实现定义为的错误函数时要考虑的最佳实践是什么
使用 OpenCL 内核？
A、B 和 C 是 3D 浮点数组，\delta 是 Kronecker delta。
(N, M) = (2, 7) 或 (N, M) = (3, 23) 的典型值。
天真的实现（如下所示）比 CPU 版本慢几个数量级。
谢谢，
T。
__kernel void cl_bilinear_alg(
__global float * A,
__global float * B,
__global float * C,
__global const int M,
__global const int N,
__global float * R)
{
int index = get_global_id(0);
int N2 = N * N;
int mat_offset = index * N2 * M;
float s1, s2, err = 0.0f;
for (int i = 0; i < N; ++i)
{
for (int j = 0; j < N; ++j)
{
for (int k = 0; k < N; ++k)
{
for (int l = 0; l < N; ++l)
{
for (int m = 0; m < N; ++m)
{
for (int n = 0; n < N; ++n)
{
s1 = (n == i) * (j == k) * (l == m);
s2 = 0;
for (int r = 0; r < M; ++r)
{
s2 += A[mat_offset + r * N2 + i * N + j] *
B[mat_offset + r * N2 + k * N + l] *
C[mat_offset + r * N2 + m * N + n];
}
err += (s2 - s1) * (s2 - s1);
}
}
}
}
}
}
R[index] = err;
}
更新
主要目标是 Geforce GTX 570，但未来可能会改变。
更新2
在对代码进行矢量化、将位移动到本地内存、展开一些循环并将预先计算的 Kronecker 乘积显式传递给内核之后，代码如下所示：
__kernel void cl_bilinear_alg(__global const float * A,
__global const float * B,
__global const float * C,
__global const int N,
__global const int M,
__global const float * kron,
__global float * R)
{
__private int index = get_global_id(0);
__private int cM = ceil(M / 4.0f);
__private int N2 = N*N;
__private int N4 = N2*N2;
__private int mat_offset = index * N2 * M;
__private float s1, s2, err = 0;
__private float4 vzero = (float4) (0.0f, 0.0f, 0.0f, 0.0f);
__local float4 va[54], vb[54], vc[54];
for (int ij = 0, k = 0; ij < N2; ++ij)
{
int r = 0;
for (; r < M / 4; r += 4, ++k)
{
int idx0 = mat_offset + N2 * r + ij;
int idx1 = mat_offset + N2 * (r + 1) + ij;
int idx2 = mat_offset + N2 * (r + 2) + ij;
int idx3 = mat_offset + N2 * (r + 3) + ij;
va[k] = (float4) (A[idx0], A[idx1], A[idx2], A[idx3]);
vb[k] = (float4) (B[idx0], B[idx1], B[idx2], B[idx3]);
vc[k] = (float4) (C[idx0], C[idx1], C[idx2], C[idx3]);
}
if (M % 4)
{
float buffa[4] = {0}, buffb[4] = {0}, buffc[4] = {0};
for (; r < M; ++r)
{
int idx = mat_offset + N2 * r + ij;
buffa[r % 4] = A[idx];
buffb[r % 4] = B[idx];
buffc[r % 4] = C[idx];
}
va[k] = vload4(0, buffa);
vb[k] = vload4(0, buffb);
vc[k++] = vload4(0, buffc);
}
}
for (int ij = 0; ij < N2; ++ij)
{
for (int kl = 0; kl < N2; ++kl)
{
for (int mn = 0; mn < N2; ++mn)
{
s1 = kron[ij * N4 + kl * N2 + mn];
s2 = 0;
for (int r = 0; r < cM; ++r)
s2 += dot(va[cM * ij + r], mad(vb[cM * kl + r], vc[cM * mn + r], vzero));
//the most expensive line
err += (s2 - s1) * (s2 - s1);
}
}
}
R[index] = err;
}
通过应用这些更改，观察到与幼稚实现相比，速度提高了 4 倍。此外，据透露，最昂贵的线路是错误更新，即
err += (s2 - s1) * (s2 - s1);
有什么建议么？