我一直在努力向量化某个特定的应用程序,现在我已经尝试了一切。从自动矢量化到手动编码的SSE内部函数。但不知何故,我无法在基于模板的应用程序上获得加速。无法检测为什么下面的代码片段不是矢量化的
以下是我使用SSE intrinsics矢量化的当前代码片段。当我使用-vec-报告3把它编译(英特尔ICC)我经常得到这样的信息:
注:循环不矢量:语句不能量化。
#pragma ivdep
for (i = STENCIL; i < z - STENCIL; i+=4)
{
it = it2 + i;
__m128 tmp2i = _mm_mul_ps(_mm_add_ps(_mm_load_ps(&p2[i+j*it_j-it_j4+k*it_k]),_mm_load_ps(&p2[i+j*it_j+it_j4+k*it_k])),X4_i); //loop was not vectorized: statement cannot be vectorized
__m128 tmp3 = _mm_mul_ps(_mm_add_ps(_mm_load_ps(&p2[i+j*it_j-it_j3+k*it_k]),_mm_load_ps(&p2[i+j*it_j+it_j3+k*it_k])),X3_i);
__m128 tmp4 = _mm_mul_ps(_mm_add_ps(_mm_load_ps(&p2[i+j*it_j-it_j2+k*it_k]),_mm_load_ps(&p2[i+j*it_j+it_j2+k*it_k])),X2_i);
__m128 tmp5 = _mm_mul_ps(_mm_add_ps(_mm_load_ps(&p2[i+j*it_j-it_j +k*it_k]),_mm_load_ps(&p2[i+j*it_j+it_j +k*it_k])),X1_i);
__m128 tmp6 = _mm_add_ps(_mm_add_ps(_mm_add_ps(tmp2i,tmp3),_mm_add_ps(tmp4,tmp5)), _mm_mul_ps(_mm_load_ps(&p2[it]),C00_i));
_mm_store_ps(&tmp2[i],tmp6);
}
我这么想的关键?由于该消息没有详细说明为什么它不能被矢量化,所以我发现很难确定瓶颈。
更新: 在仔细考虑了这些建议之后,我按以下方式调整了代码。我认为最好将其进一步分解,以确定实际导致向量依赖性的语句。
//#pragma ivdep
for (i = STENCIL; i < z - STENCIL; i+=4)
{
it = it2 + i;
__m128 center = _mm_mul_ps(_mm_load_ps(&p2[it]),C00_i);
u_j4 = _mm_load_ps(&p2[i+j*it_j-it_j4+k*it_k]); //Line 180
u_j3 = _mm_load_ps(&p2[i+j*it_j-it_j3+k*it_k]);
u_j2 = _mm_load_ps(&p2[i+j*it_j-it_j2+k*it_k]);
u_j1 = _mm_load_ps(&p2[i+j*it_j-it_j +k*it_k]);
u_j8 = _mm_load_ps(&p2[i+j*it_j+it_j4+k*it_k]);
u_j7 = _mm_load_ps(&p2[i+j*it_j+it_j3+k*it_k]);
u_j6 = _mm_load_ps(&p2[i+j*it_j+it_j2+k*it_k]);
u_j5 = _mm_load_ps(&p2[i+j*it_j+it_j +k*it_k]);
__m128 tmp2i = _mm_mul_ps(_mm_add_ps(u_j4,u_j8),X4_i);
__m128 tmp3 = _mm_mul_ps(_mm_add_ps(u_j3,u_j7),X3_i);
__m128 tmp4 = _mm_mul_ps(_mm_add_ps(u_j2,u_j6),X2_i);
__m128 tmp5 = _mm_mul_ps(_mm_add_ps(u_j1,u_j5),X1_i);
__m128 tmp6 = _mm_add_ps(_mm_add_ps(tmp2i,tmp3),_mm_add_ps(tmp4,tmp5));
__m128 tmp7 = _mm_add_ps(tmp6,center);
_mm_store_ps(&tmp2[i],tmp7); //Line 196
}
当我编译(ICC),而不#pragma ivdep
我得到以下信息上面的代码:
remark: loop was not vectorized: existence of vector dependence.
vector dependence: assumed FLOW dependence between tmp2 line 196 and tmp2 line 196.
vector dependence: assumed ANTI dependence between tmp2 line 196 and tmp2 line 196.
当我编译(ICC)它与#pragma ivdep
,得到以下信息:
remark: loop was not vectorized: unsupported data type. //Line 180
为什么第196行有一个依赖关系?我如何消除建议的矢量依赖性?
通过预计算最终值和循环次数来简化'for'构造。 – 2012-07-16 19:38:58
无法对其进行矢量化,因为您已经对其进行了矢量化。你的计算/内存访问比率太低,你没有得到任何加速。 – Mysticial 2012-07-16 19:57:06
这不是我第一次想到的对齐方式(Mysticial纠正了我),但绝对值得从简化数组偏移表达式开始。 – 2012-07-16 20:10:50