向量化

C.图。串行循环向量化的图论方法

The S. C. graph theory method for the vectorization of serial loops

FORTRANDO循环向量化的相关函数法

An associative function algorithm for the vectorization of FORTRAN Do-loops

该模型可以用以指导对JavaScript程序的向量化优化，并能够对优化结果进行较为准确的预测。

The new model can be used to guide the optimizing procedure of JavaScript programs and predict the result speedup .

本文讨论FORTRAN内层DO循环的向量化问题。

In this paper , the problems on vectorization of FORTRAN inner DO - loop are discussed .

然而应用程序一般很难直接适用于SIMD扩展，需要对其进行必要的向量化处理。

However , applications can be hardly adapt to SIMD Extension , vectorizing them before running is essential .

本文利用多线程、向量化运算等技术加速Shear-Warp算法，充分发挥多核CPU的特点，使其能够适应当前CPU的发展趋势，被更广泛的应用推广。

In this paper we use multi-thread and vectorization methods to accelerate the Shear-warp algorithm which make full use of the multi-core CPU Characteristics .

在YH-1上将程序向量化，大大节省了计算时间。

Computing time is much reduced with program vectorized in YH-1 .

本文针对FORTRANDO循环，给出并证明了在允许DO体加入暂存语句条件下的向量化判定定理，并在此基础上形成以数组项为结点的相关分析法。

This paper gives and proves the decision theory of vectorization on the condition of adding temporary storage statements to DO body for FORTRAN DO loops .

本文向您提供了对IBMMASS库以及IBMXLC/C++和XLFortran汇编器的自动向量化功能的描述。

This article has offered you a description of the IBM MASS libraries , and the auto-vectorization capabilities of the IBM XL C / C + + and XL Fortran compilers .

对文档向量化中常用的TF-IDF公式，互信息量公式以及信息增益公式进行了分析。

The most common used formulas : TF-IDF , MI , and IG were analyzed .

基于线性预测系数自适应前后向量化的可变速率MELP语音编码

Variable - rate MELP speech coder based on adaptive forward - backward quantization of linear predictive coefficients

同时采用了数据挖掘中的K-means算法，将网页中获取的检索信息（经过向量化处理后的信息）进行聚类分析，并且将聚类分析后的分类结果集返回给用户。

Meanwhile , adopt the K-means algorithm of the data mining to cluster analysis the retrieval information results from the web and return the clustered results to the user .

这个发行版包含很多变化&其中两个特别的变化是引入了新的优化框架（TreeSSA）和支持自动向量化（autovectorization）。

This release included a large number of changes & two in particular being the introduction of a new optimization framework ( Tree SSA ) and support for autovectorization .

对基本的Apriori算法进行研究改进，采用了向量化的数据结构，减少了输入数据集的存储空间，可以将数据集放入内存，避免对数据库多次扫描带来的I/O开销，提高了算法的效率。

We make some improvement in Apriori algorithm . First , use the vector data structure , reduce the space of the input dataset , so it can be put into the main memory and avoid the overhead caused by scanning database many times , the efficiency is improved .

事实上，核心转换代码实际几乎已经向量化了。

In fact , the core conversion code is actually almost already vectorized .

采用向量化运算进行图像融合的真实感纹理映射

Realistic Texture Mapping Using Vector Operation for Image Synthesis

IF语句向量化的再识别算法

Re-recognition Algorithm for Vectorization of Loops with IF Statements

向量化的本质认识和功能分析

The Recognition of Vectored Essence and Functional Analysis

接着针对向量化的邮件表示，建立了一种基于信息熵的决策树邮件分类识别模型；

And then bring forward a determination tree classifying model base on information entropy .

如果您想要取消自动向量化的激活，那么您可以添加选项–qhot=novector。

If you want to disable auto-vectorization , you can add the option-qhot = novector .

串行运算向量化的相关分析方法

The relevance analysis approach to Vectorization

向量化中数据依赖关系的强化分析

Augmented data dependency analysis in Vectorization

DO循环向量化的追踪遍数

The tracing number of do loop

向量化的区间分割技术

Interval segmentation technique in Vectorization

向量化中临时数组的引入

Introducing temporary array in Vectorization

向量化中的识别指导性指令

Recognition Directors in Vectorization

自动向量化的汇编器选项

Compiler options for auto-vectorization

多项式预处理共轭梯度算法的高度向量化，且不需要构造全局矩阵，它在大规模并行结构中能被有效地实现。

The high-vectorization of Multinomial Preprocessing Conjugate Gradient Method makes it be effectively realized in large-scale parallel structure .

向量化中的分段处理

Segment processing in Vectorization

本文探讨了不同循环变换类型对应的多面体表示，研究了多面体表示下的向量化性能度量模型。

The thesis discusses different polyhedral representation of loop transformation , research vectorization performance metrics model under polyhedral representation .