start to add support for loading two K tiles at once

samples/99_matrixexperiments/matrix_helpers.cl

@@ -216,8 +216,30 @@ int8 load_a_rowmajor_d16_m8_k16_sg8(global ushort* A, int rowStart, int colStart
     return ret;
 }
 
+// M rows x K columns x V tiles (in the K dimension)
+// This is the SIMD8 version, where each work-item loads two values.
+// The first tile is returned the first components of the return value, the the next tile, etc.
+int16 load_a_rowmajor_d16_m8_k16v2_sg8(global ushort* A, int rowStart, int colStart, int stride)
+{
+    int16 ret;
+
+    global uint* A_ui = (global uint*)A;
+    int offset_ui = rowStart * stride / 2 + colStart / 2;
+
+    ret.s08 = intel_sub_group_block_read2(A_ui + offset_ui); offset_ui += stride / 2;
+    ret.s19 = intel_sub_group_block_read2(A_ui + offset_ui); offset_ui += stride / 2;
+    ret.s2a = intel_sub_group_block_read2(A_ui + offset_ui); offset_ui += stride / 2;
+    ret.s3b = intel_sub_group_block_read2(A_ui + offset_ui); offset_ui += stride / 2;
+    ret.s4c = intel_sub_group_block_read2(A_ui + offset_ui); offset_ui += stride / 2;
+    ret.s5d = intel_sub_group_block_read2(A_ui + offset_ui); offset_ui += stride / 2;
+    ret.s6e = intel_sub_group_block_read2(A_ui + offset_ui); offset_ui += stride / 2;
+    ret.s7f = intel_sub_group_block_read2(A_ui + offset_ui); offset_ui += stride / 2;
+
+    return ret;
+}
+
 // M rows x K columns
-// This is the SIMD16 version, where each work-item loads one values.
+// This is the SIMD16 version, where each work-item loads one value.
 short load_a_rowmajor_d16_m1_k16_sg16(global ushort* A, int rowStart, int colStart, int stride)
 {
     ushort ret;
@@ -229,7 +251,7 @@ short load_a_rowmajor_d16_m1_k16_sg16(global ushort* A, int rowStart, int colSta
 }
 
 // M rows x K columns
-// This is the SIMD16 version, where each work-item loads one values.
+// This is the SIMD16 version, where each work-item loads one value.
 short2 load_a_rowmajor_d16_m2_k16_sg16(global ushort* A, int rowStart, int colStart, int stride)
 {
     ushort2 ret;
@@ -242,7 +264,7 @@ short2 load_a_rowmajor_d16_m2_k16_sg16(global ushort* A, int rowStart, int colSt
 }
 
 // M rows x K columns
-// This is the SIMD16 version, where each work-item loads one values.
+// This is the SIMD16 version, where each work-item loads one value.
 short4 load_a_rowmajor_d16_m4_k16_sg16(global ushort* A, int rowStart, int colStart, int stride)
 {
     ushort4 ret;
@@ -257,7 +279,7 @@ short4 load_a_rowmajor_d16_m4_k16_sg16(global ushort* A, int rowStart, int colSt
 }
 
 // M rows x K columns
-// This is the SIMD16 version, where each work-item loads one values.
+// This is the SIMD16 version, where each work-item loads one value.
 short8 load_a_rowmajor_d16_m8_k16_sg16(global ushort* A, int rowStart, int colStart, int stride)
 {
     ushort8 ret;
@@ -275,6 +297,26 @@ short8 load_a_rowmajor_d16_m8_k16_sg16(global ushort* A, int rowStart, int colSt
     return as_short8(ret);
 }
 
+// M rows x K columns x V tiles (in the K dimension)
+// This is the SIMD16 version, where each work-item loads one value.
+// The first tile is returned the first components of the return value, the the next tile, etc.
+short16 load_a_rowmajor_d16_m8_k16v2_sg16(global ushort* A, int rowStart, int colStart, int stride)
+{
+    short16 ret;
+
+    int offset = rowStart * stride + colStart;
+    ret.s08 = intel_sub_group_block_read_us2(A + offset); offset += stride / 2;
+    ret.s19 = intel_sub_group_block_read_us2(A + offset); offset += stride / 2;
+    ret.s2a = intel_sub_group_block_read_us2(A + offset); offset += stride / 2;
+    ret.s3b = intel_sub_group_block_read_us2(A + offset); offset += stride / 2;
+    ret.s4c = intel_sub_group_block_read_us2(A + offset); offset += stride / 2;
+    ret.s5d = intel_sub_group_block_read_us2(A + offset); offset += stride / 2;
+    ret.s6e = intel_sub_group_block_read_us2(A + offset); offset += stride / 2;
+    ret.s7f = intel_sub_group_block_read_us2(A + offset); offset += stride / 2;
+
+    return ret;
+}
+
 // K rows x N columns:
 // Each work-item loads K values and converts to VNNI.
 // Stride is in units of elements.