#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_int32 : require #extension GL_KHR_shader_subgroup_shuffle : enable #include "types.comp" #include "flash_attn_base.comp" const uint32_t D_per_thread = D / D_split; const uint32_t cols_per_iter = WorkGroupSize / D_split; const uint32_t cols_per_thread = Bc / cols_per_iter; layout (binding = 0) readonly buffer Q {float data_q[];}; layout (binding = 0) readonly buffer QV4 {vec4 data_qv4[];}; layout (binding = 1) readonly buffer K {float16_t data_k[];}; layout (binding = 1) readonly buffer KV4 {f16vec4 data_kv4[];}; layout (binding = 2) readonly buffer V {float16_t data_v[];}; layout (binding = 2) readonly buffer VV4 {f16vec4 data_vv4[];}; layout (binding = 3) readonly buffer M {float16_t data_m[];}; // 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) { uint32_t offset = (iq2 + r) * D + c; data_o[o_offset + offset] = D_TYPE(elem); return elem; } shared FLOAT_TYPE tmpsh[WorkGroupSize]; shared vec4 tmpshv4[WorkGroupSize]; shared float masksh[Bc][Br]; shared vec4 Qf[Br][D / 4]; void main() { #ifdef NEEDS_INIT_IQ_SHMEM init_iq_shmem(gl_WorkGroupSize); #endif init_indices(); const uint32_t tid = gl_LocalInvocationIndex; const uint32_t d_tid = gl_LocalInvocationIndex % D_split; const uint32_t col_tid = gl_LocalInvocationIndex / D_split; uint32_t q_offset = (iq2*p.nb02+iq3*p.nb03) / 4; [[unroll]] for (uint32_t idx = 0; idx < Br * D / 4; idx += gl_WorkGroupSize.x) { uint32_t d = (idx + tid) % (D / 4); uint32_t r = (idx + tid) / (D / 4); if (r < Br && d < D / 4 && i * Br + r < N) { Qf[r][d] = vec4(data_qv4[q_offset / 4 + (i * Br + r) * q_stride / 4 + d]) * p.scale; } } barrier(); vec4 Of[Br][D_per_thread / 4]; [[unroll]] for (uint32_t d = 0; d < D_per_thread / 4; ++d) { [[unroll]] for (uint32_t r = 0; r < Br; ++r) { Of[r][d] = vec4(0.0); } } float Lf[Br], Mf[Br]; // 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); [[unroll]] for (uint32_t r = 0; r < Br; ++r) { Lf[r] = 0; Mf[r] = NEG_FLT_MAX_OVER_2; } float slope[Br]; [[unroll]] for (uint32_t r = 0; r < Br; ++r) { slope[r] = 1.0; } // ALiBi if (p.max_bias > 0.0f) { [[unroll]] for (uint32_t r = 0; r < Br; ++r) { slope[r] = perElemOpComputeSlope(r, col_tid, ACC_TYPE(0), iq2); } } #if BLOCK_SIZE > 1 uint32_t k_offset = (ik2*p.nb12 + ik3*p.nb13) / BLOCK_BYTE_SIZE; uint32_t v_offset = (iv2*p.nb22 + iv3*p.nb23) / BLOCK_BYTE_SIZE; #else uint32_t k_offset = (ik2*p.nb12 + ik3*p.nb13) / 2; uint32_t v_offset = (iv2*p.nb22 + iv3*p.nb23) / 2; #endif [[dont_unroll]] for (uint32_t j = start_j; j < end_j; ++j) { float Sf[Br][cols_per_thread]; [[unroll]] for (uint32_t r = 0; r < Br; ++r) { [[unroll]] for (uint32_t c = 0; c < cols_per_thread; ++c) { Sf[r][c] = 0.0; } } [[unroll]] for (uint32_t c = 0; c < cols_per_thread; ++c) { [[unroll]] for (uint32_t d = 0; d < D_per_thread / 4; ++d) { #if BLOCK_SIZE > 1 uint coord = (j * Bc + c * cols_per_iter + col_tid) * k_stride * BLOCK_SIZE + 4 * (d * D_split + d_tid); uint ib = coord / BLOCK_SIZE; uint iqs = (coord % BLOCK_SIZE); vec4 K_Tf = dequantize4(ib, iqs, k_offset, BINDING_IDX_K); #else vec4 K_Tf = vec4(data_kv4[k_offset / 4 + (j * Bc + c * cols_per_iter + col_tid) * k_stride / 4 + d * D_split + d_tid]); #endif [[unroll]] for (uint32_t r = 0; r < Br; ++r) { Sf[r][c] += dot(Qf[r][d * D_split + d_tid], K_Tf); } } } [[unroll]] for (uint32_t c = 0; c < cols_per_thread; ++c) { // Compute sum across the D_split [[unroll]] for (uint s = D_split / 2; s > 0; s >>= 1) { [[unroll]] for (uint32_t r = 0; r < Br; ++r) { Sf[r][c] += subgroupShuffleXor(Sf[r][c], s); } } } if (p.logit_softcap != 0.0f) { [[unroll]] for (uint32_t r = 0; r < Br; ++r) { [[unroll]] for (uint32_t c = 0; c < cols_per_thread; ++c) { Sf[r][c] = p.logit_softcap * tanh(Sf[r][c]); } } } if (p.mask != 0) { [[unroll]] for (uint32_t idx = 0; idx < Bc * Br; idx += gl_WorkGroupSize.x) { uint32_t c = (idx + tid) % Bc; uint32_t r = (idx + tid) / Bc; if (idx + tid < Bc * Br) { masksh[c][r] = float(data_m[(i * Br + r) * m_stride + (j * Bc + c)]); } } barrier(); [[unroll]] for (uint32_t c = 0; c < cols_per_thread; ++c) { [[unroll]] for (uint32_t r = 0; r < Br; ++r) { float mvf = masksh[c * cols_per_iter + col_tid][r]; Sf[r][c] += slope[r]*mvf; } } barrier(); } float rowmaxf[Br], Pf[Br][cols_per_thread], rowsumf[Br], eMf[Br], Moldf[Br]; [[unroll]] for (uint32_t r = 0; r < Br; ++r) { rowmaxf[r] = Sf[r][0]; [[unroll]] for (uint32_t c = 0; c < cols_per_thread; ++c) { rowmaxf[r] = max(rowmaxf[r], Sf[r][c]); } Moldf[r] = Mf[r]; // M = max(rowmax, Mold) // P = e^(S - M) // eM = e^(Mold - M) Mf[r] = max(rowmaxf[r], Moldf[r]); [[unroll]] for (uint32_t c = 0; c < cols_per_thread; ++c) { Pf[r][c] = exp(Sf[r][c] - Mf[r]); } eMf[r] = exp(Moldf[r] - Mf[r]); // Compute sum across row of P rowsumf[r] = 0.0; [[unroll]] for (uint32_t c = 0; c < cols_per_thread; ++c) { rowsumf[r] += Pf[r][c]; } Lf[r] = eMf[r]*Lf[r] + rowsumf[r]; } [[unroll]] for (uint32_t d = 0; d < D_per_thread / 4; ++d) { [[unroll]] for (uint32_t r = 0; r < Br; ++r) { Of[r][d] = eMf[r] * Of[r][d]; } } [[unroll]] for (uint32_t c = 0; c < cols_per_thread; ++c) { [[unroll]] for (uint32_t d = 0; d < D_per_thread / 4; ++d) { #if BLOCK_SIZE > 1 uint coord = (j * Bc + c * cols_per_iter + col_tid) * v_stride * BLOCK_SIZE + 4 * (d * D_split + d_tid); uint ib = coord / BLOCK_SIZE; uint iqs = (coord % BLOCK_SIZE); vec4 Vf = dequantize4(ib, iqs, v_offset, BINDING_IDX_V); #else vec4 Vf = vec4(data_vv4[v_offset / 4 + (j * Bc + c * cols_per_iter + col_tid) * v_stride / 4 + d * D_split + d_tid]); #endif [[unroll]] for (uint32_t r = 0; r < Br; ++r) { Of[r][d] += Pf[r][c] * Vf; } } } barrier(); } // reduce across threads [[unroll]] for (uint32_t r = 0; r < Br; ++r) { float rowmaxf, eMf; tmpsh[tid] = Mf[r]; // Compute max across the row barrier(); [[unroll]] for (int s = int(gl_WorkGroupSize.x) / 2; s >= D_split; s >>= 1) { if (tid < s) { tmpsh[tid] = max(tmpsh[tid], tmpsh[tid + s]); } barrier(); } rowmaxf = tmpsh[d_tid]; barrier(); float Moldf = Mf[r]; // M = max(rowmax, Mold) // eM = e^(Mold - M) Mf[r] = max(rowmaxf, Moldf); eMf = exp(Moldf - Mf[r]); Lf[r] = eMf*Lf[r]; tmpsh[tid] = Lf[r]; // Compute sum across the row barrier(); [[unroll]] for (int s = int(gl_WorkGroupSize.x) / 2; s >= D_split; s >>= 1) { if (tid < s) { tmpsh[tid] = tmpsh[tid] + tmpsh[tid + s]; } barrier(); } Lf[r] = tmpsh[d_tid]; barrier(); [[unroll]] for (uint32_t d = 0; d < D_per_thread / 4; ++d) { Of[r][d] = eMf * Of[r][d]; tmpshv4[tid] = Of[r][d]; barrier(); [[unroll]] for (int s = int(gl_WorkGroupSize.x) / 2; s >= D_split; s >>= 1) { if (tid < s) { Of[r][d] += tmpshv4[tid + s]; tmpshv4[tid] = Of[r][d]; } barrier(); } Of[r][d] = tmpshv4[d_tid]; barrier(); } } // 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) { uint32_t o_offset = D * p.ne1 * split_k_index; [[unroll]] for (uint32_t r = 0; r < Br; ++r) { if (r < N) { [[unroll]] for (uint32_t d = 0; d < D_per_thread / 4; ++d) { [[unroll]] for (uint32_t comp = 0; comp < 4; ++comp) { perElemOpGqaStore(r, 4*(d * D_split + d_tid) + comp, Of[r][d][comp], o_offset, iq2, N); } } } } o_offset = D * p.ne1 * p.k_num + p.ne1 * split_k_index * 2; [[unroll]] for (uint32_t r = 0; r < Br; ++r) { if (r < N) { perElemOpStoreCol0(r, 0u, ACC_TYPE(Lf[r]), o_offset, iq2, N); perElemOpStoreCol0(r, 0u, ACC_TYPE(Mf[r]), o_offset + p.ne1, iq2, N); } } return; } float Lfrcp[Br]; [[unroll]] for (uint32_t r = 0; r < Br; ++r) { Lfrcp[r] = 1.0 / Lf[r]; } [[unroll]] for (uint32_t d = 0; d < D_per_thread / 4; ++d) { [[unroll]] for (uint32_t r = 0; r < Br; ++r) { Of[r][d] *= Lfrcp[r]; } } uint32_t o_offset = iq3*p.ne2*p.ne1; if (p.gqa_ratio > 1) { [[unroll]] for (uint32_t r = 0; r < Br; ++r) { if (r < N) { [[unroll]] for (uint32_t d = 0; d < D_per_thread / 4; ++d) { [[unroll]] for (uint32_t comp = 0; comp < 4; ++comp) { perElemOpGqaStore(r, 4*(d * D_split + d_tid) + comp, Of[r][d][comp], o_offset, iq2, N); } } } } } else { [[unroll]] for (uint32_t r = 0; r < Br; ++r) { if (i * Br + r < N) { [[unroll]] for (uint32_t d = 0; d < D_per_thread / 4; ++d) { [[unroll]] for (uint32_t comp = 0; comp < 4; ++comp) { data_o[o_offset + iq2 * D + (i * Br + r) * p.ne1 * D + 4*(d * D_split + d_tid) + comp] = D_TYPE(Of[r][d][comp]); } } } } } }