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https://github.com/ggerganov/whisper.cpp.git
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vulkan: Add N/2 and N/4 optimized paths in coopmat2 shader (llama/12312)
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ggml/src/ggml-vulkan
@ -1597,33 +1597,33 @@ static void ggml_vk_load_shaders(vk_device& device) {
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uint32_t l_align, m_align, s_align;
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if (device->coopmat2) {
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// spec constants and tile sizes for non-quant matmul/matmul_id
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l_warptile = { 256, 128, 256, 64 };
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m_warptile = { 256, 128, 128, 64 };
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s_warptile = { 128, 64, 64, 64 };
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l_warptile = { 256, 128, 256, 64, 1 };
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m_warptile = { 256, 128, 128, 64, 0 };
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s_warptile = { 128, 64, 64, 64, 0 };
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l_wg_denoms = {128, 256, 1 };
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m_wg_denoms = {128, 128, 1 };
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s_wg_denoms = { 64, 64, 1 };
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// spec constants and tile sizes for quant matmul (non-Qi_K)
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l_warptile_mmq = { 256, 128, 256, 64 };
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m_warptile_mmq = { 256, 128, 128, 64 };
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s_warptile_mmq = { 256, 32, 64, 128 };
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l_warptile_mmq = { 256, 128, 256, 64, 1 };
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m_warptile_mmq = { 256, 128, 128, 64, 1 };
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s_warptile_mmq = { 256, 32, 64, 128, 0 };
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l_mmq_wg_denoms = { 128, 256, 1 };
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m_mmq_wg_denoms = { 128, 128, 1 };
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s_mmq_wg_denoms = { 32, 64, 1 };
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// spec constants and tile sizes for quant matmul (Qi_K)
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l_warptile_mmq_k = { 256, 64, 128, 64 };
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m_warptile_mmq_k = { 256, 32, 64, 64 };
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s_warptile_mmq_k = { 256, 32, 32, 128 };
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l_warptile_mmq_k = { 256, 64, 128, 64, 1 };
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m_warptile_mmq_k = { 256, 32, 64, 64, 0 };
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s_warptile_mmq_k = { 256, 32, 32, 128, 0 };
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l_mmq_wg_denoms_k = { 64, 128, 1 };
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m_mmq_wg_denoms_k = { 32, 64, 1 };
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s_mmq_wg_denoms_k = { 32, 32, 1 };
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// spec constants and tile sizes for quant matmul_id
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l_warptile_mmqid = { 256, 128, 64, 16 };
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m_warptile_mmqid = { 256, 128, 64, 16 };
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s_warptile_mmqid = { 256, 128, 64, 16 };
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l_warptile_mmqid = { 256, 128, 64, 16, 0 };
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m_warptile_mmqid = { 256, 128, 64, 16, 0 };
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s_warptile_mmqid = { 256, 128, 64, 16, 0 };
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l_mmqid_wg_denoms = { 128, 64, 1 };
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m_mmqid_wg_denoms = { 128, 64, 1 };
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s_mmqid_wg_denoms = { 128, 64, 1 };
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@ -23,6 +23,10 @@ layout (constant_id = 1) const uint BM = 64;
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layout (constant_id = 2) const uint BN = 64;
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layout (constant_id = 3) const uint BK = 16; // Assumed to be 32 if working with a quant
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layout (constant_id = 4) const bool enable_smaller_matrices = false;
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const uint BNover2 = enable_smaller_matrices ? (BN / 2) : BN;
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const uint BNover4 = enable_smaller_matrices ? (BN / 4) : BN;
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layout (push_constant) uniform parameter
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{
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uint M;
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@ -168,15 +172,13 @@ void main() {
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const uint end_k = min(p.K, (ik + 1) * p.k_split);
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#endif
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coopmat<ACC_TYPE, gl_ScopeWorkgroup, BM, BN, gl_MatrixUseAccumulator> sum;
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sum = coopmat<ACC_TYPE, gl_ScopeWorkgroup, BM, BN, gl_MatrixUseAccumulator>(0.0);
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#ifdef MUL_MAT_ID
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uint pos_a = (expert_idx * p.batch_stride_a) / QUANT_K;
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uint pos_b = 0;
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#else
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uint pos_a = (batch_idx_a * p.batch_stride_a) / QUANT_K;
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uint pos_b = batch_idx * p.batch_stride_b;
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uint pos_d = batch_idx * p.batch_stride_d + ik * p.batch_stride_d * gl_NumWorkGroups.z;
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#endif
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uint stride_a = p.stride_a / QUANT_K;
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@ -197,6 +199,7 @@ void main() {
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tensorLayoutNV<2> tensorLayoutB = createTensorLayoutNV(2);
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tensorLayoutNV<2, gl_CooperativeMatrixClampModeConstantNV> tensorLayoutBClamp = createTensorLayoutNV(2, gl_CooperativeMatrixClampModeConstantNV);
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tensorLayoutNV<2, gl_CooperativeMatrixClampModeConstantNV> tensorLayoutD = createTensorLayoutNV(2, gl_CooperativeMatrixClampModeConstantNV);
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tensorLayoutD = setTensorLayoutStrideNV(tensorLayoutD, p.stride_d, 1);
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#if QUANT_K > 1
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tensorLayoutA = setTensorLayoutBlockSizeNV(tensorLayoutA, 1, QUANT_K);
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@ -232,16 +235,54 @@ void main() {
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tensorLayoutB = setTensorLayoutStrideNV(tensorLayoutB, stride_b, 1);
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uint k_iters = (end_k - start_k + BK - 1) / BK;
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if (enable_smaller_matrices && ic * BN + BNover4 >= p.N) {
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coopmat<ACC_TYPE, gl_ScopeWorkgroup, BM, BNover4, gl_MatrixUseAccumulator> sum = coopmat<ACC_TYPE, gl_ScopeWorkgroup, BM, BNover4, gl_MatrixUseAccumulator>(0.0);
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for (uint block_k = start_k, i = 0; i < k_iters; block_k += BK, ++i) {
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for (uint block_k = start_k, i = 0; i < k_iters; block_k += BK, ++i) {
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coopmat<FLOAT_TYPE, gl_ScopeWorkgroup, BM, BK, gl_MatrixUseA> mat_a;
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coopmat<FLOAT_TYPE, gl_ScopeWorkgroup, BK, BNover4, gl_MatrixUseB> mat_b;
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coopmat<FLOAT_TYPE, gl_ScopeWorkgroup, BM, BK, gl_MatrixUseA> mat_a;
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coopmat<FLOAT_TYPE, gl_ScopeWorkgroup, BK, BN, gl_MatrixUseB> mat_b;
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coopMatLoadTensorNV(mat_a, data_a, pos_a, sliceTensorLayoutNV(tensorLayoutA, ir * BM, BM, block_k, BK) DECODEFUNCA);
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coopMatLoadTensorNV(mat_b, data_b, pos_b, sliceTensorLayoutNV(tensorLayoutB, ic * BN, BNover4, block_k, BK), tensorViewTranspose);
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coopMatLoadTensorNV(mat_a, data_a, pos_a, sliceTensorLayoutNV(tensorLayoutA, ir * BM, BM, block_k, BK) DECODEFUNCA);
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coopMatLoadTensorNV(mat_b, data_b, pos_b, sliceTensorLayoutNV(tensorLayoutB, ic * BN, BN, block_k, BK), tensorViewTranspose);
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sum = coopMatMulAdd(mat_a, mat_b, sum);
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}
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coopmat<D_TYPE, gl_ScopeWorkgroup, BM, BNover4, gl_MatrixUseAccumulator> mat_d = coopmat<D_TYPE, gl_ScopeWorkgroup, BM, BNover4, gl_MatrixUseAccumulator>(sum);
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sum = coopMatMulAdd(mat_a, mat_b, sum);
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coopMatStoreTensorNV(mat_d, data_d, pos_d, sliceTensorLayoutNV(tensorLayoutD, ic * BN, BNover4, ir * BM, BM), tensorViewTranspose);
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return;
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} else if (enable_smaller_matrices && ic * BN + BNover2 >= p.N) {
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coopmat<ACC_TYPE, gl_ScopeWorkgroup, BM, BNover2, gl_MatrixUseAccumulator> sum = coopmat<ACC_TYPE, gl_ScopeWorkgroup, BM, BNover2, gl_MatrixUseAccumulator>(0.0);
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for (uint block_k = start_k, i = 0; i < k_iters; block_k += BK, ++i) {
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coopmat<FLOAT_TYPE, gl_ScopeWorkgroup, BM, BK, gl_MatrixUseA> mat_a;
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coopmat<FLOAT_TYPE, gl_ScopeWorkgroup, BK, BNover2, gl_MatrixUseB> mat_b;
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coopMatLoadTensorNV(mat_a, data_a, pos_a, sliceTensorLayoutNV(tensorLayoutA, ir * BM, BM, block_k, BK) DECODEFUNCA);
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coopMatLoadTensorNV(mat_b, data_b, pos_b, sliceTensorLayoutNV(tensorLayoutB, ic * BN, BNover2, block_k, BK), tensorViewTranspose);
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sum = coopMatMulAdd(mat_a, mat_b, sum);
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}
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coopmat<D_TYPE, gl_ScopeWorkgroup, BM, BNover2, gl_MatrixUseAccumulator> mat_d = coopmat<D_TYPE, gl_ScopeWorkgroup, BM, BNover2, gl_MatrixUseAccumulator>(sum);
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coopMatStoreTensorNV(mat_d, data_d, pos_d, sliceTensorLayoutNV(tensorLayoutD, ic * BN, BNover2, ir * BM, BM), tensorViewTranspose);
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return;
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} else {
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coopmat<ACC_TYPE, gl_ScopeWorkgroup, BM, BN, gl_MatrixUseAccumulator> sum = coopmat<ACC_TYPE, gl_ScopeWorkgroup, BM, BN, gl_MatrixUseAccumulator>(0.0);
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for (uint block_k = start_k, i = 0; i < k_iters; block_k += BK, ++i) {
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coopmat<FLOAT_TYPE, gl_ScopeWorkgroup, BM, BK, gl_MatrixUseA> mat_a;
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coopmat<FLOAT_TYPE, gl_ScopeWorkgroup, BK, BN, gl_MatrixUseB> mat_b;
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coopMatLoadTensorNV(mat_a, data_a, pos_a, sliceTensorLayoutNV(tensorLayoutA, ir * BM, BM, block_k, BK) DECODEFUNCA);
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coopMatLoadTensorNV(mat_b, data_b, pos_b, sliceTensorLayoutNV(tensorLayoutB, ic * BN, BN, block_k, BK), tensorViewTranspose);
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sum = coopMatMulAdd(mat_a, mat_b, sum);
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}
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coopmat<D_TYPE, gl_ScopeWorkgroup, BM, BN, gl_MatrixUseAccumulator> mat_d = coopmat<D_TYPE, gl_ScopeWorkgroup, BM, BN, gl_MatrixUseAccumulator>(sum);
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coopMatStoreTensorNV(mat_d, data_d, pos_d, sliceTensorLayoutNV(tensorLayoutD, ic * BN, BN, ir * BM, BM), tensorViewTranspose);
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return;
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}
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} else
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#endif // !defined(MUL_MAT_ID)
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@ -254,6 +295,9 @@ void main() {
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tensorLayoutBClamp = setTensorLayoutStrideNV(tensorLayoutBClamp, stride_b, 1);
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coopmat<ACC_TYPE, gl_ScopeWorkgroup, BM, BN, gl_MatrixUseAccumulator> sum;
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sum = coopmat<ACC_TYPE, gl_ScopeWorkgroup, BM, BN, gl_MatrixUseAccumulator>(0.0);
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[[dont_unroll]]
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for (uint block_k = start_k; block_k < end_k; block_k += BK) {
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@ -296,19 +340,16 @@ void main() {
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sum = coopMatMulAdd(mat_a, mat_b, sum);
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}
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}
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}
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// Convert from ACC_TYPE to D_TYPE
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coopmat<D_TYPE, gl_ScopeWorkgroup, BM, BN, gl_MatrixUseAccumulator> mat_d;
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mat_d = coopmat<D_TYPE, gl_ScopeWorkgroup, BM, BN, gl_MatrixUseAccumulator>(sum);
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// Convert from ACC_TYPE to D_TYPE
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coopmat<D_TYPE, gl_ScopeWorkgroup, BM, BN, gl_MatrixUseAccumulator> mat_d;
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mat_d = coopmat<D_TYPE, gl_ScopeWorkgroup, BM, BN, gl_MatrixUseAccumulator>(sum);
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#ifdef MUL_MAT_ID
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// Call callback to store each element, remapping row through shared memory
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coopMatPerElementNV(mat_d, mat_d, perElemOpD, ir, ic);
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// Call callback to store each element, remapping row through shared memory
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coopMatPerElementNV(mat_d, mat_d, perElemOpD, ir, ic);
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#else
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tensorLayoutD = setTensorLayoutStrideNV(tensorLayoutD, p.stride_d, 1);
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uint pos_d = batch_idx * p.batch_stride_d + ik * p.batch_stride_d * gl_NumWorkGroups.z;
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coopMatStoreTensorNV(mat_d, data_d, pos_d, sliceTensorLayoutNV(tensorLayoutD, ic * BN, BN, ir * BM, BM), tensorViewTranspose);
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coopMatStoreTensorNV(mat_d, data_d, pos_d, sliceTensorLayoutNV(tensorLayoutD, ic * BN, BN, ir * BM, BM), tensorViewTranspose);
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#endif
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}
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}
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