{
int depth = matA.depth(), cn = matA.channels();
int type = CV_MAKETYPE(depth, cn);
- const int block_size = 16;
CV_Assert( type == matB.type() && (type == CV_32FC1 || type == CV_64FC1 || type == CV_32FC2 || type == CV_64FC2) );
CV_Assert( matB.type() == type && (!haveC || matC.type() == type) );
CV_Assert( sizeA.width == sizeB.height && (!haveC || sizeC == sizeD) );
- String opts = format("-D T=%s -D T1=%s -D cn=%d -D LOCAL_SIZE=%d %s %s",
- ocl::typeToStr(type), ocl::typeToStr(depth), cn, block_size,
- haveC ? "-D HAVE_C" : "",
- doubleSupport ? " -D DOUBLE_SUPPORT" : "");
-
- ocl::Kernel k("gemm", cv::ocl::core::gemm_oclsrc, opts);
- if (k.empty())
- return false;
+ int max_wg_size = (int)dev.maxWorkGroupSize();
+ int block_size = (max_wg_size / (32*cn) < 32) ? (max_wg_size / (16*cn) < 16) ? (max_wg_size / (8*cn) < 8) ? 1 : 8 : 16 : 32;
matD.create(sizeD, type);
else
D.setTo(Scalar::all(0));
+ int vectorWidths[] = { 4, 4, 2, 2, 1, 4, cn, -1 };
+
+ int kercn = ocl::checkOptimalVectorWidth(vectorWidths, B, D);
+
+ String opts = format("-D T=%s -D T1=%s -D WT=%s -D cn=%d -D kercn=%d -D LOCAL_SIZE=%d %s %s %s",
+ ocl::typeToStr(type), ocl::typeToStr(depth), ocl::typeToStr(CV_MAKETYPE(depth, kercn)),
+ cn, kercn, block_size,
+ (sizeA.width % block_size !=0) ? "-D NO_MULT" : "",
+ haveC ? "-D HAVE_C" : "",
+ doubleSupport ? " -D DOUBLE_SUPPORT" : "");
+
+ ocl::Kernel k("gemm", cv::ocl::core::gemm_oclsrc, opts);
+ if (k.empty())
+ return false;
+
if (depth == CV_64F)
k.args(ocl::KernelArg::ReadOnlyNoSize(A),
- ocl::KernelArg::ReadOnlyNoSize(B),
- ocl::KernelArg::ReadWrite(D),
+ ocl::KernelArg::ReadOnlyNoSize(B, cn, kercn),
+ ocl::KernelArg::ReadWrite(D, cn, kercn),
sizeA.width, alpha, beta);
else
k.args(ocl::KernelArg::ReadOnlyNoSize(A),
- ocl::KernelArg::ReadOnlyNoSize(B),
- ocl::KernelArg::ReadWrite(D),
+ ocl::KernelArg::ReadOnlyNoSize(B, cn, kercn),
+ ocl::KernelArg::ReadWrite(D, cn, kercn),
sizeA.width, (float)alpha, (float)beta);
- size_t globalsize[2] = { sizeD.width, sizeD.height};
+ size_t globalsize[2] = { sizeD.width * cn / kercn, sizeD.height};
size_t localsize[2] = { block_size, block_size};
- return k.run(2, globalsize, localsize, false);
+ return k.run(2, globalsize, block_size!=1 ? localsize : NULL, false);
}
-
#endif
-
}
void cv::gemm( InputArray matA, InputArray matB, double alpha,
#endif
#endif
-#define TSIZE (int)sizeof(T)
+#define TSIZE (int)sizeof(T)
+#define WTSIZE (int)sizeof(WT)
#define IND_A mad24(y, A_step, A_offset)
-#define STEP_A 1
-
-#define IND_B mad24(x, TSIZE, B_offset)
-#define STEP_B B_step / TSIZE
+#define IND_B mad24(x, WTSIZE, B_offset)
+#define STEP_B B_step / WTSIZE
#if cn==2
+#if kercn==2
+#define MUL(i, a, b)\
+ {\
+ sum.x += fma(a.x, b.x, - a.y * b.y);\
+ sum.y += fma(a.x, b.y, a.y * b.x);\
+ }
+#else
#define MUL(i, a, b)\
{\
sum.x += fma(a.x, b.x, - a.y * b.y);\
sum.y += fma(a.x, b.y, a.y * b.x);\
+ sum.z += fma(a.x, b.z, - a.y * b.w);\
+ sum.w += fma(a.x, b.w, a.y * b.z);\
}
+#endif
#else
#define MUL(i, a, b) sum = fma(a, b, sum);
#endif
int lidy = get_local_id(1);
__global const T* A = (__global const T*)(A_ptr + IND_A);
- __global const T* B = (__global const T*)(B_ptr + IND_B);
+ __global const WT* B = (__global const WT*)(B_ptr + IND_B);
- T sum = (T)(0);
- __local T a_local[LOCAL_SIZE*LOCAL_SIZE];
- __local T b_local[LOCAL_SIZE*LOCAL_SIZE];
+ WT sum = (WT)(0);
- for (int p = 0; p < (n+LOCAL_SIZE-1)/LOCAL_SIZE; ++p)
+#if LOCAL_SIZE == 1
+
+ if (x < D_cols && y < D_rows)
{
- a_local[mad24(lidy, LOCAL_SIZE, lidx)] = A[mad24(p, LOCAL_SIZE, lidx)];
- b_local[mad24(lidy, LOCAL_SIZE, lidx)] = B[mad24(p, LOCAL_SIZE, lidy)*STEP_B];
+ for (int i = 0; i < n; ++i)
+ MUL(i, A[i], B[i*STEP_B]);
+#else
+
+ __local T a_local[LOCAL_SIZE*LOCAL_SIZE];
+ __local WT b_local[LOCAL_SIZE*LOCAL_SIZE];
+
+ int reps;
+#if NO_MULT
+ reps = (n + LOCAL_SIZE-1)/LOCAL_SIZE;
+#else
+ reps = n/LOCAL_SIZE;
+#endif
+
+ for (int p = 0; p < reps; ++p)
+ {
+ if (p * LOCAL_SIZE + lidx < n && y < D_rows)
+ a_local[mad24(lidy, LOCAL_SIZE, lidx)] = A[mad24(p, LOCAL_SIZE, lidx)];
+ if (p * LOCAL_SIZE + lidy < n && x < D_cols)
+ b_local[mad24(lidy, LOCAL_SIZE, lidx)] = B[mad24(p, LOCAL_SIZE, lidy)*STEP_B];
barrier(CLK_LOCAL_MEM_FENCE);
if (x < D_cols && y < D_rows)
{
- for (int i = 0; i < LOCAL_SIZE && p * LOCAL_SIZE + i < n; ++i)
+ for (int i = 0; i < LOCAL_SIZE
+#if NO_MULT
+ && p * LOCAL_SIZE + i < n
+#endif
+ ; ++i)
MUL(i, a_local[mad24(lidy, LOCAL_SIZE, i)], b_local[mad24(i, LOCAL_SIZE, lidx)]);
}
if (x < D_cols && y < D_rows)
{
- __global T* D = (__global T*)(D_ptr + mad24(y, D_step, mad24(x, TSIZE, D_offset)));
+#endif
+ __global WT* D = (__global WT*)(D_ptr + mad24(y, D_step, mad24(x, WTSIZE, D_offset)));
#if HAVE_C
D[0] = mad(alpha, sum, D[0]*beta);
#else
D[0] = alpha * sum;
#endif
}
-}
+}
\ No newline at end of file