COMPMID-3925: Dispatch CLGEMM with no padding y requirement

- Add has_pad_y flag in GEMMKernelInfo
- Skip reinterpret as 3D in CLGEMMMatrixMultiplyReshapedOnlyRHSKernel if
  has_pad_y = false
- Add test to validate CLGEMMMatrixMultiplyReshapedOnlyRHSkernel with
  had_pad_y = false/true
- Configure two variants of CLGEMMMatrixMultiplyReshapedOnlyRHSKernel to
  run with has_pad_y = false/true in CLGEMM
- Check if the lhs/dst tensors have pad y. If not, run
  CLGEMMMatrixMultiplyReshapedOnlyRHSKernel without padding requirement

Change-Id: I68bb43389789736d676b899ac7c77fd9138babaf
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4248
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

11 files changed, 150 insertions, 177 deletions

diff --git a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.h b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.h
index fc21f2a0f6..eab7fd219e 100644
--- a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.h
@@ -162,6 +162,7 @@ private:
     bool             _add_bias;
     bool             _broadcast_bias;
     bool             _export_to_cl_image;
+    bool             _has_pad_y;
 };
 } // namespace arm_compute
 #endif /*ARM_COMPUTE_CLGEMMMATRIXMULTIPLYRESHAPEDONLYRHSKERNEL_H*/
diff --git a/arm_compute/core/KernelDescriptors.h b/arm_compute/core/KernelDescriptors.h
index 1ee1686fb1..ea46bfa5a6 100644
--- a/arm_compute/core/KernelDescriptors.h
+++ b/arm_compute/core/KernelDescriptors.h
@@ -64,6 +64,7 @@ struct GEMMKernelInfo
         bool                ireinterpret_input_as_3d,
         bool                ibroadcast_bias,
         bool                ifp_mixed_precision,
+        bool                ihas_pad_y,
         ActivationLayerInfo iactivation_info,
         int                 inmult_transpose1xW_width,
         int                 imult_interleave4x4_height,
@@ -72,7 +73,7 @@ struct GEMMKernelInfo
         int32_t             ina_offset,
         int32_t             inb_offset)
         : m(im), n(in), k(ik), depth_output_gemm3d(idepth_output_gemm3d), reinterpret_input_as_3d(ireinterpret_input_as_3d), broadcast_bias(ibroadcast_bias), fp_mixed_precision(ifp_mixed_precision),
-          activation_info(iactivation_info), mult_transpose1xW_width(inmult_transpose1xW_width), mult_interleave4x4_height(imult_interleave4x4_height), lhs_info(ilhs_info), rhs_info(irhs_info),
+          has_pad_y(ihas_pad_y), activation_info(iactivation_info), mult_transpose1xW_width(inmult_transpose1xW_width), mult_interleave4x4_height(imult_interleave4x4_height), lhs_info(ilhs_info), rhs_info(irhs_info),
           a_offset(ina_offset), b_offset(inb_offset)
     {
     }
@@ -84,6 +85,7 @@ struct GEMMKernelInfo
     bool                    reinterpret_input_as_3d{ false }; /**< Flag used to reinterpret the input as 3D */
     bool                    broadcast_bias{ false };          /**< Flag used to broadcast the bias addition */
     bool                    fp_mixed_precision{ false };      /**< Flag used to indicate wider accumulators (32 bit instead of 16 for FP16). */
+    bool                    has_pad_y{ false };               /**< Flag used to indicate if the input/output tensors have internal pad on the y direction */
     ActivationLayerInfo     activation_info{};                /**< Activation function to perform after the matrix multiplication */
     int                     mult_transpose1xW_width{ 1 };     /**< Multiplication factor for the width of the 1xW transposed block */
     int                     mult_interleave4x4_height{ 1 };   /**< Multiplication factor for the height of the 4x4 interleaved block */
diff --git a/arm_compute/runtime/CL/functions/CLGEMM.h b/arm_compute/runtime/CL/functions/CLGEMM.h
index 6e9cf0e2ca..92f9736e35 100644
--- a/arm_compute/runtime/CL/functions/CLGEMM.h
+++ b/arm_compute/runtime/CL/functions/CLGEMM.h
@@ -206,11 +206,15 @@ private:
     weights_transformations::CLGEMMReshapeRHSMatrixKernelManaged _reshape_rhs_kernel_managed;
     CLGEMMMatrixMultiplyReshapedKernel                           _mm_reshaped_kernel;
     CLGEMMMatrixMultiplyReshapedOnlyRHSKernel                    _mm_reshaped_only_rhs_kernel;
+    CLGEMMMatrixMultiplyReshapedOnlyRHSKernel                    _mm_reshaped_only_rhs_fallback_kernel;
     CLTensor                                                     _tmp_a;
     CLTensor                                                     _tmp_b;
     const ICLTensor                                             *_original_b;
+    const ICLTensor                                             *_lhs;
+    ICLTensor                                                   *_dst;
     bool                                                         _reshape_b_only_on_first_run;
     bool                                                         _is_prepared;
+    bool                                                         _has_pad_y;
     CLGEMMKernelType                                             _gemm_kernel_type;
 };
 } // namespace arm_compute
diff --git a/src/core/CL/cl_kernels/gemm.cl b/src/core/CL/cl_kernels/gemm.cl
index 653aa5591c..fa93760847 100644
--- a/src/core/CL/cl_kernels/gemm.cl
+++ b/src/core/CL/cl_kernels/gemm.cl
@@ -1121,7 +1121,7 @@ __kernel void gemm_mm_reshaped_only_rhs_t(IMAGE_DECLARATION(lhs),
 
 #if defined(REINTERPRET_INPUT_AS_3D)
     // The plane (zlhs) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
-    CALCULATE_Z_OFFSET(M0, uint, zlhs, y, HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
+    CALCULATE_Z_OFFSET(M0, uint, zlhs, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
 
     // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
     // multiply lhs_stride_z by DEPTH_GEMM3D
@@ -1227,7 +1227,7 @@ __kernel void gemm_mm_reshaped_only_rhs_t(IMAGE_DECLARATION(lhs),
 #if defined(REINTERPRET_OUTPUT_AS_3D)
 
     // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
-    CALCULATE_Z_OFFSET(M0, uint, zout, y, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
+    CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
 
     // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
     // multiply dst_stride_z by DEPTH_GEMM3D
@@ -1418,7 +1418,7 @@ __kernel void gemm_mm_reshaped_only_rhs_t_texture(IMAGE_DECLARATION(lhs),
 
 #if defined(REINTERPRET_INPUT_AS_3D)
     // The plane (zlhs) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
-    CALCULATE_Z_OFFSET(M0, uint, zlhs, y, HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
+    CALCULATE_Z_OFFSET(M0, uint, zlhs, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
 
     // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
     // multiply lhs_stride_z by DEPTH_GEMM3D
@@ -1573,7 +1573,7 @@ __kernel void gemm_mm_reshaped_only_rhs_t_texture(IMAGE_DECLARATION(lhs),
 #if defined(REINTERPRET_OUTPUT_AS_3D)
 
     // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
-    CALCULATE_Z_OFFSET(M0, uint, zout, y, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
+    CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
 
     // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
     // multiply dst_stride_z by DEPTH_GEMM3D
@@ -1839,7 +1839,7 @@ __kernel void gemm_mm_reshaped_only_rhs_nt(IMAGE_DECLARATION(lhs),
 #if defined(REINTERPRET_INPUT_AS_3D)
 
     // The plane (zin) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
-    CALCULATE_Z_OFFSET(M0, uint, zin, y, HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
+    CALCULATE_Z_OFFSET(M0, uint, zin, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
 
     // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
     // multiply lhs_stride_z by DEPTH_GEMM3D
@@ -1969,7 +1969,7 @@ __kernel void gemm_mm_reshaped_only_rhs_nt(IMAGE_DECLARATION(lhs),
 
 #if defined(REINTERPRET_OUTPUT_AS_3D)
     // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
-    CALCULATE_Z_OFFSET(M0, uint, zout, y, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
+    CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
 
     // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
     // multiply dst_stride_z by DEPTH_GEMM3D
@@ -2157,7 +2157,7 @@ __kernel void gemm_mm_reshaped_only_rhs_nt_texture(IMAGE_DECLARATION(lhs),
 #if defined(REINTERPRET_INPUT_AS_3D)
 
     // The plane (zin) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
-    CALCULATE_Z_OFFSET(M0, uint, zin, y, HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
+    CALCULATE_Z_OFFSET(M0, uint, zin, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
 
     // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
     // multiply lhs_stride_z by DEPTH_GEMM3D
@@ -2278,7 +2278,7 @@ __kernel void gemm_mm_reshaped_only_rhs_nt_texture(IMAGE_DECLARATION(lhs),
 
 #if defined(REINTERPRET_OUTPUT_AS_3D)
     // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
-    CALCULATE_Z_OFFSET(M0, uint, zout, y, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
+    CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
 
     // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
     // multiply dst_stride_z by DEPTH_GEMM3D
@@ -4120,7 +4120,7 @@ __kernel void gemm_mm_native(IMAGE_DECLARATION(lhs),
 
 #if defined(REINTERPRET_INPUT_AS_3D)
     // The plane (zlhs) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
-    CALCULATE_Z_OFFSET(M0, uint, zlhs, y, HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
+    CALCULATE_Z_OFFSET(M0, uint, zlhs, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
 
     // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
     // multiply lhs_stride_z by DEPTH_GEMM3D
@@ -4232,7 +4232,7 @@ __kernel void gemm_mm_native(IMAGE_DECLARATION(lhs),
 
 #if defined(REINTERPRET_OUTPUT_AS_3D)
     // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
-    CALCULATE_Z_OFFSET(M0, uint, zout, y, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
+    CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
 
     // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
     // multiply dst_stride_z by DEPTH_GEMM3D
diff --git a/src/core/CL/cl_kernels/gemm_helpers.h b/src/core/CL/cl_kernels/gemm_helpers.h
index 2534204f2f..54d38655a4 100644
--- a/src/core/CL/cl_kernels/gemm_helpers.h
+++ b/src/core/CL/cl_kernels/gemm_helpers.h
@@ -624,49 +624,49 @@
  * @{
  */
 #define CALCULATE_Z_OFFSET_1(M0, DATA_TYPE, Z, Y, HEIGHT_GEMM3D, DEPTH_GEMM3D, CROSS_PLANE_PAD, STRIDE_Y) \
-    Z##0 = (0 + (DATA_TYPE)(Y * (DATA_TYPE)M0)) / (DATA_TYPE)HEIGHT_GEMM3D;                               \
+    Z##0 = (0 + (DATA_TYPE)(Y)) / (DATA_TYPE)HEIGHT_GEMM3D;                               \
     Z##0 = min((DATA_TYPE)(DEPTH_GEMM3D - 1), Z##0);                                                      \
     Z##0 *= (CROSS_PLANE_PAD * STRIDE_Y);
 
 #define CALCULATE_Z_OFFSET_2(M0, DATA_TYPE, Z, Y, HEIGHT_GEMM3D, DEPTH_GEMM3D, CROSS_PLANE_PAD, STRIDE_Y) \
     CALCULATE_Z_OFFSET_1(M0, DATA_TYPE, Z, Y, HEIGHT_GEMM3D, DEPTH_GEMM3D, CROSS_PLANE_PAD, STRIDE_Y)     \
-    Z##1 = (1 + (DATA_TYPE)(Y * (DATA_TYPE)M0)) / (DATA_TYPE)HEIGHT_GEMM3D;                               \
+    Z##1 = (1 + (DATA_TYPE)(Y)) / (DATA_TYPE)HEIGHT_GEMM3D;                               \
     Z##1 = min((DATA_TYPE)(DEPTH_GEMM3D - 1), Z##1);                                                      \
     Z##1 *= (CROSS_PLANE_PAD * STRIDE_Y);
 
 #define CALCULATE_Z_OFFSET_3(M0, DATA_TYPE, Z, Y, HEIGHT_GEMM3D, DEPTH_GEMM3D, CROSS_PLANE_PAD, STRIDE_Y) \
     CALCULATE_Z_OFFSET_2(M0, DATA_TYPE, Z, Y, HEIGHT_GEMM3D, DEPTH_GEMM3D, CROSS_PLANE_PAD, STRIDE_Y)     \
-    Z##2 = (2 + (DATA_TYPE)(Y * (DATA_TYPE)M0)) / (DATA_TYPE)HEIGHT_GEMM3D;                               \
+    Z##2 = (2 + (DATA_TYPE)(Y)) / (DATA_TYPE)HEIGHT_GEMM3D;                               \
     Z##2 = min((DATA_TYPE)(DEPTH_GEMM3D - 1), Z##2);                                                      \
     Z##2 *= (CROSS_PLANE_PAD * STRIDE_Y);
 
 #define CALCULATE_Z_OFFSET_4(M0, DATA_TYPE, Z, Y, HEIGHT_GEMM3D, DEPTH_GEMM3D, CROSS_PLANE_PAD, STRIDE_Y) \
     CALCULATE_Z_OFFSET_3(M0, DATA_TYPE, Z, Y, HEIGHT_GEMM3D, DEPTH_GEMM3D, CROSS_PLANE_PAD, STRIDE_Y)     \
-    Z##3 = (3 + (DATA_TYPE)(Y * (DATA_TYPE)M0)) / (DATA_TYPE)HEIGHT_GEMM3D;                               \
+    Z##3 = (3 + (DATA_TYPE)(Y)) / (DATA_TYPE)HEIGHT_GEMM3D;                               \
     Z##3 = min((DATA_TYPE)(DEPTH_GEMM3D - 1), Z##3);                                                      \
     Z##3 *= (CROSS_PLANE_PAD * STRIDE_Y);
 
 #define CALCULATE_Z_OFFSET_5(M0, DATA_TYPE, Z, Y, HEIGHT_GEMM3D, DEPTH_GEMM3D, CROSS_PLANE_PAD, STRIDE_Y) \
     CALCULATE_Z_OFFSET_4(M0, DATA_TYPE, Z, Y, HEIGHT_GEMM3D, DEPTH_GEMM3D, CROSS_PLANE_PAD, STRIDE_Y)     \
-    Z##4 = (4 + (DATA_TYPE)(Y * (DATA_TYPE)M0)) / (DATA_TYPE)HEIGHT_GEMM3D;                               \
+    Z##4 = (4 + (DATA_TYPE)(Y)) / (DATA_TYPE)HEIGHT_GEMM3D;                               \
     Z##4 = min((DATA_TYPE)(DEPTH_GEMM3D - 1), Z##4);                                                      \
     Z##4 *= (CROSS_PLANE_PAD * STRIDE_Y);
 
 #define CALCULATE_Z_OFFSET_6(M0, DATA_TYPE, Z, Y, HEIGHT_GEMM3D, DEPTH_GEMM3D, CROSS_PLANE_PAD, STRIDE_Y) \
     CALCULATE_Z_OFFSET_5(M0, DATA_TYPE, Z, Y, HEIGHT_GEMM3D, DEPTH_GEMM3D, CROSS_PLANE_PAD, STRIDE_Y)     \
-    Z##5 = (5 + (DATA_TYPE)(Y * (DATA_TYPE)M0)) / (DATA_TYPE)HEIGHT_GEMM3D;                               \
+    Z##5 = (5 + (DATA_TYPE)(Y)) / (DATA_TYPE)HEIGHT_GEMM3D;                               \
     Z##5 = min((DATA_TYPE)(DEPTH_GEMM3D - 1), Z##5);                                                      \
     Z##5 *= (CROSS_PLANE_PAD * STRIDE_Y);
 
 #define CALCULATE_Z_OFFSET_7(M0, DATA_TYPE, Z, Y, HEIGHT_GEMM3D, DEPTH_GEMM3D, CROSS_PLANE_PAD, STRIDE_Y) \
     CALCULATE_Z_OFFSET_6(M0, DATA_TYPE, Z, Y, HEIGHT_GEMM3D, DEPTH_GEMM3D, CROSS_PLANE_PAD, STRIDE_Y)     \
-    Z##6 = (6 + (DATA_TYPE)(Y * (DATA_TYPE)M0)) / (DATA_TYPE)HEIGHT_GEMM3D;                               \
+    Z##6 = (6 + (DATA_TYPE)(Y)) / (DATA_TYPE)HEIGHT_GEMM3D;                               \
     Z##6 = min((DATA_TYPE)(DEPTH_GEMM3D - 1), Z##6);                                                      \
     Z##6 *= (CROSS_PLANE_PAD * STRIDE_Y);
 
 #define CALCULATE_Z_OFFSET_8(M0, DATA_TYPE, Z, Y, HEIGHT_GEMM3D, DEPTH_GEMM3D, CROSS_PLANE_PAD, STRIDE_Y) \
     CALCULATE_Z_OFFSET_7(M0, DATA_TYPE, Z, Y, HEIGHT_GEMM3D, DEPTH_GEMM3D, CROSS_PLANE_PAD, STRIDE_Y)     \
-    Z##7 = (7 + (DATA_TYPE)(Y * (DATA_TYPE)M0)) / (DATA_TYPE)HEIGHT_GEMM3D;                               \
+    Z##7 = (7 + (DATA_TYPE)(Y)) / (DATA_TYPE)HEIGHT_GEMM3D;                               \
     Z##7 = min((DATA_TYPE)(DEPTH_GEMM3D - 1), Z##7);                                                      \
     Z##7 *= (CROSS_PLANE_PAD * STRIDE_Y);
 
diff --git a/src/core/CL/cl_kernels/gemmlowp.cl b/src/core/CL/cl_kernels/gemmlowp.cl
index 950faeca0b..4a05635669 100644
--- a/src/core/CL/cl_kernels/gemmlowp.cl
+++ b/src/core/CL/cl_kernels/gemmlowp.cl
@@ -433,7 +433,7 @@ __kernel void gemmlowp_mm_reshaped_lhs_nt_rhs_t(IMAGE_DECLARATION(lhs),
 
 #if defined(REINTERPRET_OUTPUT_AS_3D)
     // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
-    CALCULATE_Z_OFFSET(M0, uint, zout, y, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
+    CALCULATE_Z_OFFSET(M0, uint, zout, y * M0, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
 
     // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
     // multiply dst_stride_z by DEPTH_GEMM3D
@@ -567,7 +567,7 @@ __kernel void gemmlowp_mm_reshaped_only_rhs_t(IMAGE_DECLARATION(lhs),
 
 #if defined(REINTERPRET_INPUT_AS_3D)
     // The plane (zlhs) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
-    CALCULATE_Z_OFFSET(M0, uint, zlhs, y, HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
+    CALCULATE_Z_OFFSET(M0, uint, zlhs, y * M0, HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
 
     // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
     // multiply lhs_stride_z by DEPTH_GEMM3D
@@ -604,7 +604,7 @@ __kernel void gemmlowp_mm_reshaped_only_rhs_t(IMAGE_DECLARATION(lhs),
 
 #if defined(REINTERPRET_OUTPUT_AS_3D)
     // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
-    CALCULATE_Z_OFFSET(M0, uint, zout, y, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
+    CALCULATE_Z_OFFSET(M0, uint, zout, y * M0, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
 
     // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
     // multiply dst_stride_z by DEPTH_GEMM3D
@@ -781,7 +781,7 @@ __kernel void gemmlowp_mm_reshaped_only_rhs_t_fused_output_stage_fixedpoint(IMAG
 
 #if defined(REINTERPRET_INPUT_AS_3D)
     // The plane (zlhs) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
-    CALCULATE_Z_OFFSET(M0, uint, zlhs, y, HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
+    CALCULATE_Z_OFFSET(M0, uint, zlhs, y * M0, HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
 
     // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
     // multiply lhs_stride_z by DEPTH_GEMM3D
@@ -819,7 +819,7 @@ __kernel void gemmlowp_mm_reshaped_only_rhs_t_fused_output_stage_fixedpoint(IMAG
 
 #if defined(REINTERPRET_OUTPUT_AS_3D)
     // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
-    CALCULATE_Z_OFFSET(M0, uint, zout, y, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
+    CALCULATE_Z_OFFSET(M0, uint, zout, y * M0, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
 
     // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
     // multiply dst_stride_z by DEPTH_GEMM3D
@@ -1009,7 +1009,7 @@ __kernel void gemmlowp_mm_native(IMAGE_DECLARATION(lhs),
 
 #if defined(REINTERPRET_INPUT_AS_3D)
     // The plane (zlhs) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
-    CALCULATE_Z_OFFSET(M0, uint, zlhs, y, HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
+    CALCULATE_Z_OFFSET(M0, uint, zlhs, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
 
     // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
     // multiply lhs_stride_z by DEPTH_GEMM3D
@@ -1080,7 +1080,7 @@ __kernel void gemmlowp_mm_native(IMAGE_DECLARATION(lhs),
 
 #if defined(REINTERPRET_OUTPUT_AS_3D)
     // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
-    CALCULATE_Z_OFFSET(M0, uint, zout, y, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
+    CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
 
     // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
     // multiply dst_stride_z by DEPTH_GEMM3D
diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp
index 912c763ed5..68f761b9e7 100644
--- a/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp
@@ -133,7 +133,8 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input0, ITe
 
     // In case both input and output have to be reinterpreted as 3D tensors,
     // force reinterpret_input_as_3d and reinterpret_output_as_3d to be false.
-    if(reinterpret_input_as_3d == reinterpret_output_as_3d)
+    // This approach should only be used when the input/output tensors have pad on the y direction
+    if((reinterpret_input_as_3d == reinterpret_output_as_3d) && gemm_info.has_pad_y)
     {
         reinterpret_output_as_3d = false;
     }
@@ -159,16 +160,6 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input0, ITe
     win     = calculate_max_window(tmp_info, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
     win_out = calculate_max_window(*output, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
 
-    AccessWindowStatic input0_access(input0, 0, 0,
-                                     input0->dimension(0),
-                                     input0->dimension(1));
-    AccessWindowStatic input1_access(input1, 0, 0,
-                                     input1->dimension(0),
-                                     input1->dimension(1));
-    AccessWindowStatic output_access(output, 0, 0,
-                                     output->dimension(0),
-                                     output->dimension(1));
-
     if(input2 != nullptr)
     {
         const int bias_processed_per_iteration_x = num_elems_processed_per_iteration_x;
@@ -177,17 +168,9 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input0, ITe
                                          ceil_to_multiple(input2->dimension(0), bias_processed_per_iteration_x),
                                          input2->dimension(1));
 
-        window_changed = update_window_and_padding(win, input0_access, input1_access, input2_access) || // window used by the execute_window_loop
-                         update_window_and_padding(win_out, output_access);                             // window used to update the padding requirements of output tensor
-    }
-    else
-    {
-        window_changed = update_window_and_padding(win, input0_access, input1_access) || // window used by the execute_window_loop
-                         update_window_and_padding(win_out, output_access);              // window used to update the padding requirements of output tensor
+        window_changed = update_window_and_padding(win, input2_access);
     }
 
-    output_access.set_valid_region(win_out, ValidRegion(Coordinates(), output->tensor_shape()));
-
     // Collapse along the Z direction
     // This collapse needs to be here in order to tune the Z dimension of LWS
     Window             collapsed             = win;
@@ -201,7 +184,7 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input0, ITe
 
 CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::CLGEMMMatrixMultiplyReshapedOnlyRHSKernel()
     : _input0(nullptr), _input1(nullptr), _input2(nullptr), _output(nullptr), _slide_matrix_b(true), _reinterpret_input_as_3d(false), _reinterpret_output_as_3d(false), _use_dummy_work_items(false),
-      _add_bias(false), _broadcast_bias(false), _export_to_cl_image(false)
+      _add_bias(false), _broadcast_bias(false), _export_to_cl_image(false), _has_pad_y(false)
 {
 }
 
@@ -232,10 +215,13 @@ void CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::configure(const CLCompileContext
     _add_bias                 = _input2 != nullptr;
     _broadcast_bias           = gemm_info.broadcast_bias;
     _export_to_cl_image       = rhs_info.export_to_cl_image;
+    _has_pad_y                = gemm_info.has_pad_y;
+
+    auto padding_info = get_padding_info({ input0, input1, output });
 
     // In case both input and output have to be reinterpreted as 3D tensors,
     // force reinterpret_input_as_3d and reinterpret_output_as_3d to be false.
-    if(_reinterpret_input_as_3d == _reinterpret_output_as_3d)
+    if((_reinterpret_input_as_3d == _reinterpret_output_as_3d) && _has_pad_y)
     {
         _reinterpret_input_as_3d  = false;
         _reinterpret_output_as_3d = false;
@@ -257,6 +243,7 @@ void CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::configure(const CLCompileContext
     // This means that the actual m used by the kernel is given by output->info()->dimension(1) and not by gemm_info.m
     const unsigned int internal_m = _reinterpret_output_as_3d ? gemm_info.m : output->info()->dimension(1);
 
+    // These variables are used only if gemm_info.has_pad_y == true
     const unsigned int h_gemm_3d = _reinterpret_output_as_3d ? output->info()->dimension(1) : input0->info()->dimension(1);
     const unsigned int d_gemm_3d = _reinterpret_output_as_3d ? output->info()->dimension(2) : input0->info()->dimension(2);
 
@@ -274,11 +261,7 @@ void CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::configure(const CLCompileContext
     build_opts.add_option_if(!(helpers::float_ops::is_one(alpha)), "-DALPHA=" + float_to_string_with_full_precision(alpha));
     build_opts.add_option_if(_input2 != nullptr, "-DBETA=" + float_to_string_with_full_precision(beta));
     build_opts.add_option_if(helpers::float_ops::is_one(beta), "-DUNIT_BETA");
-    build_opts.add_option_if(_reinterpret_input_as_3d, "-DREINTERPRET_INPUT_AS_3D");
-    build_opts.add_option_if(_reinterpret_output_as_3d, "-DREINTERPRET_OUTPUT_AS_3D");
     build_opts.add_option_if(gemm_info.broadcast_bias, "-DBROADCAST_BIAS");
-    build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(h_gemm_3d));
-    build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DDEPTH_GEMM3D=" + support::cpp11::to_string(d_gemm_3d));
     build_opts.add_option_if(!_slide_matrix_b, "-DMATRIX_B_DEPTH=" + support::cpp11::to_string(input1->info()->dimension(2)));
     build_opts.add_option_if(rhs_info.interleave, "-DRHS_INTERLEAVE");
     build_opts.add_option_if(_use_dummy_work_items, "-DDUMMY_WORK_ITEMS");
@@ -296,6 +279,13 @@ void CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::configure(const CLCompileContext
     build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(gemm_info.activation_info.activation())));
     build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.a()));
     build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.b()));
+    if(_has_pad_y)
+    {
+        build_opts.add_option_if(_reinterpret_input_as_3d, "-DREINTERPRET_INPUT_AS_3D");
+        build_opts.add_option_if(_reinterpret_output_as_3d, "-DREINTERPRET_OUTPUT_AS_3D");
+        build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(h_gemm_3d));
+        build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DDEPTH_GEMM3D=" + support::cpp11::to_string(d_gemm_3d));
+    }
 
     std::string kernel_name("gemm_mm_reshaped_only_rhs_");
     kernel_name += rhs_info.transpose ? "t" : "nt";
@@ -307,6 +297,7 @@ void CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::configure(const CLCompileContext
     // Set config_id for enabling LWS tuning
     _config_id = kernel_name;
     _config_id += "_";
+    _config_id += (_has_pad_y ? "" : "no_pad_y_");
     _config_id += (_add_bias ? "add_bias_" : "");
     _config_id += (_broadcast_bias ? "broadcast_bias_" : "");
     _config_id += (_reinterpret_input_as_3d ? "3di_" : "");
@@ -331,6 +322,8 @@ void CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::configure(const CLCompileContext
     _config_id += support::cpp11::to_string(rhs_info.h0);
     _config_id += "_";
     _config_id += support::cpp11::to_string(rhs_info.interleave);
+
+    ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
 }
 
 Status CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float alpha, float beta,
@@ -363,15 +356,24 @@ void CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::run(const Window &window, cl::Co
         ARM_COMPUTE_ERROR_ON(_input1->info()->strides_in_bytes()[3] != 0);
     }
 
+    const size_t lhs_idx_batch_size = _reinterpret_input_as_3d && !_has_pad_y? 3u : 2u;
+    const size_t rhs_idx_batch_size = 2u;
+    const size_t bia_idx_batch_size = 2u;
+    const size_t out_idx_batch_size = _reinterpret_output_as_3d && !_has_pad_y? 3u : 2u;
+
     Window slice          = window.first_slice_window_3D();
     Window slice_matrix_b = slice;
 
     slice_matrix_b.set(Window::DimX, Window::Dimension(0, 1, 1));
     slice_matrix_b.set(Window::DimY, Window::Dimension(0, 1, 1));
 
+    // Get cross plane pads
     const unsigned int total_cross_plane_pad_lhs = _input0->info()->padding().top + _input0->info()->padding().bottom;
     const unsigned int total_cross_plane_pad_out = _output->info()->padding().top + _output->info()->padding().bottom;
 
+    // The execution should fail if we try to run with has_pad_y = false but we have padding in either the LHS or DST tensor
+    ARM_COMPUTE_ERROR_ON(!_has_pad_y && ((total_cross_plane_pad_lhs != 0) || (total_cross_plane_pad_out != 0)));
+
     cl::Image2D input1_image2d;
 
     if(_export_to_cl_image)
@@ -414,28 +416,28 @@ void CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::run(const Window &window, cl::Co
         add_2D_tensor_argument(idx, _output, slice);
 
         // LHS stride_z
-        _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input0->info()->strides_in_bytes()[2]));
+        _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input0->info()->strides_in_bytes()[lhs_idx_batch_size]));
 
         // RHS stride_z (not used if _export_to_cl_image == true)
-        _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input1->info()->strides_in_bytes()[2]));
+        _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input1->info()->strides_in_bytes()[rhs_idx_batch_size]));
 
         // Bias stride_z (if _add_bias == true)
         if(_add_bias)
         {
-            _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input2->info()->strides_in_bytes()[2]));
+            _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input2->info()->strides_in_bytes()[bia_idx_batch_size]));
         }
 
         // Output stride_z
-        _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[2]));
+        _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[out_idx_batch_size]));
 
         // Cross-plan padding (if _reinterpret_input_as_3d = true)
-        if(_reinterpret_input_as_3d)
+        if(_reinterpret_input_as_3d && _has_pad_y)
         {
             _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(total_cross_plane_pad_lhs));
         }
 
         // Cross-plan padding (if _reinterpret_output_as_3d = true)
-        if(_reinterpret_output_as_3d)
+        if(_reinterpret_output_as_3d && _has_pad_y)
         {
             _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(total_cross_plane_pad_out));
         }
diff --git a/src/runtime/CL/functions/CLGEMM.cpp b/src/runtime/CL/functions/CLGEMM.cpp
index ccae6713a6..80c5496ede 100644
--- a/src/runtime/CL/functions/CLGEMM.cpp
+++ b/src/runtime/CL/functions/CLGEMM.cpp
@@ -60,11 +60,15 @@ CLGEMM::CLGEMM(std::shared_ptr<IMemoryManager> memory_manager, IWeightsManager *
       _reshape_rhs_kernel_managed(),
       _mm_reshaped_kernel(),
       _mm_reshaped_only_rhs_kernel(),
+      _mm_reshaped_only_rhs_fallback_kernel(),
       _tmp_a(),
       _tmp_b(),
       _original_b(nullptr),
+      _lhs(nullptr),
+      _dst(nullptr),
       _reshape_b_only_on_first_run(false),
       _is_prepared(false),
+      _has_pad_y(false),
       _gemm_kernel_type(CLGEMMKernelType::NATIVE_V1)
 {
 }
@@ -295,16 +299,8 @@ void CLGEMM::configure_reshaped_only_rhs(const CLCompileContext &compile_context
     std::unique_ptr<ICLGEMMKernelConfiguration> gemm_config = CLGEMMReshapedOnlyRHSKernelConfigurationFactory::create(gpu_target);
     ARM_COMPUTE_ERROR_ON_NULLPTR(gemm_config.get());
 
-    unsigned int m_internal = m;
-    unsigned int b_internal = batch_size;
-    if(reinterpret_input_as_3d)
-    {
-        m_internal = a->info()->dimension(1);
-        b_internal = a->info()->dimension(2);
-    }
-
     // Configure lhs_info and rhs_info
-    std::tie(lhs_info, rhs_info) = gemm_config->configure(m_internal, n, k, b_internal, data_type);
+    std::tie(lhs_info, rhs_info) = gemm_config->configure(m, n, k, batch_size, data_type);
 
     ICLTensor *reshaped_rhs = &_tmp_b;
     if(_weights_manager && _weights_manager->are_weights_managed(b))
@@ -317,9 +313,18 @@ void CLGEMM::configure_reshaped_only_rhs(const CLCompileContext &compile_context
         _reshape_rhs_kernel.configure(compile_context, b, &_tmp_b, rhs_info);
     }
 
-    // Configure and tune matrix multiply kernel
+    // Configure two variants of CLGEMMMatrixMultiplyReshapedOnlyRHSKernel (has_pad_y = false/true)
+    // During the prepare stage we check the padding requirement for the lhs and dst tensors. If they do not have
+    // pad y, we dispatch CLGEMMMatrixMultiplyReshapedOnlyRHSKernel with has_pad_y = false
+
+    // Configure matrix multiply kernel with no y padding support
+    kernel_info.has_pad_y = false;
     _mm_reshaped_only_rhs_kernel.configure(compile_context, a, reshaped_rhs, c, output, alpha, beta, lhs_info, rhs_info, kernel_info);
 
+    // Configure matrix multiply kernel with y padding support
+    kernel_info.has_pad_y = true;
+    _mm_reshaped_only_rhs_fallback_kernel.configure(compile_context, a, reshaped_rhs, c, output, alpha, beta, lhs_info, rhs_info, kernel_info);
+
     if(!_reshape_b_only_on_first_run && use_mm_b)
     {
         _tmp_b.allocator()->allocate();
@@ -493,6 +498,10 @@ Status CLGEMM::validate_reshaped_only_rhs(const ITensorInfo *a, const ITensorInf
     ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMReshapeRHSMatrixKernel::validate(b, &tmp_b_info, rhs_info));
 
     // Validate matrix multiply
+    kernel_info.has_pad_y = false;
+    ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::validate(a, &tmp_b_info, c, output, alpha, beta, lhs_info, rhs_info, kernel_info));
+
+    kernel_info.has_pad_y = true;
     ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::validate(a, &tmp_b_info, c, output, alpha, beta, lhs_info, rhs_info, kernel_info));
 
     return Status{};
@@ -514,6 +523,8 @@ void CLGEMM::configure(const CLCompileContext &compile_context, const ICLTensor
     _reshape_b_only_on_first_run = gemm_info.reshape_b_only_on_first_run();
     _is_prepared                 = gemm_info.retain_internal_weights();
     _original_b                  = b;
+    _lhs                         = a;
+    _dst                         = output;
 
     // Get the GPU target
     bool               reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d();
@@ -608,7 +619,6 @@ Status CLGEMM::validate(const ITensorInfo *a, const ITensorInfo *b, const ITenso
 void CLGEMM::run()
 {
     prepare();
-
     MemoryGroupResourceScope scope_mg(_memory_group);
 
     // Run matrix multiply kernel
@@ -675,8 +685,14 @@ void CLGEMM::run()
                     CLScheduler::get().enqueue(_reshape_rhs_kernel, false);
                 }
             }
-
-            CLScheduler::get().enqueue(_mm_reshaped_only_rhs_kernel, true);
+            if(_has_pad_y)
+            {
+                CLScheduler::get().enqueue(_mm_reshaped_only_rhs_fallback_kernel, true);
+            }
+            else
+            {
+                CLScheduler::get().enqueue(_mm_reshaped_only_rhs_kernel, true);
+            }
             break;
         }
         default:
@@ -690,6 +706,16 @@ void CLGEMM::prepare()
 {
     if(!_is_prepared)
     {
+        // In case of RESHAPED_ONLY_RHS, we need to check the padding requirement
+        if(_gemm_kernel_type == CLGEMMKernelType::RESHAPED_ONLY_RHS)
+        {
+            // Check if the lhs or dst tensors have padding
+            const unsigned int cross_plane_pad_lhs = _lhs->info()->padding().top + _lhs->info()->padding().bottom;
+            const unsigned int cross_plane_pad_dst = _dst->info()->padding().top + _dst->info()->padding().bottom;
+
+            _has_pad_y = (cross_plane_pad_lhs != 0) || (cross_plane_pad_dst != 0);
+        }
+
         if(_gemm_kernel_type != CLGEMMKernelType::NATIVE_V1 && _reshape_b_only_on_first_run)
         {
             if(_weights_manager && _weights_manager->are_weights_managed(_original_b))
diff --git a/tests/validation/CL/GEMMMatrixMultiplyReshaped.cpp b/tests/validation/CL/GEMMMatrixMultiplyReshaped.cpp
index 98149ce149..5629a80f8e 100644
--- a/tests/validation/CL/GEMMMatrixMultiplyReshaped.cpp
+++ b/tests/validation/CL/GEMMMatrixMultiplyReshaped.cpp
@@ -340,6 +340,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                                                                      false /**< reinterpret the input as 3D */,
                                                                      true  /**< Flag used to broadcast the bias addition */,
                                                                      false /**< wider accumm */,
+                                                                     false /**< has pad y */,
                                                                    ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
                                                                      1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                                      1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
@@ -354,6 +355,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                                                                      false /**< reinterpret the input as 3D */,
                                                                      true  /**< Flag used to broadcast the bias addition */,
                                                                      false /**< wider accumm */,
+                                                                     false /**< has pad y */,
                                                                    ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
                                                                      1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                                      1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
@@ -371,6 +373,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                                                                      false /**< reinterpret the input as 3D */,
                                                                      false  /**< Flag used to broadcast the bias addition */,
                                                                      false /**< wider accumm */,
+                                                                     false /**< has pad y */,
                                                                    ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
                                                                      1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                                      1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
@@ -386,6 +389,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                                                                      false /**< reinterpret the input as 3D */,
                                                                      false  /**< Flag used to broadcast the bias addition */,
                                                                      true /**< wider accumm */,
+                                                                     true /**< has pad y */,
                                                                    ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
                                                                      1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                                      1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
@@ -400,6 +404,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                                                                      false /**< reinterpret the input as 3D */,
                                                                      false  /**< Flag used to broadcast the bias addition */,
                                                                      false /**< wider accumm */,
+                                                                     false /**< has pad y */,
                                                                    ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
                                                                      1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                                      1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
@@ -573,6 +578,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                                                              false /**< reinterpret the input as 3D */,
                                                              true  /**< Flag used to broadcast the bias addition */,
                                                              false /**< wider accumm */,
+                                                             false /**< has pad y */,
                                                            ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
                                                              1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                              1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
@@ -586,6 +592,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                                                              false /**< reinterpret the input as 3D */,
                                                              true  /**< Flag used to broadcast the bias addition */,
                                                              false /**< wider accumm */,
+                                                             false /**< has pad y */,
                                                            ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
                                                              1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                              1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
@@ -599,6 +606,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                                                              false /**< reinterpret the input as 3D */,
                                                              true  /**< Flag used to broadcast the bias addition */,
                                                              false /**< wider accumm */,
+                                                             false /**< has pad y */,
                                                            ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
                                                              1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                              1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
@@ -613,6 +621,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                                                              false /**< reinterpret the input as 3D */,
                                                              true  /**< Flag used to broadcast the bias addition */,
                                                              false /**< wider accumm */,
+                                                             false /**< has pad y */,
                                                            ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
                                                              1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                              1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
@@ -626,6 +635,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                                                              false /**< reinterpret the input as 3D */,
                                                              true  /**< Flag used to broadcast the bias addition */,
                                                              false /**< wider accumm */,
+                                                             false /**< has pad y */,
                                                            ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
                                                              1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                              1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
@@ -939,6 +949,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                                                              false /**< reinterpret the input as 3D */,
                                                              true  /**< Flag used to broadcast the bias addition */,
                                                              false /**< wider accumm */,
+                                                             false /**< has pad y */,
                                                            ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
                                                              1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                              1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
@@ -952,6 +963,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                                                              false /**< reinterpret the input as 3D */,
                                                              true  /**< Flag used to broadcast the bias addition */,
                                                              false /**< wider accumm */,
+                                                             false /**< has pad y */,
                                                            ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
                                                              1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                              1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
@@ -965,6 +977,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                                                              false /**< reinterpret the input as 3D */,
                                                              true  /**< Flag used to broadcast the bias addition */,
                                                              false /**< wider accumm */,
+                                                             false /**< has pad y */,
                                                            ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
                                                              1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                              1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
@@ -979,6 +992,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                                                              false /**< reinterpret the input as 3D */,
                                                              true  /**< Flag used to broadcast the bias addition */,
                                                              false /**< wider accumm */,
+                                                             false /**< has pad y */,
                                                            ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
                                                              1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                              1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
@@ -992,6 +1006,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                                                              false /**< reinterpret the input as 3D */,
                                                              true  /**< Flag used to broadcast the bias addition */,
                                                              false /**< wider accumm */,
+                                                             false /**< has pad y */,
                                                            ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
                                                              1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                              1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
diff --git a/tests/validation/CL/GEMMMatrixMultiplyReshapedOnlyRHS.cpp b/tests/validation/CL/GEMMMatrixMultiplyReshapedOnlyRHS.cpp
index d792afac1d..33912ae2ba 100644
--- a/tests/validation/CL/GEMMMatrixMultiplyReshapedOnlyRHS.cpp
+++ b/tests/validation/CL/GEMMMatrixMultiplyReshapedOnlyRHS.cpp
@@ -92,13 +92,12 @@ const auto n_values = framework::dataset::make("N", 51);
 const auto k_values = framework::dataset::make("K", 23);
 
 /** Batch size values to test */
-const auto b_values = framework::dataset::make("batch_size", 1, 3);
+const auto b_values = framework::dataset::make("batch_size", 2);
 
 /** Activation values to test */
 const auto act_values = framework::dataset::make("Activation",
 {
-    ActivationLayerInfo(),
-    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, -0.8f, 10.f),
 });
 
 /** M0 values to test - precommit */
@@ -211,70 +210,6 @@ bool validate_configuration(unsigned int m_value, unsigned int n_value, unsigned
     CLGEMMMatrixMultiplyReshapedOnlyRHS gemm;
     return bool(gemm.validate(&lhs, &rhs_reshaped, &bias, &dst, alpha, beta, lhs_info, rhs_info, kernel_info));
 }
-
-/** Zero padding test */
-bool validate_zero_padding(unsigned int m_value, unsigned int n_value, unsigned int k_value, unsigned int b_value,
-                            unsigned int m0_value, unsigned int n0_value, unsigned int k0_value, unsigned int h0_value,
-                            bool i_value_rhs, bool t_value_rhs, bool export_to_cl_image, bool broadcast_bias, bool input_as_3d, unsigned int depth_output_gemm3d, const ActivationLayerInfo &act_info,
-                            DataType dt_input0, DataType dt_input1, DataType dt_input2, DataType dt_output, float alpha, float beta)
-{
-    const unsigned int M = m_value;
-    const unsigned int N = n_value;
-    const unsigned int K = k_value;
-
-    GEMMLHSMatrixInfo lhs_info;
-    lhs_info.m0         = m0_value;
-    lhs_info.k0         = k0_value;
-
-    GEMMRHSMatrixInfo rhs_info;
-    rhs_info.n0         = n0_value;
-    rhs_info.k0         = k0_value;
-    rhs_info.h0         = h0_value;
-    rhs_info.interleave = i_value_rhs;
-    rhs_info.transpose  = t_value_rhs;
-    rhs_info.export_to_cl_image = export_to_cl_image;
-
-    GEMMKernelInfo kernel_info;
-    kernel_info.m                       = M;
-    kernel_info.n                       = N;
-    kernel_info.k                       = K;
-    kernel_info.depth_output_gemm3d     = depth_output_gemm3d;
-    kernel_info.reinterpret_input_as_3d = input_as_3d;
-    kernel_info.broadcast_bias          = broadcast_bias;
-    kernel_info.activation_info         = act_info;
-
-    const TensorShape lhs_shape(K, M, b_value);
-    const TensorShape rhs_shape(N, K, b_value);
-    const TensorShape rhs_shape_reshaped = compute_rhs_reshaped_shape(TensorInfo(rhs_shape, 1, dt_input1),
-                                                                      rhs_info);
-
-    const TensorShape dst_shape = compute_mm_shape(TensorInfo(lhs_shape, 1, dt_input0),
-                                                   TensorInfo(rhs_shape_reshaped, 1, dt_input1),
-                                                   kernel_info);
-
-    const TensorShape bias_shape(N,
-                                 M, // Correct calculation should be: broadcast_bias? 1 : M, it's wrong here on purpose just for validation test
-                                 broadcast_bias? 1 : b_value);
-
-    // Create tensors
-    CLTensor lhs  = create_tensor<CLTensor>(lhs_shape, dt_input0);
-    CLTensor rhs_reshaped  = create_tensor<CLTensor>(rhs_shape_reshaped, dt_input1);
-    CLTensor bias = create_tensor<CLTensor>(bias_shape, dt_input2);
-    CLTensor dst  = create_tensor<CLTensor>(dst_shape, dt_output);
-
-    ARM_COMPUTE_EXPECT(lhs.info()->is_resizable(), framework::LogLevel::ERRORS);
-    ARM_COMPUTE_EXPECT(rhs_reshaped.info()->is_resizable(), framework::LogLevel::ERRORS);
-    ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);
-    ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
-
-    // Validate zero-padding
-    CLGEMMMatrixMultiplyReshapedOnlyRHS gemm;
-
-    gemm.configure(&lhs, &rhs_reshaped, &bias, &dst, alpha, beta, lhs_info, rhs_info, kernel_info);
-
-    // Padding can be added along rhs and bias's X dimension
-    return dst.info()->padding().empty() && lhs.info()->padding().empty() && bias.info()->padding().bottom == 0 && bias.info()->padding().top == 0;
-}
 } // namespace
 
 TEST_SUITE(CL)
@@ -326,33 +261,6 @@ b_value, m0_value, n0_value, k0_value, broadcast_bias, input_as_3d, depth_output
     ARM_COMPUTE_EXPECT(status == expected_value, framework::LogLevel::ERRORS);
 }
 
-/** Validate zero padding tests
- *
- * A series of validation tests to check that no padding is added as part of configuration for 4 different scenarios.
- *
- * Checks performed in order:
- *     - No partial blocks in both x and y dimensions
- *     - Partial blocks in x dimension
- *     - Partial blocks in y dimension
- *     - Partial blocks in both x and y dimensions
- *     - Special case: partial_n0 == 9 (vstore1 should be invoked instead of vstore_partial_1)
- */
-DATA_TEST_CASE(ValidateZeroPadding, framework::DatasetMode::ALL, zip(zip(zip(zip(
-framework::dataset::make("M",                   { 24, 64, 101,   1, 100 }),
-framework::dataset::make("N",                   { 48, 29,  16, 122,  41 })),
-framework::dataset::make("M0",                  {  4,  8,   7,   2,   1 })),
-framework::dataset::make("N0",                  {  4,  4,  16,   3,  16 })),
-framework::dataset::make("export_to_cl_image",  { false, true, true, false, false })),
-m_value, n_value, m0_value, n0_value, export_to_cl_image)
-{
-    constexpr DataType dt = DataType::F32;
-    // Disable export_to_cl_image if the target platform does not support the OpenCL cl_khr_image2d_from_buffer extension
-    bool actual_export_to_cl_image = image2d_from_buffer_supported(CLKernelLibrary::get().get_device()) && export_to_cl_image;
-
-    bool status = validate_zero_padding(m_value, n_value, 23, 1, m0_value, n0_value, 4, 1, false, false, actual_export_to_cl_image, false, 0, 0, ActivationLayerInfo(), dt, dt, dt, dt, 1.0f, 1.0f);
-    ARM_COMPUTE_EXPECT(status, framework::LogLevel::ERRORS);
-}
-
 TEST_SUITE(Float)
 TEST_SUITE(FP32)
 
@@ -443,7 +351,7 @@ FIXTURE_DATA_TEST_CASE(RunNightly, CLGEMMMatrixMultiplyReshapedOnlyRHSFixture<fl
 }
 
 FIXTURE_DATA_TEST_CASE(RunPrecommit3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixture<float>, framework::DatasetMode::PRECOMMIT,
-                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
                                                                    m_w_values,
                                                                    m_h_values),
                                                                    n_values),
@@ -456,6 +364,7 @@ FIXTURE_DATA_TEST_CASE(RunPrecommit3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixt
                                                                    i_values_rhs),
                                                                    t_values_rhs),
                                                                    framework::dataset::make("export_to_cl_image_rhs", false)),
+                                                                   framework::dataset::make("has_pad_y", {false, true})),
                                                                    framework::dataset::make("DataType", DataType::F32)),
                                                                    a_values),
                                                                    beta_values),
@@ -466,7 +375,7 @@ FIXTURE_DATA_TEST_CASE(RunPrecommit3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixt
 }
 
 FIXTURE_DATA_TEST_CASE(RunNightly3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixture<float>, framework::DatasetMode::NIGHTLY,
-                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
                                                                    m_w_values,
                                                                    m_h_values),
                                                                    n_values),
@@ -479,6 +388,7 @@ FIXTURE_DATA_TEST_CASE(RunNightly3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixtur
                                                                    i_values_rhs),
                                                                    t_values_rhs),
                                                                    framework::dataset::make("export_to_cl_image_rhs", false)),
+                                                                   framework::dataset::make("has_pad_y", {false, true})),
                                                                    framework::dataset::make("DataType", DataType::F32)),
                                                                    a_values),
                                                                    beta_values),
@@ -552,7 +462,7 @@ FIXTURE_DATA_TEST_CASE(RunNightly, CLGEMMMatrixMultiplyReshapedOnlyRHSFixture<fl
 }
 
 FIXTURE_DATA_TEST_CASE(RunPrecommit3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixture<float>, framework::DatasetMode::PRECOMMIT,
-                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
                                                                    m_w_values,
                                                                    m_h_values),
                                                                    n_values),
@@ -565,6 +475,7 @@ FIXTURE_DATA_TEST_CASE(RunPrecommit3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixt
                                                                    i_values_rhs),
                                                                    t_values_rhs),
                                                                    framework::dataset::make("export_to_cl_image_rhs", true)),
+                                                                   framework::dataset::make("has_pad_y", {false, true})),
                                                                    framework::dataset::make("DataType", DataType::F32)),
                                                                    a_values),
                                                                    beta_values),
@@ -575,7 +486,7 @@ FIXTURE_DATA_TEST_CASE(RunPrecommit3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixt
 }
 
 FIXTURE_DATA_TEST_CASE(RunNightly3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixture<float>, framework::DatasetMode::NIGHTLY,
-                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
                                                                    m_w_values,
                                                                    m_h_values),
                                                                    n_values),
@@ -588,6 +499,7 @@ FIXTURE_DATA_TEST_CASE(RunNightly3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixtur
                                                                    i_values_rhs),
                                                                    t_values_rhs),
                                                                    framework::dataset::make("export_to_cl_image_rhs", true)),
+                                                                   framework::dataset::make("has_pad_y", {false, true})),
                                                                    framework::dataset::make("DataType", DataType::F32)),
                                                                    a_values),
                                                                    beta_values),
@@ -647,7 +559,7 @@ FIXTURE_DATA_TEST_CASE(RunNightly, CLGEMMMatrixMultiplyReshapedOnlyRHSFixture<ha
 }
 
 FIXTURE_DATA_TEST_CASE(RunPrecommit3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixture<half>, framework::DatasetMode::PRECOMMIT,
-                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
                                                                    m_w_values,
                                                                    m_h_values),
                                                                    n_values),
@@ -660,6 +572,7 @@ FIXTURE_DATA_TEST_CASE(RunPrecommit3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixt
                                                                    i_values_rhs),
                                                                    t_values_rhs),
                                                                    framework::dataset::make("export_to_cl_image_rhs", false)),
+                                                                   framework::dataset::make("has_pad_y", {false, true})),
                                                                    framework::dataset::make("DataType", DataType::F16)),
                                                                    a_values),
                                                                    beta_values),
@@ -670,7 +583,7 @@ FIXTURE_DATA_TEST_CASE(RunPrecommit3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixt
 }
 
 FIXTURE_DATA_TEST_CASE(RunNightly3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixture<half>, framework::DatasetMode::NIGHTLY,
-                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
                                                                    m_w_values,
                                                                    m_h_values),
                                                                    n_values),
@@ -683,6 +596,7 @@ FIXTURE_DATA_TEST_CASE(RunNightly3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixtur
                                                                    i_values_rhs),
                                                                    t_values_rhs),
                                                                    framework::dataset::make("export_to_cl_image_rhs", false)),
+                                                                   framework::dataset::make("has_pad_y", {false, true})),
                                                                    framework::dataset::make("DataType", DataType::F16)),
                                                                    a_values),
                                                                    beta_values),
@@ -756,7 +670,7 @@ FIXTURE_DATA_TEST_CASE(RunNightly, CLGEMMMatrixMultiplyReshapedOnlyRHSFixture<ha
 }
 
 FIXTURE_DATA_TEST_CASE(RunPrecommit3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixture<half>, framework::DatasetMode::PRECOMMIT,
-                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
                                                                    m_w_values,
                                                                    m_h_values),
                                                                    n_values),
@@ -769,6 +683,7 @@ FIXTURE_DATA_TEST_CASE(RunPrecommit3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixt
                                                                    i_values_rhs),
                                                                    t_values_rhs),
                                                                    framework::dataset::make("export_to_cl_image_rhs", true)),
+                                                                   framework::dataset::make("has_pad_y", {false, true})),
                                                                    framework::dataset::make("DataType", DataType::F16)),
                                                                    a_values),
                                                                    beta_values),
@@ -779,7 +694,7 @@ FIXTURE_DATA_TEST_CASE(RunPrecommit3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixt
 }
 
 FIXTURE_DATA_TEST_CASE(RunNightly3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixture<half>, framework::DatasetMode::NIGHTLY,
-                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
                                                                    m_w_values,
                                                                    m_h_values),
                                                                    n_values),
@@ -792,6 +707,7 @@ FIXTURE_DATA_TEST_CASE(RunNightly3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixtur
                                                                    i_values_rhs),
                                                                    t_values_rhs),
                                                                    framework::dataset::make("export_to_cl_image_rhs", true)),
+                                                                   framework::dataset::make("has_pad_y", {false, true})),
                                                                    framework::dataset::make("DataType", DataType::F16)),
                                                                    a_values),
                                                                    beta_values),
diff --git a/tests/validation/fixtures/GEMMFixture.h b/tests/validation/fixtures/GEMMFixture.h
index 0a964a7114..6288b6b970 100644
--- a/tests/validation/fixtures/GEMMFixture.h
+++ b/tests/validation/fixtures/GEMMFixture.h
@@ -1125,7 +1125,7 @@ class GEMMMatrixMultiplyReshapedOnlyRHS3DValidationFixture : public framework::F
 public:
     template <typename...>
     void setup(unsigned int m_w, unsigned int m_h, unsigned int n, unsigned int k, unsigned int batch_size, unsigned int m0, unsigned int n0, unsigned int k0, unsigned int h0,
-               bool interleave_rhs, bool transpose_rhs, bool export_to_cl_image, DataType data_type, float alpha, float beta, const ActivationLayerInfo &act_info)
+               bool interleave_rhs, bool transpose_rhs, bool export_to_cl_image, bool has_pad_y, DataType data_type, float alpha, float beta, const ActivationLayerInfo &act_info)
     {
         GEMMLHSMatrixInfo lhs_info;
         lhs_info.m0 = m0;
@@ -1147,7 +1147,7 @@ public:
         const TensorShape rhs_shape(n, k, batch_size);
         const TensorShape bias_shape(n, 1, 1);
 
-        _target    = compute_target(lhs_shape, rhs_shape, bias_shape, lhs_info, rhs_info, data_type, alpha, beta, m_h, act_info);
+        _target    = compute_target(lhs_shape, rhs_shape, bias_shape, lhs_info, rhs_info, data_type, alpha, beta, m_h, act_info, has_pad_y);
         _reference = compute_reference(lhs_shape, rhs_shape, data_type, alpha, beta, m_h, act_info);
     }
 
@@ -1161,7 +1161,7 @@ protected:
 
     TensorType compute_target(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const TensorShape &bias_shape, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info,
                               DataType data_type, float alpha, float beta,
-                              unsigned int m_h, const ActivationLayerInfo &act_info)
+                              unsigned int m_h, const ActivationLayerInfo &act_info, bool has_pad_y)
     {
         // Create tensors
         TensorType lhs  = create_tensor<TensorType>(lhs_shape, data_type, 1);
@@ -1181,15 +1181,22 @@ protected:
         kernel_info.reinterpret_input_as_3d = false;
         kernel_info.broadcast_bias          = true;
         kernel_info.activation_info         = act_info;
+        kernel_info.has_pad_y               = has_pad_y;
 
         // The output tensor will be auto-initialized within the function
-
         // Create and configure function
         ReshapeRHSFunctionType reshape_rhs;
         GEMMFunctionType       gemm;
         reshape_rhs.configure(&rhs, &rhs_reshaped, rhs_info);
         gemm.configure(&lhs, &rhs_reshaped, &bias, &dst, alpha, beta, lhs_info, rhs_info, kernel_info);
 
+        if(has_pad_y)
+        {
+            // Add dummy padding into lhs to validate has_pad_y path
+            lhs.info()->extend_padding(PaddingSize(2, 0, 2, 0));
+            dst.info()->extend_padding(PaddingSize(2, 0, 1, 0));
+        }
+
         ARM_COMPUTE_EXPECT(lhs.info()->is_resizable(), framework::LogLevel::ERRORS);
         ARM_COMPUTE_EXPECT(rhs.info()->is_resizable(), framework::LogLevel::ERRORS);
         ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);