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archibate
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Jan 26, 2022
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| template <class T> | ||
| void saxpy(T a, std::vector<T> &x, std::vector<T> const &y) { | ||
| void saxpy(T a, std::vector<T> __restrict &x, std::vector<T> const __restrict &y) { |
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看第四课，这个没有用哦！需要取出 x.data() 存到一个 __restrict 指针才行。
| res.reserve(n*3); | ||
| tbb::parallel_for(tbb::blocked_range<size_t>(0, n), | ||
| [&](tbb::blocked_range<size_t> r) { | ||
| static thread_local std::vector<T> local; |
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CPU: i7-6500U 2C4T(2 cores, 4 threads)
使用TBB完成循环的并行（中间也实验了下OpenMP）
saxpy部分试图使用手写SIMD指令加速，但没有什么效果，应该是编译器优化自动SIMD了吧？
输出结果如下：
原版
fill: 1.61105s
fill: 1.56055s
saxpy: 0.0412753s
sqrtdot: 0.104043s
5165.4
minvalue: 0.101617s
-1.11803
magicfilter: 0.51515s
55924034
scanner: 0.101111s
5.28566e+07
TBB后
fill: 0.6906s
fill: 0.753506s
saxpy: 0.040185s
sqrtdot: 0.024997s
5792.62
minvalue: 0.012356s
-1.11803
magicfilter: 0.256035s
55924034
scanner: 0.075566s
6.18781e+07