces scalars as outputs. This class of vector operation forms the basis of many scientific computations, such as inner product and finding the maximum among the vector components. Vector reduction on a pipeline processor demands a feedback connection around the pipeline. Since the output of such a pipeline depends on the previous output, improper control of the feedback input may destroy the benefit from pipelining. Two new vector-reduction techniques are proposed in this paper. In addition to saving reduction time and eliminating intermediate storage (as compared to Kuck's method and Kogge's method), the new methods will greatly simplify the machine-level programming effort needed to implement vector-reduction operations. An interleaved technique is introduced to reduce multiple vectors to corresponding scalars using the same arithmetic pipeline. The pipeline can be fully utilized by interleaving multiple vector-reduction processes. The proposed techniques can be applied to improve the performance of vector-arithmetic pipelines in scientific supercomputers.