mirror of
https://github.com/ggml-org/llama.cpp.git
synced 2025-10-27 08:21:30 +00:00
2f5a4e1e09
* vulkan: move common FA code to flash_attn_base.comp * vulkan: move common FA index/stride setup code to flash_attn_base.comp * build fix
338 lines
11 KiB
Plaintext
338 lines
11 KiB
Plaintext
#version 450
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#extension GL_EXT_control_flow_attributes : enable
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#extension GL_EXT_shader_16bit_storage : require
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#extension GL_EXT_shader_explicit_arithmetic_types_float16 : require
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#extension GL_EXT_shader_explicit_arithmetic_types_int32 : require
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#extension GL_KHR_shader_subgroup_shuffle : enable
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#include "types.comp"
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#include "flash_attn_base.comp"
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const uint32_t D_per_thread = D / D_split;
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const uint32_t cols_per_iter = WorkGroupSize / D_split;
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const uint32_t cols_per_thread = Bc / cols_per_iter;
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layout (binding = 0) readonly buffer Q {float data_q[];};
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layout (binding = 0) readonly buffer QV4 {vec4 data_qv4[];};
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layout (binding = 1) readonly buffer K {float16_t data_k[];};
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layout (binding = 1) readonly buffer KV4 {f16vec4 data_kv4[];};
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layout (binding = 2) readonly buffer V {float16_t data_v[];};
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layout (binding = 2) readonly buffer VV4 {f16vec4 data_vv4[];};
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layout (binding = 3) readonly buffer M {float16_t data_m[];};
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// Store the output when doing grouped query attention.
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// Rows index by Q's dimension 2, and the first N rows are valid.
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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)
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{
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uint32_t offset = (iq2 + r) * D + c;
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data_o[o_offset + offset] = D_TYPE(elem);
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return elem;
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}
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shared FLOAT_TYPE tmpsh[WorkGroupSize];
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shared vec4 tmpshv4[WorkGroupSize];
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shared float masksh[Bc][Br];
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shared vec4 Qf[Br][D / 4];
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void main() {
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#ifdef NEEDS_INIT_IQ_SHMEM
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init_iq_shmem(gl_WorkGroupSize);
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#endif
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init_indices();
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const uint32_t tid = gl_LocalInvocationIndex;
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const uint32_t d_tid = gl_LocalInvocationIndex % D_split;
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const uint32_t col_tid = gl_LocalInvocationIndex / D_split;
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uint32_t q_offset = (iq2*p.nb02+iq3*p.nb03) / 4;
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[[unroll]] for (uint32_t idx = 0; idx < Br * D / 4; idx += gl_WorkGroupSize.x) {
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uint32_t d = (idx + tid) % (D / 4);
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uint32_t r = (idx + tid) / (D / 4);
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if (r < Br && d < D / 4 &&
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i * Br + r < N) {
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Qf[r][d] = vec4(data_qv4[q_offset / 4 + (i * Br + r) * q_stride / 4 + d]) * p.scale;
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}
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}
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barrier();
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vec4 Of[Br][D_per_thread / 4];
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[[unroll]] for (uint32_t d = 0; d < D_per_thread / 4; ++d) {
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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Of[r][d] = vec4(0.0);
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}
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}
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float Lf[Br], Mf[Br];
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// Use -FLT_MAX/2 rather than -inf to reduce the possibility of NaNs, e.g. when computing Mold-M.
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const float NEG_FLT_MAX_OVER_2 = uintBitsToFloat(0xFEFFFFFF);
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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Lf[r] = 0;
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Mf[r] = NEG_FLT_MAX_OVER_2;
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}
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float slope[Br];
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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slope[r] = 1.0;
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}
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// ALiBi
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if (p.max_bias > 0.0f) {
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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slope[r] = perElemOpComputeSlope(r, col_tid, ACC_TYPE(0), iq2);
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}
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}
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#if BLOCK_SIZE > 1
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uint32_t k_offset = (ik2*p.nb12 + ik3*p.nb13) / BLOCK_BYTE_SIZE;
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uint32_t v_offset = (iv2*p.nb22 + iv3*p.nb23) / BLOCK_BYTE_SIZE;
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#else
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uint32_t k_offset = (ik2*p.nb12 + ik3*p.nb13) / 2;
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uint32_t v_offset = (iv2*p.nb22 + iv3*p.nb23) / 2;
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#endif
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[[dont_unroll]]
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for (uint32_t j = start_j; j < end_j; ++j) {
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float Sf[Br][cols_per_thread];
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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[[unroll]] for (uint32_t c = 0; c < cols_per_thread; ++c) {
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Sf[r][c] = 0.0;
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}
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}
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[[unroll]] for (uint32_t c = 0; c < cols_per_thread; ++c) {
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[[unroll]] for (uint32_t d = 0; d < D_per_thread / 4; ++d) {
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#if BLOCK_SIZE > 1
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uint coord = (j * Bc + c * cols_per_iter + col_tid) * k_stride * BLOCK_SIZE + 4 * (d * D_split + d_tid);
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uint ib = coord / BLOCK_SIZE;
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uint iqs = (coord % BLOCK_SIZE);
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vec4 K_Tf = dequantize4(ib, iqs, k_offset, BINDING_IDX_K);
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#else
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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]);
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#endif
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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Sf[r][c] += dot(Qf[r][d * D_split + d_tid], K_Tf);
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}
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}
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}
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[[unroll]] for (uint32_t c = 0; c < cols_per_thread; ++c) {
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// Compute sum across the D_split
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[[unroll]] for (uint s = D_split / 2; s > 0; s >>= 1) {
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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Sf[r][c] += subgroupShuffleXor(Sf[r][c], s);
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}
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}
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}
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if (p.logit_softcap != 0.0f) {
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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[[unroll]] for (uint32_t c = 0; c < cols_per_thread; ++c) {
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Sf[r][c] = p.logit_softcap * tanh(Sf[r][c]);
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}
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}
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}
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if (p.mask != 0) {
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[[unroll]] for (uint32_t idx = 0; idx < Bc * Br; idx += gl_WorkGroupSize.x) {
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uint32_t c = (idx + tid) % Bc;
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uint32_t r = (idx + tid) / Bc;
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if (idx + tid < Bc * Br) {
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masksh[c][r] = float(data_m[(i * Br + r) * m_stride + (j * Bc + c)]);
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}
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}
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barrier();
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[[unroll]] for (uint32_t c = 0; c < cols_per_thread; ++c) {
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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float mvf = masksh[c * cols_per_iter + col_tid][r];
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Sf[r][c] += slope[r]*mvf;
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}
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}
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barrier();
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}
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float rowmaxf[Br], Pf[Br][cols_per_thread], rowsumf[Br], eMf[Br], Moldf[Br];
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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rowmaxf[r] = Sf[r][0];
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[[unroll]] for (uint32_t c = 0; c < cols_per_thread; ++c) {
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rowmaxf[r] = max(rowmaxf[r], Sf[r][c]);
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}
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Moldf[r] = Mf[r];
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// M = max(rowmax, Mold)
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// P = e^(S - M)
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// eM = e^(Mold - M)
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Mf[r] = max(rowmaxf[r], Moldf[r]);
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[[unroll]] for (uint32_t c = 0; c < cols_per_thread; ++c) {
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Pf[r][c] = exp(Sf[r][c] - Mf[r]);
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}
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eMf[r] = exp(Moldf[r] - Mf[r]);
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// Compute sum across row of P
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rowsumf[r] = 0.0;
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[[unroll]] for (uint32_t c = 0; c < cols_per_thread; ++c) {
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rowsumf[r] += Pf[r][c];
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}
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Lf[r] = eMf[r]*Lf[r] + rowsumf[r];
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}
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[[unroll]] for (uint32_t d = 0; d < D_per_thread / 4; ++d) {
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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Of[r][d] = eMf[r] * Of[r][d];
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}
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}
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[[unroll]] for (uint32_t c = 0; c < cols_per_thread; ++c) {
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[[unroll]] for (uint32_t d = 0; d < D_per_thread / 4; ++d) {
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#if BLOCK_SIZE > 1
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uint coord = (j * Bc + c * cols_per_iter + col_tid) * v_stride * BLOCK_SIZE + 4 * (d * D_split + d_tid);
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uint ib = coord / BLOCK_SIZE;
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uint iqs = (coord % BLOCK_SIZE);
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vec4 Vf = dequantize4(ib, iqs, v_offset, BINDING_IDX_V);
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#else
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vec4 Vf = vec4(data_vv4[v_offset / 4 + (j * Bc + c * cols_per_iter + col_tid) * v_stride / 4 + d * D_split + d_tid]);
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#endif
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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Of[r][d] += Pf[r][c] * Vf;
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}
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}
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}
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barrier();
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}
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// reduce across threads
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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float rowmaxf, eMf;
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tmpsh[tid] = Mf[r];
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// Compute max across the row
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barrier();
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[[unroll]] for (int s = int(gl_WorkGroupSize.x) / 2; s >= D_split; s >>= 1) {
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if (tid < s) {
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tmpsh[tid] = max(tmpsh[tid], tmpsh[tid + s]);
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}
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barrier();
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}
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rowmaxf = tmpsh[d_tid];
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barrier();
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float Moldf = Mf[r];
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// M = max(rowmax, Mold)
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// eM = e^(Mold - M)
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Mf[r] = max(rowmaxf, Moldf);
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eMf = exp(Moldf - Mf[r]);
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Lf[r] = eMf*Lf[r];
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tmpsh[tid] = Lf[r];
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// Compute sum across the row
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barrier();
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[[unroll]] for (int s = int(gl_WorkGroupSize.x) / 2; s >= D_split; s >>= 1) {
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if (tid < s) {
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tmpsh[tid] = tmpsh[tid] + tmpsh[tid + s];
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}
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barrier();
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}
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Lf[r] = tmpsh[d_tid];
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barrier();
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[[unroll]] for (uint32_t d = 0; d < D_per_thread / 4; ++d) {
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Of[r][d] = eMf * Of[r][d];
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tmpshv4[tid] = Of[r][d];
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barrier();
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[[unroll]] for (int s = int(gl_WorkGroupSize.x) / 2; s >= D_split; s >>= 1) {
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if (tid < s) {
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Of[r][d] += tmpshv4[tid + s];
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tmpshv4[tid] = Of[r][d];
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}
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barrier();
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}
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Of[r][d] = tmpshv4[d_tid];
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barrier();
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}
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}
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// If there is split_k, then the split_k resolve shader does the final
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// division by L. Store the intermediate O value and per-row m and L values.
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if (p.k_num > 1) {
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uint32_t o_offset = D * p.ne1 * split_k_index;
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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if (r < N) {
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[[unroll]] for (uint32_t d = 0; d < D_per_thread / 4; ++d) {
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[[unroll]] for (uint32_t comp = 0; comp < 4; ++comp) {
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perElemOpGqaStore(r, 4*(d * D_split + d_tid) + comp, Of[r][d][comp], o_offset, iq2, N);
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}
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}
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}
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}
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o_offset = D * p.ne1 * p.k_num + p.ne1 * split_k_index * 2;
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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if (r < N) {
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perElemOpStoreCol0(r, 0u, ACC_TYPE(Lf[r]), o_offset, iq2, N);
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perElemOpStoreCol0(r, 0u, ACC_TYPE(Mf[r]), o_offset + p.ne1, iq2, N);
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}
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}
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return;
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}
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float Lfrcp[Br];
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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Lfrcp[r] = 1.0 / Lf[r];
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}
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[[unroll]] for (uint32_t d = 0; d < D_per_thread / 4; ++d) {
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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Of[r][d] *= Lfrcp[r];
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}
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}
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uint32_t o_offset = iq3*p.ne2*p.ne1;
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if (p.gqa_ratio > 1) {
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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if (r < N) {
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[[unroll]] for (uint32_t d = 0; d < D_per_thread / 4; ++d) {
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[[unroll]] for (uint32_t comp = 0; comp < 4; ++comp) {
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perElemOpGqaStore(r, 4*(d * D_split + d_tid) + comp, Of[r][d][comp], o_offset, iq2, N);
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}
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}
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}
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}
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} else {
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[[unroll]] for (uint32_t r = 0; r < Br; ++r) {
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if (i * Br + r < N) {
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[[unroll]] for (uint32_t d = 0; d < D_per_thread / 4; ++d) {
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[[unroll]] for (uint32_t comp = 0; comp < 4; ++comp) {
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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]);
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}
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}
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}
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}
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}
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}
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