推荐一个超牛的吉他手: Sungha Jung (郑河成郑成河)
这是他的官网: http://www.sunghajung.com/
视频多数是呦土鳖上的,这是他翻的Depappepe的Fake,Depappepe组合的木吉他相当给力
Youku上也有,Taylor Swift的You Belong With Me
推荐一个超牛的吉他手: Sungha Jung (郑河成郑成河)
这是他的官网: http://www.sunghajung.com/
视频多数是呦土鳖上的,这是他翻的Depappepe的Fake,Depappepe组合的木吉他相当给力
Youku上也有,Taylor Swift的You Belong With Me
缺乏常识的人总是容易学到新东西…于是今天又知道一个节日。
今天,也就是五月的最后一个周一,是Memorial Day,wiki上译作亡兵纪念日,是为了悼念在战争中阵亡的美国官兵而设立的一个节日。下午从实验室出来也没有看到什么悼念的活动。倒是因为多数人不用上班,草坪上满是躺着晒太阳的男女老少。也有人在河边钓鱼,和往常一样很多人在跑步。
上周看到的一个游行就是和这个节日有关的,挺有意思。
If you are writing something involving the math between vectors in C/C++, you may want to check out Vlfeat (http://vlfeat.org).
It is designed to be a library for Computer Vision related stuff, but it also bring you a wrapper for SSE2 acceleration for vector computation.
Say your original code for the calculation of vectors product looks like this:
float productOfVectors(const float *vecA, const float *vecB, const int dimension) {
float value = 0.0f;
for (int i = 0; i < dimension; i++)
{
value += (vecA[i] * vecB[i]);
}
return value;
}
It can save you time significantly by adding vlfeat to your project and replace it with this:
float productOfVectors(const float *vecA, const float *vecB, const int dimension) {
float value = 0.0f;
vl_eval_vector_comparison_on_all_pairs_f(&value, dimension, vecA, 1, vecB, 1, vl_get_vector_comparison_function_f(VlKernelL2));
return value;
}
It's pretty easy but it really works. It takes use of the SSE2 instructions provided by your CPU which result in an non-trivial acceleration when you are doing large scale computation.
You can find more supported forms of calculation here, thanks for the developer's good job.