C++指南：系统独立的SSE SIMD实战

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本文档是一份实践指南，专门针对操作系统独立的C++中的Streaming SIMD Extensions (SSE)技术。首次发布于2009年9月22日，它旨在帮助开发者理解和利用SSE进行高效的并行计算，尤其在浮点运算加速方面，即使对于初学者也提供了一定的入门指导。 1.0 引言随着现代个人计算机处理器的性能提升，SSE指令集使得单精度浮点运算速度提高了4倍，这对图形处理、科学计算等领域具有重大意义。然而，学习曲线陡峭且关于SSE的文档资源相对匮乏。大部分资源集中在指令列表和简短教程上，缺乏对SSE原理和设计策略的深入讨论。英特尔的优化参考手册是个例外，但其内容较为底层。 2.0 SIMD概述 SIMD（Single Instruction Multiple Data，单指令多数据）是一种并行计算架构，允许处理器同时处理多个数据元素，通过单个操作实现并行处理。C++与SSE结合后，可以显著提升代码的性能，特别是在处理大量数据时。 3.0 SSE的有效使用指南详细讲解如何有效利用SSE，包括选择合适的运算指令、数据对齐和内存访问优化，以及如何编写和测试SSE兼容的代码。作者强调了在设计时考虑数据宽度和负载因子的重要性，以最大限度地发挥SIMD的优势。 4.0 SSE数据结构这部分介绍如何设计和使用适合SSE的数据结构，如数组、结构体等，以便于数据并行操作。可能涉及的数据类型和内存布局技巧也是关键内容。 5.0 位掩码操作位掩码是SSE编程中的一个重要工具，用于控制和操作特定的内存元素。文章会介绍如何使用位掩码执行位操作，提高代码的可读性和效率。 6.0 C++ SSE头文件指南会列出必要的C++头文件和包含指令的方法，确保编译器支持并正确地调用SSE功能。此外，还会解释如何处理不同平台之间的兼容性问题。 7.0 算法示例文章提供了四个实用算法示例： - 1.向量归一化：演示如何使用SSE加速向量长度计算。 - 2. N粒子动态：展示如何在物理模拟中利用SSE并行处理多个粒子的运动。 - 3. 折射光线与球体相交：展示如何通过SSE加速碰撞检测。 - 4. 锥体与四边形相交：进一步扩展到更复杂的几何形状交集判断。 8.0 结论结论部分总结了本指南的主要内容和学习SSE的关键点，以及如何将所学应用到实际项目中。同时，也指出未来可能的研究方向和SSE技术的演变。 9. 参考文献文章引用了作者在撰写过程中参考的相关文献和资料，为读者提供了进一步学习的途径。通过阅读这份指南，读者不仅能够掌握SSE的基础知识，还能学会如何将其融入到C++程序中，以提升代码的性能和效率。

that depending on the task the other uses memory cache more efficiently.

This block of four three dimensional vectors will be called mat4x3 data type in the code. To see its usefulness we will normalize these

four vectors in it. To achieve that first 3 multiplications followed by 3 additions are needed vertically as follows:

Continuing from that we can execute a special SSE square root instruction to the result and multiple each three of the original

components with its reciprocal to get the final result (also mat4x3, of course):

This normalization can be seen in the first code example.

5.0 Mask operations

With width four SIMD at least four bits are needed to represent a mask:

SSE uses the same 128-bit type for representing masks returned by floating point comparisons. Single float's byte sequence 0x00000000

in hexadecimals represents false and 0xFFFFFFFF represents true. SSE has comparison instructions for all the basic arithmetic

comparisons like greater or equal than.

Mask are then produced by using standard C++ comparison operators between two vec4 types:

or listing all the elements:

The resulting mask can then be used to conditionally only write to parts of vec4 or deciding a path based on whether all the bits are set,

none of them are set, or some of them are set.

Examples of different kinds of control logic turned into mask operations can be found in the algorithm examples.

6.0 C++ SSE header

In February 2009 Krzysztof Jakubowski posted a full implementation of C++ wrapping over the 32-bit floating point and the 32-bit

integer SSE C intrinsics on a ray tracing Internet forum called ompf. It is called veclib and it s licensed with very permissive zlib license.

From my experiments with that implementation this guide was born.

Generally, when writing vector code in vector notation in C++, one can in my experience do so without any overhead to worry about by

using expression templates. Basically expression templates help avoid unnecessary temporaries over naive C++ operator overloaded

implementations. An implementation of this is a BSD-type licensed piece of code called cvalarray.

What I advocate is to use these two implementations together to get, as far as I know, the fastest and neatest freely available C++

implementation of basic 3D vectors and SSE types. Of course, for some specific higher level tasks there are better options, like Eigen for

linear algebra. To get better notation compared to what veclib uses I took example of GLSL specifications to come up with this for

writing SSE code:

C++ vector types with SSE for single precision (32-bit)

vec2,vec3,vec4 floating point vector

vec2b,vec3b,vec4b mask type for floating point vector

ivec2,ivec3,ivec4 signed integer vector

ivec2b,ivec3b,ivec4b mask type for signed integer vector

mat4x2,mat4x3,mat4x4 4 column floating point matrix (SSE)

Also any of these can be prefixed with "p" for double precision. And this is then a full header file, that implements part of these types:

#include "cvalarray.hpp"

#include "veclib.h"

typedef veclib::f32x4 vec4;

typedef veclib::f32x4b vec4b;

typedef veclib::i32x4 ivec4;

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