#version 450 #extension GL_EXT_control_flow_attributes : enable #extension GL_EXT_shader_16bit_storage : require #extension GL_EXT_shader_explicit_arithmetic_types_float16 : require #extension GL_EXT_shader_explicit_arithmetic_types_int8 : require #extension GL_EXT_shader_explicit_arithmetic_types_int32 : require #extension GL_EXT_shader_explicit_arithmetic_types_int16 : require #extension GL_KHR_memory_scope_semantics : enable #extension GL_KHR_cooperative_matrix : enable #extension GL_NV_cooperative_matrix2 : enable #extension GL_EXT_buffer_reference : enable #extension GL_KHR_shader_subgroup_ballot : enable #extension GL_KHR_shader_subgroup_vote : enable #extension GL_EXT_null_initializer : enable #include "types.comp" #include "dequant_funcs_cm2.comp" #include "flash_attn_base.comp" layout (binding = 0) readonly buffer Q {uint8_t data_q[];}; layout (binding = 1) readonly buffer K {uint8_t data_k[];}; layout (binding = 2) readonly buffer V {uint8_t data_v[];}; layout (binding = 3) readonly buffer M {uint8_t data_m[];}; ACC_TYPE maxReduce(const in ACC_TYPE x, const in ACC_TYPE y) { return max(x, y); } ACC_TYPE smearReduce(const in ACC_TYPE x, const in ACC_TYPE y) { return x; } // Replace matrix elements >= numRows or numCols with 'replace' ACC_TYPE replacePadding(const in uint32_t row, const in uint32_t col, const in ACC_TYPE elem, const in ACC_TYPE replace, const in uint32_t numRows, const in uint32_t numCols) { if (row >= numRows || col >= numCols) { return replace; } return elem; } ACC_TYPE Exp(const in uint32_t row, const in uint32_t col, const in ACC_TYPE elem) { return exp(elem); } ACC_TYPE Max(const in uint32_t row, const in uint32_t col, const in ACC_TYPE elem0, const in ACC_TYPE elem1) { return max(elem0, elem1); } #if defined(BLOCK_SIZE) #define DECODEFUNC , DEQUANTFUNC #else #define DECODEFUNC #endif // Store the output when doing grouped query attention. // Rows index by Q's dimension 2, and the first N rows are valid. D_TYPE perElemOpGqaStore(const in uint32_t r, const in uint32_t c, const in D_TYPE elem, const in uint32_t o_offset, const in uint32_t iq2, const in uint32_t N) { if (r < N && c < HSV) { uint32_t offset = (iq2 + r) * HSV + c; data_o[o_offset + offset] = D_TYPE(elem); } return elem; } void main() { #ifdef NEEDS_INIT_IQ_SHMEM init_iq_shmem(gl_WorkGroupSize); #endif init_indices(); tensorLayoutNV<2, gl_CooperativeMatrixClampModeConstantNV> tensorLayoutQ = createTensorLayoutNV(2, gl_CooperativeMatrixClampModeConstantNV); tensorLayoutNV<2, Clamp> tensorLayoutK = createTensorLayoutNV(2, Clamp); tensorLayoutNV<2, Clamp> tensorLayoutV = createTensorLayoutNV(2, Clamp); tensorViewNV<2, false, 1, 0> tensorViewTranspose = createTensorViewNV(2, false, 1, 0); #if defined(BLOCK_SIZE) tensorLayoutK = setTensorLayoutBlockSizeNV(tensorLayoutK, 1, BLOCK_SIZE); tensorLayoutV = setTensorLayoutBlockSizeNV(tensorLayoutV, 1, BLOCK_SIZE); #endif tensorLayoutQ = setTensorLayoutDimensionNV(tensorLayoutQ, N, HSK); tensorLayoutK = setTensorLayoutDimensionNV(tensorLayoutK, KV, HSK); tensorLayoutV = setTensorLayoutDimensionNV(tensorLayoutV, KV, HSV); // hint to the compiler that strides are aligned for the aligned variant of the shader if (Clamp != gl_CooperativeMatrixClampModeConstantNV) { q_stride &= ~7; #if !defined(BLOCK_SIZE) k_stride &= ~7; v_stride &= ~7; #endif m_stride &= ~7; } tensorLayoutQ = setTensorLayoutStrideNV(tensorLayoutQ, q_stride, 1); tensorLayoutK = setTensorLayoutStrideNV(tensorLayoutK, k_stride, 1); tensorLayoutV = setTensorLayoutStrideNV(tensorLayoutV, v_stride, 1); coopmat Q; coopmat Qf16; uint32_t q_offset = iq2*p.nb02+iq3*p.nb03; coopMatLoadTensorNV(Q, data_q, q_offset, sliceTensorLayoutNV(tensorLayoutQ, i * Br, Br, 0, HSK)); Qf16 = coopmat(Q); Qf16 *= float16_t(p.scale); coopmat O = coopmat(0); coopmat L, M; // Use -FLT_MAX/2 rather than -inf to reduce the possibility of NaNs, e.g. when computing Mold-M. const float NEG_FLT_MAX_OVER_2 = uintBitsToFloat(0xFEFFFFFF); L = coopmat(0); M = coopmat(NEG_FLT_MAX_OVER_2); coopmat slopeMat = coopmat(1.0); // ALiBi if (p.max_bias > 0.0f) { coopMatPerElementNV(slopeMat, slopeMat, perElemOpComputeSlope, iq2); } uint32_t m_offset = 0; if (p.nem2 != 1 || p.nem3 != 1) { m_offset = ((iq3 % p.nem3) * p.nem2 + (iq2 % p.nem2)) * p.nem1 * KV * 2 /*sizeof(float16_t)*/; } [[dont_unroll]] for (uint32_t j = start_j; j < end_j; ++j) { coopmat S = coopmat(0); coopmat K_T; uint32_t k_offset = ik2*p.nb12 + ik3*p.nb13; coopMatLoadTensorNV(K_T, data_k, k_offset, sliceTensorLayoutNV(tensorLayoutK, j * Bc, Bc, 0, HSK), tensorViewTranspose DECODEFUNC); S = coopMatMulAdd(Qf16, K_T, S); if (p.logit_softcap != 0.0f) { [[unroll]] for (int k = 0; k < S.length(); ++k) { S[k] = ACC_TYPE(p.logit_softcap)*tanh(S[k]); } } if ((p.mask_n_head_log2 & MASK_ENABLE_BIT) != 0) { tensorLayoutNV<2, Clamp> tensorLayoutM = createTensorLayoutNV(2, Clamp); tensorLayoutM = setTensorLayoutDimensionNV(tensorLayoutM, p.nem1, KV); tensorLayoutM = setTensorLayoutStrideNV(tensorLayoutM, m_stride, 1); coopmat mv; coopMatLoadTensorNV(mv, data_m, m_offset, sliceTensorLayoutNV(tensorLayoutM, i * Br, Br, j * Bc, Bc)); S += slopeMat*coopmat(mv); } // Clear padding elements to -inf, so they don't contribute to rowmax if (Clamp != 0 && ((j + 1) * Bc > KV || (i + 1) * Br > N)) { uint R = ((i + 1) * Br > N) ? (N % Br) : Br; uint C = ((j + 1) * Bc > KV) ? (KV % Bc) : Bc; coopMatPerElementNV(S, S, replacePadding, ACC_TYPE(NEG_FLT_MAX_OVER_2), R, C); } coopmat rowmax, P, rowsum, eM; coopMatReduceNV(rowmax, S, gl_CooperativeMatrixReduceRowNV, maxReduce); coopmat Mold = M; // M = max(rowmax, Mold) // P = e^(S - M) // eM = e^(Mold - M) coopMatPerElementNV(M, rowmax, Max, Mold); coopMatPerElementNV(P, S - M, Exp); coopMatPerElementNV(eM, Mold - M, Exp); // Clear padding elements to 0, so they don't contribute to rowsum if (Clamp != 0 && ((j + 1) * Bc > KV || (i + 1) * Br > N)) { uint R = ((i + 1) * Br > N) ? (N % Br) : Br; uint C = ((j + 1) * Bc > KV) ? (KV % Bc) : Bc; coopMatPerElementNV(P, P, replacePadding, ACC_TYPE(0.0), R, C); } coopmat P_A = coopmat(P); // compute rowsum by multiplying by matrix of all ones. coopmat One = coopmat(1.0); rowsum = coopmat(0.0); rowsum = coopMatMulAdd(P_A, One, rowsum); coopmat V; uint32_t v_offset = iv2*p.nb22 + iv3*p.nb23; coopMatLoadTensorNV(V, data_v, v_offset, sliceTensorLayoutNV(tensorLayoutV, j * Bc, Bc, 0, HSV) DECODEFUNC); L = eM*L + rowsum; // This is the "diagonal" matrix in the paper, but since we do componentwise // multiply rather than matrix multiply it has the diagonal element smeared // across the row coopmat eMdiag; // resize eM by using smear/reduce coopMatReduceNV(eMdiag, eM, gl_CooperativeMatrixReduceRowNV, smearReduce); // multiply with fp16 accumulation, then add to O. coopmat PV = coopmat(0); PV = coopMatMulAdd(P_A, V, PV); O = eMdiag * O + coopmat(PV); } // If there is split_k, then the split_k resolve shader does the final // division by L. Store the intermediate O value and per-row m and L values. if (p.k_num > 1) { coopmat O_D = coopmat(O); uint32_t o_offset = HSV * p.ne1 * (split_k_index + iq3 * p.k_num); coopMatPerElementNV(O_D, O_D, perElemOpGqaStore, o_offset, iq2, N); o_offset = HSV * p.ne1 * p.ne3 * p.k_num + p.ne1 * (split_k_index + iq3 * p.k_num) * 2; coopMatPerElementNV(L, L, perElemOpStoreCol0, o_offset, iq2, N); coopMatPerElementNV(M, M, perElemOpStoreCol0, o_offset + p.ne1, iq2, N); return; } coopmat Ldiag; // resize L by using smear/reduce coopMatReduceNV(Ldiag, L, gl_CooperativeMatrixReduceRowNV, smearReduce); [[unroll]] for (int k = 0; k < Ldiag.length(); ++k) { Ldiag[k] = ACC_TYPE(1.0) / Ldiag[k]; } O = Ldiag*O; uint32_t o_offset = iq3*p.ne2*p.ne1*HSV; coopmat O_D = coopmat(O); if (p.gqa_ratio > 1) { coopMatPerElementNV(O_D, O_D, perElemOpGqaStore, o_offset, iq2, N); } else { tensorLayoutNV<3, gl_CooperativeMatrixClampModeConstantNV> tensorLayoutD = createTensorLayoutNV(3, gl_CooperativeMatrixClampModeConstantNV); tensorLayoutD = setTensorLayoutDimensionNV(tensorLayoutD, p.ne2, p.ne1, HSV); // permute dimensions tensorViewNV<3, false, 1, 0, 2> tensorViewPermute = createTensorViewNV(3, false, 1, 0, 2); coopMatStoreTensorNV(O_D, data_o, o_offset, sliceTensorLayoutNV(tensorLayoutD, i * Br, Br, iq2, N, 0, HSV), tensorViewPermute); } }