mirror of
https://github.com/likelovewant/ollama-for-amd.git
synced 2025-12-21 22:33:56 +00:00
vulkan: temporary cary of vulkan fixes (#12971)
This should be reverted once we update ggml past b6897
This commit is contained in:
16
ml/backend/ggml/ggml/src/ggml-impl.h
vendored
16
ml/backend/ggml/ggml/src/ggml-impl.h
vendored
@@ -693,6 +693,7 @@ GGML_API void ggml_dxgi_pdh_release();
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#endif
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#ifdef __cplusplus
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#include <array>
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#include <initializer_list>
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#include <vector>
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@@ -708,6 +709,21 @@ inline bool ggml_can_fuse_subgraph(const struct ggml_cgraph * cgraph,
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return ggml_can_fuse_subgraph(cgraph, start_idx, ops.size(), ops.begin(), outputs.begin(), outputs.size());
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}
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// Return true if the edges in the graph match expectations.
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inline bool ggml_check_edges(const struct ggml_cgraph * cgraph,
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int start_idx,
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std::initializer_list<std::array<int, 3>> edges) {
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for (const auto & edge : edges) {
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int dst_node = edge[0];
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int src_idx = edge[1];
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int src_node = edge[2];
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if (cgraph->nodes[start_idx + dst_node]->src[src_idx] != cgraph->nodes[start_idx + src_node]) {
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return false;
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}
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}
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return true;
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}
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// expose GGUF internals for test code
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GGML_API size_t gguf_type_size(enum gguf_type type);
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GGML_API struct gguf_context * gguf_init_from_file_impl(FILE * file, struct gguf_init_params params);
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@@ -677,7 +677,7 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mm_id_map0(ggml_metal_
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char name[256];
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snprintf(base, 256, "kernel_mul_mm_id_map0_ne20_%d", ne20);
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snprintf(name, 256, "%s", base);
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snprintf(name, 256, "%s_ne02=%d", base, ne02);
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ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name);
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if (res) {
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830
ml/backend/ggml/ggml/src/ggml-vulkan/ggml-vulkan.cpp
vendored
830
ml/backend/ggml/ggml/src/ggml-vulkan/ggml-vulkan.cpp
vendored
File diff suppressed because it is too large
Load Diff
@@ -14,6 +14,7 @@ layout (binding = 1) buffer D {int data_d[];};
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layout (push_constant) uniform parameter {
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uint ncols;
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uint nrows;
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uint order;
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} p;
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@@ -26,10 +27,9 @@ void swap(uint idx0, uint idx1) {
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dst_row[idx1] = tmp;
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}
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void argsort(bool needs_bounds_check) {
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void argsort(bool needs_bounds_check, const uint row) {
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// bitonic sort
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const int col = int(gl_LocalInvocationID.x);
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const uint row = gl_WorkGroupID.y;
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const uint row_offset = row * p.ncols;
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@@ -72,8 +72,16 @@ void argsort(bool needs_bounds_check) {
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void main() {
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if (p.ncols == BLOCK_SIZE) {
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argsort(false);
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uint row = gl_WorkGroupID.y;
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while (row < p.nrows) {
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argsort(false, row);
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row += gl_WorkGroupSize.y * gl_NumWorkGroups.y;
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}
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} else {
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argsort(true);
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uint row = gl_WorkGroupID.y;
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while (row < p.nrows) {
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argsort(true, row);
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row += gl_WorkGroupSize.y * gl_NumWorkGroups.y;
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}
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}
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}
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@@ -437,7 +437,7 @@ vec4 dequantize4(uint ib, uint iqs, uint a_offset) {
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#if defined(DATA_A_MXFP4)
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vec2 dequantize(uint ib, uint iqs, uint a_offset) {
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const uint vui = uint(data_a[a_offset + ib].qs[iqs]);
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return vec2(kvalues_mxfp4[vui & 0xF], kvalues_mxfp4[vui >> 4]);
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return vec2(kvalues_mxfp4[vui & 0xF], kvalues_mxfp4[vui >> 4]) * 0.5;
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}
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vec4 dequantize4(uint ib, uint iqs, uint a_offset) {
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vec2 v0 = dequantize(ib, iqs, a_offset);
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@@ -488,9 +488,9 @@ vec2 dequantize(uint ib, uint iqs, uint a_offset) {
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const uvec2 qs = uvec2(data_a[a_offset + ib].qs[qsi], data_a[a_offset + ib].qs[qsi + 1]);
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const uint scales = data_a[a_offset + ib].scales[scalesi];
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const vec2 d = vec2(data_a[a_offset + ib].d);
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const vec2 dm = vec2(data_a[a_offset + ib].dm);
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return d.x * float(scales & 0xF) * vec2((qs >> qsshift) & 3) - d.y * float(scales >> 4);
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return dm.x * float(scales & 0xF) * vec2((qs >> qsshift) & 3) - dm.y * float(scales >> 4);
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}
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vec2 get_dm(uint ib, uint a_offset) {
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return vec2(1, 0);
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@@ -529,7 +529,7 @@ vec2 dequantize(uint ib, uint iqs, uint a_offset) {
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const uint is = 2 * n + b; // 0..7
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const uint qsi = n * 32 + (iqs % 16) * 2; // 0,2,4..126
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const vec2 loadd = vec2(data_a[a_offset + ib].d);
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const vec2 loadd = vec2(data_a[a_offset + ib].dm);
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const uint scidx0 = (is < 4) ? is : (is + 4);
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const uint scidx1 = (is < 4) ? is : (is - 4);
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@@ -567,7 +567,7 @@ vec2 dequantize(uint ib, uint iqs, uint a_offset) {
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const uint8_t hm = uint8_t(1 << (iqs / 16));
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const vec2 loadd = vec2(data_a[a_offset + ib].d);
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const vec2 loadd = vec2(data_a[a_offset + ib].dm);
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const uint scidx0 = (is < 4) ? is : (is + 4);
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const uint scidx1 = (is < 4) ? is : (is - 4);
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@@ -120,7 +120,7 @@ layout(buffer_reference, std430, buffer_reference_align = 16) buffer decodeBufQ2
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float16_t dequantFuncQ2_K(const in decodeBufQ2_K bl, const in uint blockCoords[2], const in uint coordInBlock[2])
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{
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decodeBufQ2_K_packed16 bl16 = decodeBufQ2_K_packed16(bl);
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const f16vec2 d = bl.block.d;
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const f16vec2 dm = bl.block.dm;
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const uint idx = coordInBlock[1];
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const uint scalesi = (idx & 0xF0) >> 4; // 0..15
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@@ -131,7 +131,7 @@ float16_t dequantFuncQ2_K(const in decodeBufQ2_K bl, const in uint blockCoords[2
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qs = unpack8(qs)[idx & 1];
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const uint scales = bl.block.scales[scalesi];
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float16_t ret = d.x * float16_t(scales & 0xF) * float16_t(qs) - d.y * float16_t(scales >> 4);
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float16_t ret = dm.x * float16_t(scales & 0xF) * float16_t(qs) - dm.y * float16_t(scales >> 4);
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return ret;
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}
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@@ -680,7 +680,7 @@ float16_t dequantFuncMXFP4(const in decodeBufMXFP4 bl, const in uint blockCoords
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uint32_t qs = bl.block.qs[iqs];
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qs >>= shift;
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qs &= 0xF;
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float16_t ret = float16_t(kvalues_mxfp4[qs] * d);
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float16_t ret = float16_t(kvalues_mxfp4[qs] * d * 0.5);
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return ret;
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}
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#endif
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@@ -26,7 +26,7 @@ void main() {
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const float d = e8m0_to_fp32(data_a[ib].e);
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[[unroll]] for (uint l = 0; l < 8; ++l) {
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data_b[b_idx + l + 0] = D_TYPE(d * kvalues_mxfp4[data_a[ib].qs[q_idx + l] & 0xF]);
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data_b[b_idx + l + 16] = D_TYPE(d * kvalues_mxfp4[data_a[ib].qs[q_idx + l] >> 4]);
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data_b[b_idx + l + 0] = D_TYPE(d * 0.5 * float(kvalues_mxfp4[data_a[ib].qs[q_idx + l] & 0xF]));
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data_b[b_idx + l + 16] = D_TYPE(d * 0.5 * float(kvalues_mxfp4[data_a[ib].qs[q_idx + l] >> 4]));
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}
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}
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@@ -24,8 +24,8 @@ void main() {
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const uint ql_idx = 32 * ip + il;
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const uint8_t qs = data_a[i].qs[32 * ip + il];
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FLOAT_TYPE dall = FLOAT_TYPE(data_a[i].d.x);
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FLOAT_TYPE dmin = FLOAT_TYPE(data_a[i].d.y);
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FLOAT_TYPE dall = FLOAT_TYPE(data_a[i].dm.x);
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FLOAT_TYPE dmin = FLOAT_TYPE(data_a[i].dm.y);
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data_b[y_idx + 0] = D_TYPE(dall * FLOAT_TYPE((data_a[i].scales[is+0] & 0xF) * ((qs >> 0) & 3)) - dmin * FLOAT_TYPE(data_a[i].scales[is+0] >> 4));
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data_b[y_idx + 32] = D_TYPE(dall * FLOAT_TYPE((data_a[i].scales[is+2] & 0xF) * ((qs >> 2) & 3)) - dmin * FLOAT_TYPE(data_a[i].scales[is+2] >> 4));
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data_b[y_idx + 64] = D_TYPE(dall * FLOAT_TYPE((data_a[i].scales[is+4] & 0xF) * ((qs >> 4) & 3)) - dmin * FLOAT_TYPE(data_a[i].scales[is+4] >> 4));
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@@ -20,8 +20,8 @@ void main() {
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const uint is = 2 * il;
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const uint n = 4;
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const FLOAT_TYPE dall = FLOAT_TYPE(data_a[ib].d.x);
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const FLOAT_TYPE dmin = FLOAT_TYPE(data_a[ib].d.y);
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const FLOAT_TYPE dall = FLOAT_TYPE(data_a[ib].dm.x);
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const FLOAT_TYPE dmin = FLOAT_TYPE(data_a[ib].dm.y);
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const uint y_idx = ib * QUANT_K + 64 * il + n * ir;
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const uint qs_idx = 32*il + n * ir;
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@@ -19,8 +19,8 @@ void main() {
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const uint ir = tid % 16;
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const uint is = 2 * il;
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const FLOAT_TYPE dall = FLOAT_TYPE(data_a[ib].d.x);
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const FLOAT_TYPE dmin = FLOAT_TYPE(data_a[ib].d.y);
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const FLOAT_TYPE dall = FLOAT_TYPE(data_a[ib].dm.x);
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const FLOAT_TYPE dmin = FLOAT_TYPE(data_a[ib].dm.y);
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const uint y_idx = ib * QUANT_K + 64 * il + 2 * ir;
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const uint qs_idx = 32*il + 2 * ir;
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@@ -41,9 +41,7 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint itid,
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const vec4 qs_u32_4 = vec4(unpack8((qs_u32 >> 4) & 0x03030303));
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const vec4 qs_u32_6 = vec4(unpack8((qs_u32 >> 6) & 0x03030303));
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vec2 d = vec2(data_a[ib0 + i].d);
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const FLOAT_TYPE dall = FLOAT_TYPE(d.x);
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const FLOAT_TYPE dmin = FLOAT_TYPE(d.y);
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const FLOAT_TYPE_VEC2 dm = vec2(data_a[ib0 + i].dm);
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[[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
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vec2 b0 = vec2(data_b_v2[(j*p.batch_stride_b + b_offset + y_idx) / 2 + 0]);
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@@ -75,7 +73,7 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint itid,
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fma(FLOAT_TYPE(b96[l]), sccache2[csel][ix][6 + 8*v_im],
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fma(FLOAT_TYPE(b112[l]), sccache2[csel][ix][7 + 8*v_im], sum2))))))));
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}
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temp[j][n] = fma(dall, sum1, fma(-dmin, sum2, temp[j][n]));
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temp[j][n] = fma(dm.x, sum1, fma(-dm.y, sum2, temp[j][n]));
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}
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}
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}
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@@ -14,9 +14,7 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint v_im,
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[[unroll]] for (uint n = 0; n < num_rows; ++n) {
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const uint ib0 = a_offset / QUANT_K + (first_row+n)*num_blocks_per_row;
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vec2 d = vec2(data_a[ib0 + i].d);
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const FLOAT_TYPE dall = FLOAT_TYPE(d.x);
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const FLOAT_TYPE dmin = FLOAT_TYPE(d.y);
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const FLOAT_TYPE_VEC2 dm = FLOAT_TYPE_VEC2(data_a[ib0 + i].dm);
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const uint32_t scale0_u32 = data_a_packed16[ib0 + i].scales[v_im ];
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const uint32_t scale4_u32 = data_a_packed16[ib0 + i].scales[v_im + 2];
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@@ -81,7 +79,7 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint v_im,
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fma(FLOAT_TYPE(by10.y), sc2, fma(FLOAT_TYPE(by132.y), sc3, fma(FLOAT_TYPE(by20.y), sc6, fma(FLOAT_TYPE(by232.y), sc7,
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fma(FLOAT_TYPE(by10.z), sc2, fma(FLOAT_TYPE(by132.z), sc3, fma(FLOAT_TYPE(by20.z), sc6, fma(FLOAT_TYPE(by232.z), sc7,
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fma(FLOAT_TYPE(by10.w), sc2, fma(FLOAT_TYPE(by132.w), sc3, fma(FLOAT_TYPE(by20.w), sc6, FLOAT_TYPE(by232.w) * sc7)))))))))))))));
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temp[j][n] = fma(dall, fma(sx, sc0, fma(sy, sc1, fma(sz, sc4, sw * sc5))), fma(-dmin, smin, temp[j][n]));
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temp[j][n] = fma(dm.x, fma(sx, sc0, fma(sy, sc1, fma(sz, sc4, sw * sc5))), fma(-dm.y, smin, temp[j][n]));
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}
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}
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}
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@@ -14,9 +14,7 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint v_im,
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[[unroll]] for (uint n = 0; n < num_rows; ++n) {
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const uint ib0 = a_offset / QUANT_K + (first_row+n)*num_blocks_per_row;
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vec2 d = vec2(data_a[ib0 + i].d);
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const FLOAT_TYPE dall = FLOAT_TYPE(d.x);
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const FLOAT_TYPE dmin = FLOAT_TYPE(d.y);
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const FLOAT_TYPE_VEC2 dm = FLOAT_TYPE_VEC2(data_a[ib0 + i].dm);
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const uint32_t scale0_u32 = data_a_packed16[ib0 + i].scales[v_im ];
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const uint32_t scale4_u32 = data_a_packed16[ib0 + i].scales[v_im + 2];
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@@ -113,7 +111,7 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint v_im,
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fma(FLOAT_TYPE(by132.x) + FLOAT_TYPE(by132.y) + FLOAT_TYPE(by148.x) + FLOAT_TYPE(by148.y), sc3,
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fma(FLOAT_TYPE(by20.x) + FLOAT_TYPE(by20.y) + FLOAT_TYPE(by216.x) + FLOAT_TYPE(by216.y), sc6,
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(FLOAT_TYPE(by232.x) + FLOAT_TYPE(by232.y) + FLOAT_TYPE(by248.x) + FLOAT_TYPE(by248.y)) * sc7)));
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temp[j][n] = fma(dall, fma(sx, sc0, fma(sy, sc1, fma(sz, sc4, sw * sc5))), fma(-dmin, smin, temp[j][n]));
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temp[j][n] = fma(dm.x, fma(sx, sc0, fma(sy, sc1, fma(sz, sc4, sw * sc5))), fma(-dm.y, smin, temp[j][n]));
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}
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}
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}
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@@ -120,81 +120,11 @@ shared FLOAT_TYPE_VEC2 buf_b[BN * SHMEM_STRIDE];
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#define NUM_WARPS (BLOCK_SIZE / WARP)
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#ifdef MUL_MAT_ID
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shared u16vec2 row_ids[BN];
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uint _ne1;
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#ifdef MUL_MAT_ID_USE_SUBGROUPS
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shared uvec4 ballots_sh[NUM_WARPS];
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void load_row_ids(uint expert_idx, bool nei0_is_pow2, uint ic) {
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_ne1 = 0;
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uint num_elements = p.nei1 * p.nei0;
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uint nei0shift = findLSB(p.nei0);
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uint ids[16];
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uint iter = 0;
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for (uint j = 0; j < num_elements; j += BLOCK_SIZE) {
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// prefetch up to 16 elements
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if (iter == 0) {
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[[unroll]] for (uint k = 0; k < 16; ++k) {
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uint i = j + gl_LocalInvocationIndex + k*BLOCK_SIZE;
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bool in_range = i < num_elements;
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uint ii1;
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if (nei0_is_pow2) {
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ii1 = i >> nei0shift;
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} else {
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ii1 = i / p.nei0;
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}
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uint ii0 = i - ii1 * p.nei0;
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ids[k] = in_range ? data_ids[ii1*p.nbi1 + ii0] : 0;
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}
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}
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uint i = j + gl_LocalInvocationIndex;
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bool in_range = i < num_elements;
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uint ii1;
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if (nei0_is_pow2) {
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ii1 = i >> nei0shift;
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} else {
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ii1 = i / p.nei0;
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}
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uint ii0 = i - ii1 * p.nei0;
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uint id = ids[iter++];
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uvec4 ballot = subgroupBallot(in_range && id == expert_idx);
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ballots_sh[gl_SubgroupID] = ballot;
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barrier();
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uint subgroup_base = 0;
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uint total = 0;
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for (uint k = 0; k < gl_NumSubgroups; ++k) {
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if (k == gl_SubgroupID) {
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subgroup_base = total;
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}
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total += subgroupBallotBitCount(ballots_sh[k]);
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}
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barrier();
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uint idx = subgroup_base + subgroupBallotExclusiveBitCount(ballot);
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if (in_range && id == expert_idx && _ne1 + idx >= ic * BN && _ne1 + idx < (ic + 1) * BN) {
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row_ids[_ne1 + idx - ic * BN] = u16vec2(ii0, ii1);
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}
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_ne1 += total;
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iter &= 15;
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if (_ne1 >= (ic + 1) * BN) {
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break;
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}
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}
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barrier();
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||||
}
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#endif // MUL_MAT_ID_USE_SUBGROUPS
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#endif // MUL_MAT_ID
|
||||
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#ifdef COOPMAT
|
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shared ACC_TYPE coopmat_stage[TM * TN * NUM_WARPS];
|
||||
#endif
|
||||
|
||||
#include "mul_mm_id_funcs.glsl"
|
||||
#include "mul_mm_funcs.glsl"
|
||||
|
||||
void main() {
|
||||
|
||||
@@ -134,15 +134,15 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
|
||||
const uint ib = idx / 128; // 2 values per idx
|
||||
const uint iqs = idx % 128; // 0..127
|
||||
|
||||
const uint qsi = (iqs / 64) * 32 + (iqs % 16) * 2; // 0,2,4..30
|
||||
const uint qsi = (iqs / 64) * 16 + (iqs % 16); // 0..15
|
||||
const uint scalesi = iqs / 8; // 0..15
|
||||
const uint qsshift = ((iqs % 64) / 16) * 2; // 0,2,4,6
|
||||
|
||||
const uvec2 qs = uvec2(data_a[ib].qs[qsi], data_a[ib].qs[qsi + 1]);
|
||||
const uvec2 qs = uvec2(unpack8(data_a_packed16[ib].qs[qsi]));
|
||||
const uint scales = data_a[ib].scales[scalesi];
|
||||
const vec2 d = vec2(data_a[ib].d);
|
||||
const vec2 dm = vec2(data_a[ib].dm);
|
||||
|
||||
const vec2 v = d.x * float(scales & 0xF) * vec2((qs >> qsshift) & 3) - d.y * float(scales >> 4);
|
||||
const vec2 v = dm.x * float(scales & 0xF) * vec2((qs >> qsshift) & 3) - dm.y * float(scales >> 4);
|
||||
|
||||
buf_a[buf_idx] = FLOAT_TYPE_VEC2(v.xy);
|
||||
#elif defined(DATA_A_Q3_K)
|
||||
@@ -179,7 +179,7 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
|
||||
const uint is = 2 * n + b; // 0..7
|
||||
const uint qsi = n * 32 + (iqs % 16) * 2; // 0,2,4..126
|
||||
|
||||
const vec2 loadd = vec2(data_a[ib].d);
|
||||
const vec2 loadd = vec2(data_a[ib].dm);
|
||||
|
||||
const uint scidx0 = (is < 4) ? is : (is + 4);
|
||||
const uint scidx1 = (is < 4) ? is : (is - 4);
|
||||
@@ -215,7 +215,7 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
|
||||
|
||||
const uint8_t hm = uint8_t(1 << (iqs / 16));
|
||||
|
||||
const vec2 loadd = vec2(data_a[ib].d);
|
||||
const vec2 loadd = vec2(data_a[ib].dm);
|
||||
|
||||
const uint scidx0 = (is < 4) ? is : (is + 4);
|
||||
const uint scidx1 = (is < 4) ? is : (is - 4);
|
||||
@@ -468,7 +468,7 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
|
||||
const uint ib = idx / 8;
|
||||
const uint iqs = (idx & 0x07) * 2;
|
||||
|
||||
const float d = e8m0_to_fp32(data_a[ib].e);
|
||||
const float d = e8m0_to_fp32(data_a[ib].e) * 0.5;
|
||||
const uint vui = uint(data_a[ib].qs[iqs]);
|
||||
const uint vui2 = uint(data_a[ib].qs[iqs+1]);
|
||||
|
||||
|
||||
@@ -0,0 +1,70 @@
|
||||
#ifdef MUL_MAT_ID
|
||||
shared u16vec2 row_ids[BN];
|
||||
uint _ne1;
|
||||
|
||||
#ifdef MUL_MAT_ID_USE_SUBGROUPS
|
||||
shared uvec4 ballots_sh[NUM_WARPS];
|
||||
|
||||
void load_row_ids(uint expert_idx, bool nei0_is_pow2, uint ic) {
|
||||
_ne1 = 0;
|
||||
uint num_elements = p.nei1 * p.nei0;
|
||||
uint nei0shift = findLSB(p.nei0);
|
||||
|
||||
uint ids[16];
|
||||
uint iter = 0;
|
||||
|
||||
for (uint j = 0; j < num_elements; j += BLOCK_SIZE) {
|
||||
// prefetch up to 16 elements
|
||||
if (iter == 0) {
|
||||
[[unroll]] for (uint k = 0; k < 16; ++k) {
|
||||
uint i = j + gl_LocalInvocationIndex + k*BLOCK_SIZE;
|
||||
bool in_range = i < num_elements;
|
||||
uint ii1;
|
||||
if (nei0_is_pow2) {
|
||||
ii1 = i >> nei0shift;
|
||||
} else {
|
||||
ii1 = i / p.nei0;
|
||||
}
|
||||
uint ii0 = i - ii1 * p.nei0;
|
||||
ids[k] = in_range ? data_ids[ii1*p.nbi1 + ii0] : 0;
|
||||
}
|
||||
}
|
||||
uint i = j + gl_LocalInvocationIndex;
|
||||
bool in_range = i < num_elements;
|
||||
uint ii1;
|
||||
if (nei0_is_pow2) {
|
||||
ii1 = i >> nei0shift;
|
||||
} else {
|
||||
ii1 = i / p.nei0;
|
||||
}
|
||||
uint ii0 = i - ii1 * p.nei0;
|
||||
uint id = ids[iter++];
|
||||
uvec4 ballot = subgroupBallot(in_range && id == expert_idx);
|
||||
|
||||
ballots_sh[gl_SubgroupID] = ballot;
|
||||
barrier();
|
||||
|
||||
uint subgroup_base = 0;
|
||||
uint total = 0;
|
||||
for (uint k = 0; k < gl_NumSubgroups; ++k) {
|
||||
if (k == gl_SubgroupID) {
|
||||
subgroup_base = total;
|
||||
}
|
||||
total += subgroupBallotBitCount(ballots_sh[k]);
|
||||
}
|
||||
barrier();
|
||||
|
||||
uint idx = subgroup_base + subgroupBallotExclusiveBitCount(ballot);
|
||||
if (in_range && id == expert_idx && _ne1 + idx >= ic * BN && _ne1 + idx < (ic + 1) * BN) {
|
||||
row_ids[_ne1 + idx - ic * BN] = u16vec2(ii0, ii1);
|
||||
}
|
||||
_ne1 += total;
|
||||
iter &= 15;
|
||||
if (_ne1 >= (ic + 1) * BN) {
|
||||
break;
|
||||
}
|
||||
}
|
||||
barrier();
|
||||
}
|
||||
#endif // MUL_MAT_ID_USE_SUBGROUPS
|
||||
#endif // MUL_MAT_ID
|
||||
@@ -10,10 +10,9 @@
|
||||
#extension GL_EXT_shader_explicit_arithmetic_types_float16 : require
|
||||
#endif
|
||||
|
||||
#ifdef COOPMAT
|
||||
#extension GL_KHR_cooperative_matrix : enable
|
||||
#extension GL_KHR_memory_scope_semantics : enable
|
||||
#if defined(MUL_MAT_ID_USE_SUBGROUPS)
|
||||
#extension GL_KHR_shader_subgroup_basic : enable
|
||||
#extension GL_KHR_shader_subgroup_ballot : enable
|
||||
#endif
|
||||
|
||||
#ifdef MUL_MAT_ID
|
||||
@@ -24,7 +23,10 @@
|
||||
|
||||
layout(local_size_x_id = 0, local_size_y = 1, local_size_z = 1) in;
|
||||
|
||||
layout (binding = 0) readonly buffer A {A_TYPE_PACKED16 data_a[];};
|
||||
layout (binding = 0) readonly buffer A {A_TYPE data_a[];};
|
||||
#if defined(A_TYPE_PACKED16)
|
||||
layout (binding = 0) readonly buffer A_PACKED16 {A_TYPE_PACKED16 data_a_packed16[];};
|
||||
#endif
|
||||
#if defined(A_TYPE_PACKED32)
|
||||
layout (binding = 0) readonly buffer A_PACKED32 {A_TYPE_PACKED32 data_a_packed32[];};
|
||||
#endif
|
||||
@@ -76,40 +78,31 @@ layout (constant_id = 10) const uint WARP = 32;
|
||||
|
||||
#define BK 32
|
||||
|
||||
#ifdef COOPMAT
|
||||
#define SHMEM_STRIDE (BK / 4 + 4)
|
||||
#else
|
||||
#define SHMEM_STRIDE (BK / 4 + 1)
|
||||
#endif
|
||||
#define MMQ_SHMEM
|
||||
|
||||
shared int32_t buf_a_qs[BM * SHMEM_STRIDE];
|
||||
|
||||
#ifndef COOPMAT
|
||||
#if QUANT_AUXF == 1
|
||||
shared FLOAT_TYPE buf_a_dm[BM];
|
||||
#else
|
||||
shared FLOAT_TYPE_VEC2 buf_a_dm[BM];
|
||||
#endif
|
||||
#endif
|
||||
|
||||
shared int32_t buf_b_qs[BN * SHMEM_STRIDE];
|
||||
#ifndef COOPMAT
|
||||
shared FLOAT_TYPE_VEC2 buf_b_ds[BN];
|
||||
#endif
|
||||
|
||||
#define LOAD_VEC_A (4 * QUANT_R)
|
||||
#define LOAD_VEC_B 16
|
||||
#include "mul_mmq_shmem_types.glsl"
|
||||
|
||||
#ifdef MUL_MAT_ID
|
||||
shared u16vec2 row_ids[4096];
|
||||
#endif // MUL_MAT_ID
|
||||
#define BK_STEP 1
|
||||
#else
|
||||
#ifndef BK_STEP
|
||||
#define BK_STEP 4
|
||||
#endif
|
||||
#endif
|
||||
|
||||
// Shared memory cache
|
||||
shared block_a_cache buf_a[BM * BK_STEP];
|
||||
shared block_b_cache buf_b[BN * BK_STEP];
|
||||
// Register cache
|
||||
block_a_cache cache_a[WMITER * TM];
|
||||
block_b_cache cache_b;
|
||||
|
||||
#define LOAD_VEC_A (4 * QUANT_R_MMQ)
|
||||
#define LOAD_VEC_B 16
|
||||
|
||||
#define NUM_WARPS (BLOCK_SIZE / WARP)
|
||||
|
||||
#ifdef COOPMAT
|
||||
shared ACC_TYPE coopmat_stage[TM * TN * NUM_WARPS];
|
||||
#endif
|
||||
|
||||
#include "mul_mm_id_funcs.glsl"
|
||||
#include "mul_mmq_funcs.glsl"
|
||||
|
||||
void main() {
|
||||
@@ -139,26 +132,12 @@ void main() {
|
||||
const uint WNITER = (WM * WN) / (WARP * TM * TN * WMITER);
|
||||
const uint WSUBM = WM / WMITER;
|
||||
const uint WSUBN = WN / WNITER;
|
||||
|
||||
#ifdef COOPMAT
|
||||
const uint warp_i = gl_SubgroupID;
|
||||
|
||||
const uint tiw = gl_SubgroupInvocationID;
|
||||
|
||||
const uint cms_per_row = WM / TM;
|
||||
const uint cms_per_col = WN / TN;
|
||||
|
||||
const uint storestride = WARP / TM;
|
||||
const uint store_r = tiw % TM;
|
||||
const uint store_c = tiw / TM;
|
||||
#else
|
||||
const uint warp_i = gl_LocalInvocationID.x / WARP;
|
||||
|
||||
const uint tiw = gl_LocalInvocationID.x % WARP;
|
||||
|
||||
const uint tiwr = tiw % (WSUBM / TM);
|
||||
const uint tiwc = tiw / (WSUBM / TM);
|
||||
#endif
|
||||
|
||||
const uint warp_r = warp_i % (BM / WM);
|
||||
const uint warp_c = warp_i / (BM / WM);
|
||||
@@ -172,17 +151,27 @@ void main() {
|
||||
const uint loadstride_b = BLOCK_SIZE * LOAD_VEC_B / BK;
|
||||
|
||||
#ifdef MUL_MAT_ID
|
||||
uint _ne1 = 0;
|
||||
for (uint ii1 = 0; ii1 < p.nei1; ii1++) {
|
||||
for (uint ii0 = 0; ii0 < p.nei0; ii0++) {
|
||||
#ifdef MUL_MAT_ID_USE_SUBGROUPS
|
||||
if (bitCount(p.nei0) == 1) {
|
||||
load_row_ids(expert_idx, true, ic);
|
||||
} else {
|
||||
load_row_ids(expert_idx, false, ic);
|
||||
}
|
||||
#else
|
||||
_ne1 = 0;
|
||||
for (uint ii1 = 0; ii1 < p.nei1 && _ne1 < (ic + 1) * BN; ii1++) {
|
||||
for (uint ii0 = 0; ii0 < p.nei0 && _ne1 < (ic + 1) * BN; ii0++) {
|
||||
if (data_ids[ii1*p.nbi1 + ii0] == expert_idx) {
|
||||
row_ids[_ne1] = u16vec2(ii0, ii1);
|
||||
if (_ne1 >= ic * BN) {
|
||||
row_ids[_ne1 - ic * BN] = u16vec2(ii0, ii1);
|
||||
}
|
||||
_ne1++;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
barrier();
|
||||
#endif
|
||||
|
||||
// Workgroup has no work
|
||||
if (ic * BN >= _ne1) return;
|
||||
@@ -209,159 +198,70 @@ void main() {
|
||||
uint pos_b_ib = (batch_idx * p.batch_stride_b + ic * BN * p.stride_b + start_k) / BK;
|
||||
#endif
|
||||
|
||||
#ifdef COOPMAT
|
||||
coopmat<int8_t, gl_ScopeSubgroup, TM, TK, gl_MatrixUseA> cache_a;
|
||||
coopmat<int8_t, gl_ScopeSubgroup, TK, TN, gl_MatrixUseB> cache_b;
|
||||
coopmat<int32_t, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator> cm_result;
|
||||
|
||||
coopmat<ACC_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator> factors[cms_per_row * cms_per_col];
|
||||
|
||||
coopmat<ACC_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator> sums[cms_per_row * cms_per_col];
|
||||
|
||||
[[unroll]] for (uint i = 0; i < cms_per_row * cms_per_col; i++) {
|
||||
sums[i] = coopmat<ACC_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator>(0.0f);
|
||||
}
|
||||
#else
|
||||
int32_t cache_a_qs[WMITER * TM * BK / 4];
|
||||
|
||||
int32_t cache_b_qs[TN * BK / 4];
|
||||
|
||||
ACC_TYPE sums[WMITER * TM * WNITER * TN];
|
||||
|
||||
[[unroll]] for (uint i = 0; i < WMITER*TM*WNITER*TN; i++) {
|
||||
sums[i] = ACC_TYPE(0.0f);
|
||||
}
|
||||
#endif
|
||||
|
||||
#if QUANT_AUXF == 1
|
||||
FLOAT_TYPE cache_a_dm[WMITER * TM];
|
||||
#else
|
||||
FLOAT_TYPE_VEC2 cache_a_dm[WMITER * TM];
|
||||
#endif
|
||||
|
||||
FLOAT_TYPE_VEC2 cache_b_ds[TN];
|
||||
|
||||
for (uint block = start_k; block < end_k; block += BK) {
|
||||
for (uint block = start_k; block < end_k; block += BK * BK_STEP) {
|
||||
[[unroll]] for (uint l = 0; loadc_a + l < BM; l += loadstride_a) {
|
||||
const uint ib = pos_a_ib + (loadc_a + l) * p.stride_a / BK;
|
||||
const uint iqs = loadr_a;
|
||||
const uint buf_ib = loadc_a + l;
|
||||
const uint ib = pos_a_ib + buf_ib * p.stride_a / BK;
|
||||
const uint iqs = loadr_a;
|
||||
|
||||
if (iqs == 0) {
|
||||
#if QUANT_AUXF == 1
|
||||
buf_a_dm[buf_ib] = get_d(ib);
|
||||
#else
|
||||
buf_a_dm[buf_ib] = get_dm(ib);
|
||||
#endif
|
||||
[[unroll]] for (uint k_step = 0; k_step < BK_STEP; k_step++) {
|
||||
block_a_to_shmem(k_step * BM + buf_ib, ib + k_step, iqs);
|
||||
}
|
||||
#if QUANT_R == 1
|
||||
buf_a_qs[buf_ib * SHMEM_STRIDE + iqs] = repack(ib, iqs);
|
||||
#else
|
||||
const i32vec2 vals = repack(ib, iqs);
|
||||
buf_a_qs[buf_ib * SHMEM_STRIDE + iqs ] = vals.x;
|
||||
buf_a_qs[buf_ib * SHMEM_STRIDE + iqs + 4] = vals.y;
|
||||
#endif
|
||||
}
|
||||
[[unroll]] for (uint l = 0; loadc_b + l < BN; l += loadstride_b) {
|
||||
#ifdef MUL_MAT_ID
|
||||
const u16vec2 row_idx = row_ids[ic * BN + loadc_b + l];
|
||||
const uint idx = pos_b_ib + row_idx.y * p.batch_stride_b / LOAD_VEC_B + (row_idx.x % p.ne11) * p.stride_b / LOAD_VEC_B + loadr_b;
|
||||
const uint ib = idx / 8;
|
||||
const uint iqs = idx & 0x7;
|
||||
#else
|
||||
const uint ib = pos_b_ib + (loadc_b + l) * p.stride_b / BK;
|
||||
const uint ib_outer = ib / 4;
|
||||
const uint ib_inner = ib % 4;
|
||||
|
||||
const uint iqs = loadr_b;
|
||||
#endif
|
||||
|
||||
const uint buf_ib = loadc_b + l;
|
||||
|
||||
if (iqs == 0) {
|
||||
buf_b_ds[buf_ib] = FLOAT_TYPE_VEC2(data_b[ib_outer].ds[ib_inner]);
|
||||
#ifdef MUL_MAT_ID
|
||||
const u16vec2 row_idx = row_ids[buf_ib];
|
||||
const uint ib = pos_b_ib + row_idx.y * p.batch_stride_b / BK + (row_idx.x % p.ne11) * p.stride_b / BK;
|
||||
#else
|
||||
const uint ib = pos_b_ib + buf_ib * p.stride_b / BK;
|
||||
#endif
|
||||
const uint iqs = loadr_b;
|
||||
|
||||
[[unroll]] for (uint k_step = 0; k_step < BK_STEP; k_step++) {
|
||||
block_b_to_shmem(k_step * BN + buf_ib, ib + k_step, iqs);
|
||||
}
|
||||
const ivec4 values = data_b[ib_outer].qs[ib_inner * 2 + iqs];
|
||||
buf_b_qs[buf_ib * SHMEM_STRIDE + iqs * 4 ] = values.x;
|
||||
buf_b_qs[buf_ib * SHMEM_STRIDE + iqs * 4 + 1] = values.y;
|
||||
buf_b_qs[buf_ib * SHMEM_STRIDE + iqs * 4 + 2] = values.z;
|
||||
buf_b_qs[buf_ib * SHMEM_STRIDE + iqs * 4 + 3] = values.w;
|
||||
}
|
||||
|
||||
barrier();
|
||||
|
||||
pos_a_ib += 1;
|
||||
pos_b_ib += 1;
|
||||
pos_a_ib += BK_STEP;
|
||||
pos_b_ib += BK_STEP;
|
||||
|
||||
#ifdef COOPMAT
|
||||
[[unroll]] for (uint cm_row = 0; cm_row < cms_per_row; cm_row++) {
|
||||
const uint ib_a = warp_r * WM + cm_row * TM;
|
||||
for (uint k_step = 0; k_step < BK_STEP; k_step++) {
|
||||
// Load from shared into cache
|
||||
coopMatLoad(cache_a, buf_a_qs, ib_a * SHMEM_STRIDE, SHMEM_STRIDE, gl_CooperativeMatrixLayoutRowMajor);
|
||||
|
||||
// TODO: only cache values that are actually needed
|
||||
[[unroll]] for (uint t_idx = 0; t_idx < TM; t_idx++) {
|
||||
cache_a_dm[t_idx] = buf_a_dm[ib_a + t_idx];
|
||||
}
|
||||
|
||||
[[unroll]] for (uint cm_col = 0; cm_col < cms_per_col; cm_col++) {
|
||||
const uint ib_b = warp_c * WN + cm_col * TN;
|
||||
coopMatLoad(cache_b, buf_b_qs, ib_b * SHMEM_STRIDE, SHMEM_STRIDE, gl_CooperativeMatrixLayoutColumnMajor);
|
||||
|
||||
// TODO: only cache values that are actually needed
|
||||
[[unroll]] for (uint t_idx = 0; t_idx < TN; t_idx++) {
|
||||
cache_b_dm[t_idx] = buf_b_d[ib_b + t_idx];
|
||||
}
|
||||
|
||||
cm_result = coopmat<int32_t, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator>(0);
|
||||
cm_result = coopMatMulAdd(cache_a, cache_b, cm_result);
|
||||
|
||||
[[unroll]] for (uint col = 0; col < TN; col += storestride) {
|
||||
coopmat_stage[warp_i * TM * TN + (store_c + col) * TM + store_r] = ACC_TYPE(float(cache_a_d[store_r]) * float(cache_b_d[store_c + col]));
|
||||
}
|
||||
|
||||
coopMatLoad(factors, coopmat_stage, warp_i * TM * TN, TM, gl_CooperativeMatrixLayoutColumnMajor);
|
||||
sums[cm_col * cms_per_row + cm_row] += factors * coopmat<ACC_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator>(cm_result);
|
||||
}
|
||||
}
|
||||
#else
|
||||
// Load from shared into cache
|
||||
[[unroll]] for (uint wsir = 0; wsir < WMITER; wsir++) {
|
||||
[[unroll]] for (uint cr = 0; cr < TM; cr++) {
|
||||
const uint ib = warp_r * WM + wsir * WSUBM + tiwr * TM + cr;
|
||||
cache_a_dm[wsir * TM + cr] = buf_a_dm[ib];
|
||||
[[unroll]] for (uint idx_k = 0; idx_k < BK / 4; idx_k++) {
|
||||
cache_a_qs[(wsir * TM + cr) * (BK / 4) + idx_k] = buf_a_qs[ib * SHMEM_STRIDE + idx_k];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
[[unroll]] for (uint wsic = 0; wsic < WNITER; wsic++) {
|
||||
[[unroll]] for (uint cc = 0; cc < TN; cc++) {
|
||||
const uint ib = warp_c * WN + wsic * WSUBN + tiwc * TN + cc;
|
||||
cache_b_ds[cc] = buf_b_ds[ib];
|
||||
[[unroll]] for (uint idx_k = 0; idx_k < BK / 4; idx_k++) {
|
||||
cache_b_qs[cc * (BK / 4) + idx_k] = buf_b_qs[ib * SHMEM_STRIDE + idx_k];
|
||||
}
|
||||
}
|
||||
|
||||
[[unroll]] for (uint wsir = 0; wsir < WMITER; wsir++) {
|
||||
[[unroll]] for (uint cc = 0; cc < TN; cc++) {
|
||||
[[unroll]] for (uint cr = 0; cr < TM; cr++) {
|
||||
const uint cache_a_idx = wsir * TM + cr;
|
||||
const uint sums_idx = (wsic * TN + cc) * (WMITER * TM) + wsir * TM + cr;
|
||||
int32_t q_sum = 0;
|
||||
[[unroll]] for (uint idx_k = 0; idx_k < BK / 4; idx_k++) {
|
||||
q_sum += dotPacked4x8EXT(cache_a_qs[cache_a_idx * (BK / 4) + idx_k],
|
||||
cache_b_qs[cc * (BK / 4) + idx_k]);
|
||||
}
|
||||
[[unroll]] for (uint cr = 0; cr < TM; cr++) {
|
||||
const uint reg_ib = wsir * TM + cr;
|
||||
const uint buf_ib = warp_r * WM + wsir * WSUBM + tiwr * TM + cr;
|
||||
|
||||
sums[sums_idx] += mul_q8_1(q_sum, cache_a_dm[cache_a_idx], cache_b_ds[cc], 1);
|
||||
block_a_to_registers(reg_ib, k_step * BM + buf_ib);
|
||||
}
|
||||
}
|
||||
|
||||
[[unroll]] for (uint wsic = 0; wsic < WNITER; wsic++) {
|
||||
[[unroll]] for (uint cc = 0; cc < TN; cc++) {
|
||||
const uint ib = k_step * BN + warp_c * WN + wsic * WSUBN + tiwc * TN + cc;
|
||||
block_b_to_registers(ib);
|
||||
|
||||
[[unroll]] for (uint wsir = 0; wsir < WMITER; wsir++) {
|
||||
[[unroll]] for (uint cr = 0; cr < TM; cr++) {
|
||||
const uint cache_a_idx = wsir * TM + cr;
|
||||
const uint sums_idx = (wsic * TN + cc) * (WMITER * TM) + wsir * TM + cr;
|
||||
|
||||
sums[sums_idx] += mmq_dot_product(cache_a_idx);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
#endif
|
||||
|
||||
barrier();
|
||||
}
|
||||
@@ -373,54 +273,6 @@ void main() {
|
||||
const uint offsets = batch_idx * p.batch_stride_d + ik * p.batch_stride_d * gl_NumWorkGroups.z;
|
||||
#endif
|
||||
|
||||
#ifdef COOPMAT
|
||||
#ifdef MUL_MAT_ID
|
||||
[[unroll]] for (uint cm_row = 0; cm_row < cms_per_row; cm_row++) {
|
||||
[[unroll]] for (uint cm_col = 0; cm_col < cms_per_col; cm_col++) {
|
||||
coopMatStore(sums[cm_col * cms_per_row + cm_row], coopmat_stage, warp_i * TM * TN, TM, gl_CooperativeMatrixLayoutColumnMajor);
|
||||
|
||||
[[unroll]] for (uint col = 0; col < BN; col += storestride) {
|
||||
const uint row_i = dc + cm_col * TN + col + store_c;
|
||||
if (row_i >= _ne1) break;
|
||||
|
||||
const u16vec2 row_idx = row_ids[row_i];
|
||||
|
||||
data_d[row_idx.y * p.batch_stride_d + row_idx.x * p.stride_d + dr + cm_row * TM + store_r] = D_TYPE(coopmat_stage[warp_i * TM * TN + (col + store_c) * TM + store_r]);
|
||||
}
|
||||
}
|
||||
}
|
||||
#else
|
||||
const bool is_aligned = p.stride_d % 4 == 0; // Assumption: D_TYPE == float
|
||||
|
||||
[[unroll]] for (uint cm_row = 0; cm_row < cms_per_row; cm_row++) {
|
||||
[[unroll]] for (uint cm_col = 0; cm_col < cms_per_col; cm_col++) {
|
||||
const bool is_in_bounds = dr + (cm_row + 1) * TM <= p.M && dc + (cm_col + 1) * TN <= p.N;
|
||||
|
||||
if (is_aligned && is_in_bounds) {
|
||||
// Full coopMat is within bounds and stride_d is aligned with 16B
|
||||
coopmat<D_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator> cm_dtype = coopmat<D_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator>(sums[cm_col * cms_per_row + cm_row]);
|
||||
coopMatStore(cm_dtype, data_d, offsets + (dc + cm_col * TN) * p.stride_d + dr + cm_row * TM, p.stride_d, gl_CooperativeMatrixLayoutColumnMajor);
|
||||
} else if (is_in_bounds) {
|
||||
// Full coopMat is within bounds, but stride_d is not aligned
|
||||
coopMatStore(sums[cm_col * cms_per_row + cm_row], coopmat_stage, warp_i * TM * TN, TM, gl_CooperativeMatrixLayoutColumnMajor);
|
||||
|
||||
[[unroll]] for (uint col = 0; col < TN; col += storestride) {
|
||||
data_d[offsets + (dc + cm_col * TN + col + store_c) * p.stride_d + dr + cm_row * TM + store_r] = D_TYPE(coopmat_stage[warp_i * TM * TN + (col + store_c) * TM + store_r]);
|
||||
}
|
||||
} else if (dr + cm_row * TM < p.M && dc + cm_col * TN < p.N) {
|
||||
// Partial coopMat is within bounds
|
||||
coopMatStore(sums[cm_col * cms_per_row + cm_row], coopmat_stage, warp_i * TM * TN, TM, gl_CooperativeMatrixLayoutColumnMajor);
|
||||
|
||||
[[unroll]] for (uint col = 0; col < TN; col += storestride) {
|
||||
if (dr + cm_row * TM + store_r < p.M && dc + cm_col * TN + col + store_c < p.N) {
|
||||
data_d[offsets + (dc + cm_col * TN + col + store_c) * p.stride_d + dr + cm_row * TM + store_r] = D_TYPE(coopmat_stage[warp_i * TM * TN + (col + store_c) * TM + store_r]);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
#endif // MUL_MAT_ID
|
||||
#else
|
||||
[[unroll]] for (uint wsic = 0; wsic < WNITER; wsic++) {
|
||||
[[unroll]] for (uint wsir = 0; wsir < WMITER; wsir++) {
|
||||
|
||||
@@ -431,19 +283,21 @@ void main() {
|
||||
const uint row_i = dc_warp + cc;
|
||||
if (row_i >= _ne1) break;
|
||||
|
||||
const u16vec2 row_idx = row_ids[row_i];
|
||||
const u16vec2 row_idx = row_ids[row_i - ic * BN];
|
||||
#endif // MUL_MAT_ID
|
||||
[[unroll]] for (uint cr = 0; cr < TM; cr++) {
|
||||
const uint sums_idx = (wsic * TN + cc) * WMITER * TM + wsir * TM + cr;
|
||||
#ifdef MUL_MAT_ID
|
||||
data_d[row_idx.y * p.batch_stride_d + row_idx.x * p.stride_d + dr_warp + cr] = D_TYPE(sums[(wsic * TN + cc) * (WMITER * TM) + wsir * TM + cr]);
|
||||
if (dr_warp + cr < p.M) {
|
||||
data_d[row_idx.y * p.batch_stride_d + row_idx.x * p.stride_d + dr_warp + cr] = D_TYPE(sums[sums_idx].x);
|
||||
}
|
||||
#else
|
||||
if (dr_warp + cr < p.M && dc_warp + cc < p.N) {
|
||||
data_d[offsets + (dc_warp + cc) * p.stride_d + dr_warp + cr] = D_TYPE(sums[(wsic * TN + cc) * (WMITER * TM) + wsir * TM + cr]);
|
||||
data_d[offsets + (dc_warp + cc) * p.stride_d + dr_warp + cr] = D_TYPE(sums[sums_idx].x);
|
||||
}
|
||||
#endif // MUL_MAT_ID
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
#endif // COOPMAT
|
||||
}
|
||||
|
||||
@@ -6,41 +6,89 @@
|
||||
|
||||
// Each iqs value maps to a 32-bit integer
|
||||
|
||||
#if defined(DATA_A_Q4_0)
|
||||
#if defined(DATA_A_Q4_0) || defined(DATA_A_Q4_1)
|
||||
// 2-byte loads for Q4_0 blocks (18 bytes)
|
||||
// 4-byte loads for Q4_1 blocks (20 bytes)
|
||||
i32vec2 repack(uint ib, uint iqs) {
|
||||
// Use 2-byte loads since a q4_0 block (18 bytes) is not divisible by 4
|
||||
const u16vec2 quants = u16vec2(data_a[ib].qs[iqs * 2 ],
|
||||
data_a[ib].qs[iqs * 2 + 1]);
|
||||
#ifdef DATA_A_Q4_0
|
||||
const u16vec2 quants = u16vec2(data_a_packed16[ib].qs[iqs * 2 ],
|
||||
data_a_packed16[ib].qs[iqs * 2 + 1]);
|
||||
const uint32_t vui = pack32(quants);
|
||||
return i32vec2( vui & 0x0F0F0F0F,
|
||||
(vui >> 4) & 0x0F0F0F0F);
|
||||
#else // DATA_A_Q4_1
|
||||
const uint32_t vui = data_a_packed32[ib].qs[iqs];
|
||||
return i32vec2( vui & 0x0F0F0F0F,
|
||||
(vui >> 4) & 0x0F0F0F0F);
|
||||
#endif
|
||||
}
|
||||
|
||||
#ifdef DATA_A_Q4_0
|
||||
ACC_TYPE mul_q8_1(const int32_t q_sum, const float da, const vec2 dsb, const int32_t sum_divisor) {
|
||||
return ACC_TYPE(da * (float(q_sum) * dsb.x - (8 / sum_divisor) * dsb.y));
|
||||
}
|
||||
#endif
|
||||
|
||||
#if defined(DATA_A_Q4_1)
|
||||
i32vec2 repack(uint ib, uint iqs) {
|
||||
// Use 4-byte loads since a q4_1 block (20 bytes) is divisible by 4
|
||||
const uint32_t vui = data_a_packed32[ib].qs[iqs];
|
||||
return i32vec2( vui & 0x0F0F0F0F,
|
||||
(vui >> 4) & 0x0F0F0F0F);
|
||||
}
|
||||
|
||||
#else // DATA_A_Q4_1
|
||||
ACC_TYPE mul_q8_1(const int32_t q_sum, const vec2 dma, const vec2 dsb, const int32_t sum_divisor) {
|
||||
return ACC_TYPE(float(q_sum) * dma.x * dsb.x + dma.y * dsb.y / sum_divisor);
|
||||
}
|
||||
#endif
|
||||
|
||||
#if defined(DATA_A_Q5_0)
|
||||
#ifdef MMQ_SHMEM
|
||||
void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
|
||||
#ifdef DATA_A_Q4_0
|
||||
buf_a[buf_ib].qs[iqs] = pack32(u16vec2(data_a_packed16[ib].qs[iqs * 2],
|
||||
data_a_packed16[ib].qs[iqs * 2 + 1]));
|
||||
|
||||
if (iqs == 0) {
|
||||
buf_a[buf_ib].dm = FLOAT_TYPE(data_a_packed16[ib].d);
|
||||
}
|
||||
#else // DATA_A_Q4_1
|
||||
buf_a[buf_ib].qs[iqs] = data_a_packed32[ib].qs[iqs];
|
||||
|
||||
if (iqs == 0) {
|
||||
buf_a[buf_ib].dm = FLOAT_TYPE_VEC2(data_a_packed32[ib].dm);
|
||||
}
|
||||
#endif
|
||||
}
|
||||
|
||||
void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
|
||||
cache_a[reg_ib].dm = buf_a[buf_ib].dm;
|
||||
|
||||
[[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
|
||||
cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
|
||||
}
|
||||
}
|
||||
|
||||
ACC_TYPE mmq_dot_product(const uint ib_a) {
|
||||
int32_t q_sum = 0;
|
||||
[[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
|
||||
const uint32_t vui = cache_a[ib_a].qs[iqs];
|
||||
const i32vec2 qs_a = i32vec2( vui & 0x0F0F0F0F,
|
||||
(vui >> 4) & 0x0F0F0F0F);
|
||||
|
||||
const int32_t qs_b0 = cache_b.qs[iqs];
|
||||
const int32_t qs_b1 = cache_b.qs[iqs + 4];
|
||||
|
||||
q_sum += dotPacked4x8EXT(qs_a.x, qs_b0);
|
||||
q_sum += dotPacked4x8EXT(qs_a.y, qs_b1);
|
||||
}
|
||||
|
||||
return mul_q8_1(q_sum, cache_a[ib_a].dm, cache_b.ds, 1);
|
||||
}
|
||||
#endif // MMQ_SHMEM
|
||||
|
||||
#elif defined(DATA_A_Q5_0) || defined(DATA_A_Q5_1)
|
||||
// 2-byte loads for Q5_0 blocks (22 bytes)
|
||||
// 4-byte loads for Q5_1 blocks (24 bytes)
|
||||
i32vec2 repack(uint ib, uint iqs) {
|
||||
// Use 2-byte loads since a q5_0 block (22 bytes) is not divisible by 4
|
||||
const u16vec2 quants = u16vec2(data_a[ib].qs[iqs * 2 ],
|
||||
data_a[ib].qs[iqs * 2 + 1]);
|
||||
const u16vec2 quants = u16vec2(data_a_packed16[ib].qs[iqs * 2 ],
|
||||
data_a_packed16[ib].qs[iqs * 2 + 1]);
|
||||
const uint32_t vui = pack32(quants);
|
||||
const int32_t qh = int32_t((uint32_t(data_a[ib].qh[1]) << 16 | data_a[ib].qh[0]) >> (4 * iqs));
|
||||
#ifdef DATA_A_Q5_0
|
||||
const int32_t qh = int32_t((uint32_t(data_a_packed16[ib].qh[1]) << 16 | data_a_packed16[ib].qh[0]) >> (4 * iqs));
|
||||
#else // DATA_A_Q5_1
|
||||
const int32_t qh = int32_t(data_a_packed32[ib].qh >> (4 * iqs));
|
||||
#endif
|
||||
const int32_t v0 = int32_t(vui & 0x0F0F0F0F)
|
||||
| ((qh & 0xF) * 0x02040810) & 0x10101010; // (0,1,2,3) -> (4,12,20,28)
|
||||
|
||||
@@ -50,40 +98,457 @@ i32vec2 repack(uint ib, uint iqs) {
|
||||
return i32vec2(v0, v1);
|
||||
}
|
||||
|
||||
#ifdef DATA_A_Q5_0
|
||||
ACC_TYPE mul_q8_1(const int32_t q_sum, const float da, const vec2 dsb, const int32_t sum_divisor) {
|
||||
return ACC_TYPE(da * (float(q_sum) * dsb.x - (16 / sum_divisor) * dsb.y));
|
||||
}
|
||||
#endif
|
||||
|
||||
#if defined(DATA_A_Q5_1)
|
||||
i32vec2 repack(uint ib, uint iqs) {
|
||||
// Use 4-byte loads since a q5_1 block (24 bytes) is divisible by 4
|
||||
const uint32_t vui = data_a_packed32[ib].qs[iqs];
|
||||
const int32_t qh = int32_t(data_a_packed32[ib].qh >> (4 * iqs));
|
||||
const int32_t v0 = int32_t(vui & 0x0F0F0F0F)
|
||||
| ((qh & 0xF) * 0x02040810) & 0x10101010; // (0,1,2,3) -> (4,12,20,28)
|
||||
|
||||
const int32_t v1 = int32_t((vui >> 4) & 0x0F0F0F0F)
|
||||
| (((qh >> 16) & 0xF) * 0x02040810) & 0x10101010; // (16,17,18,19) -> (4,12,20,28)
|
||||
|
||||
return i32vec2(v0, v1);
|
||||
}
|
||||
|
||||
#else // DATA_A_Q5_1
|
||||
ACC_TYPE mul_q8_1(const int32_t q_sum, const vec2 dma, const vec2 dsb, const int32_t sum_divisor) {
|
||||
return ACC_TYPE(float(q_sum) * dma.x * dsb.x + dma.y * dsb.y / sum_divisor);
|
||||
}
|
||||
#endif
|
||||
|
||||
#ifdef MMQ_SHMEM
|
||||
void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
|
||||
#ifdef DATA_A_Q5_0
|
||||
buf_a[buf_ib].qs[iqs] = pack32(u16vec2(data_a_packed16[ib].qs[iqs * 2],
|
||||
data_a_packed16[ib].qs[iqs * 2 + 1]));
|
||||
|
||||
if (iqs == 0) {
|
||||
buf_a[buf_ib].dm = FLOAT_TYPE(data_a_packed16[ib].d);
|
||||
buf_a[buf_ib].qh = pack32(u16vec2(data_a_packed16[ib].qh[0], data_a_packed16[ib].qh[1]));
|
||||
}
|
||||
#else // DATA_A_Q5_1
|
||||
buf_a[buf_ib].qs[iqs] = data_a_packed32[ib].qs[iqs];
|
||||
|
||||
if (iqs == 0) {
|
||||
buf_a[buf_ib].dm = FLOAT_TYPE_VEC2(data_a_packed32[ib].dm);
|
||||
buf_a[buf_ib].qh = data_a_packed32[ib].qh;
|
||||
}
|
||||
#endif
|
||||
}
|
||||
|
||||
void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
|
||||
cache_a[reg_ib].dm = buf_a[buf_ib].dm;
|
||||
cache_a[reg_ib].qh = buf_a[buf_ib].qh;
|
||||
|
||||
[[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
|
||||
cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
|
||||
}
|
||||
}
|
||||
|
||||
ACC_TYPE mmq_dot_product(const uint ib_a) {
|
||||
int32_t q_sum = 0;
|
||||
[[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
|
||||
const uint32_t vui = cache_a[ib_a].qs[iqs];
|
||||
const int32_t qh = int32_t(cache_a[ib_a].qh >> (4 * iqs));
|
||||
const int32_t qs_a0 = int32_t(vui & 0x0F0F0F0F)
|
||||
| ((qh & 0xF) * 0x02040810) & 0x10101010; // (0,1,2,3) -> (4,12,20,28)
|
||||
const int32_t qs_a1 = int32_t((vui >> 4) & 0x0F0F0F0F)
|
||||
| (((qh >> 16) & 0xF) * 0x02040810) & 0x10101010; // (16,17,18,19) -> (4,12,20,28)
|
||||
|
||||
const int32_t qs_b0 = cache_b.qs[iqs];
|
||||
const int32_t qs_b1 = cache_b.qs[iqs + 4];
|
||||
|
||||
q_sum += dotPacked4x8EXT(qs_a0, qs_b0);
|
||||
q_sum += dotPacked4x8EXT(qs_a1, qs_b1);
|
||||
}
|
||||
|
||||
return mul_q8_1(q_sum, cache_a[ib_a].dm, cache_b.ds, 1);
|
||||
}
|
||||
#endif // MMQ_SHMEM
|
||||
#endif
|
||||
|
||||
#if defined(DATA_A_Q8_0)
|
||||
// 2-byte loads for Q8_0 blocks (34 bytes)
|
||||
int32_t repack(uint ib, uint iqs) {
|
||||
// Use 2-byte loads since a q8_0 block (34 bytes) is not divisible by 4
|
||||
return pack32(i16vec2(data_a[ib].qs[iqs * 2 ],
|
||||
data_a[ib].qs[iqs * 2 + 1]));
|
||||
return pack32(i16vec2(data_a_packed16[ib].qs[iqs * 2 ],
|
||||
data_a_packed16[ib].qs[iqs * 2 + 1]));
|
||||
}
|
||||
|
||||
ACC_TYPE mul_q8_1(const int32_t q_sum, const float da, const vec2 dsb, const int32_t sum_divisor) {
|
||||
return ACC_TYPE(float(q_sum) * da * dsb.x);
|
||||
}
|
||||
|
||||
#ifdef MMQ_SHMEM
|
||||
void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
|
||||
buf_a[buf_ib].qs[iqs] = pack32(i16vec2(data_a_packed16[ib].qs[iqs * 2],
|
||||
data_a_packed16[ib].qs[iqs * 2 + 1]));
|
||||
|
||||
if (iqs == 0) {
|
||||
buf_a[buf_ib].dm = FLOAT_TYPE(data_a_packed16[ib].d);
|
||||
}
|
||||
}
|
||||
|
||||
void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
|
||||
cache_a[reg_ib].dm = buf_a[buf_ib].dm;
|
||||
|
||||
[[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
|
||||
cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
|
||||
}
|
||||
}
|
||||
|
||||
ACC_TYPE mmq_dot_product(const uint ib_a) {
|
||||
int32_t q_sum = 0;
|
||||
[[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
|
||||
const int32_t qs_a = cache_a[ib_a].qs[iqs];
|
||||
const int32_t qs_b = cache_b.qs[iqs];
|
||||
|
||||
q_sum += dotPacked4x8EXT(qs_a, qs_b);
|
||||
}
|
||||
|
||||
return mul_q8_1(q_sum, cache_a[ib_a].dm, cache_b.ds, 1);
|
||||
}
|
||||
#endif // MMQ_SHMEM
|
||||
#endif
|
||||
|
||||
#if defined(DATA_A_MXFP4)
|
||||
// 1-byte loads for mxfp4 blocks (17 bytes)
|
||||
i32vec2 repack(uint ib, uint iqs) {
|
||||
const uint32_t quants = pack32(u8vec4(data_a[ib].qs[iqs * 4 ],
|
||||
data_a[ib].qs[iqs * 4 + 1],
|
||||
data_a[ib].qs[iqs * 4 + 2],
|
||||
data_a[ib].qs[iqs * 4 + 3]));
|
||||
|
||||
return i32vec2( quants & 0x0F0F0F0F,
|
||||
(quants >> 4) & 0x0F0F0F0F);
|
||||
}
|
||||
|
||||
ACC_TYPE mul_q8_1(const int32_t q_sum, const float da, const vec2 dsb, const int32_t sum_divisor) {
|
||||
return ACC_TYPE(da * dsb.x * float(q_sum));
|
||||
}
|
||||
|
||||
#ifdef MMQ_SHMEM
|
||||
void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
|
||||
const uint32_t qs = pack32(u8vec4(data_a[ib].qs[iqs * 4 ],
|
||||
data_a[ib].qs[iqs * 4 + 1],
|
||||
data_a[ib].qs[iqs * 4 + 2],
|
||||
data_a[ib].qs[iqs * 4 + 3]));
|
||||
|
||||
const u8vec4 i_a0 = unpack8( qs & 0x0F0F0F0F);
|
||||
const u8vec4 i_a1 = unpack8((qs >> 4) & 0x0F0F0F0F);
|
||||
|
||||
buf_a[buf_ib].qs[iqs ] = pack32(i8vec4(kvalues_mxfp4[i_a0.x], kvalues_mxfp4[i_a0.y], kvalues_mxfp4[i_a0.z], kvalues_mxfp4[i_a0.w]));
|
||||
buf_a[buf_ib].qs[iqs + 4] = pack32(i8vec4(kvalues_mxfp4[i_a1.x], kvalues_mxfp4[i_a1.y], kvalues_mxfp4[i_a1.z], kvalues_mxfp4[i_a1.w]));
|
||||
|
||||
if (iqs == 0) {
|
||||
buf_a[buf_ib].d = FLOAT_TYPE(e8m0_to_fp32(data_a[ib].e) * 0.5);
|
||||
}
|
||||
}
|
||||
|
||||
void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
|
||||
cache_a[reg_ib].d = buf_a[buf_ib].d;
|
||||
|
||||
[[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
|
||||
cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
|
||||
}
|
||||
}
|
||||
|
||||
ACC_TYPE mmq_dot_product(const uint ib_a) {
|
||||
int32_t q_sum = 0;
|
||||
[[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
|
||||
const int32_t qs_a = cache_a[ib_a].qs[iqs];
|
||||
|
||||
q_sum += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]);
|
||||
}
|
||||
|
||||
return mul_q8_1(q_sum, cache_a[ib_a].d, cache_b.ds, 1);
|
||||
}
|
||||
#endif // MMQ_SHMEM
|
||||
#endif
|
||||
|
||||
// For k-quants, ib and iqs still assume 32-wide blocks, but k-quants are 256-wide
|
||||
// iqs still refers to a 32-bit integer, meaning 0..7 for 32-wide quants
|
||||
#if defined(DATA_A_Q2_K)
|
||||
// 4-byte loads for Q2_K blocks (84 bytes)
|
||||
int32_t repack(uint ib, uint iqs) {
|
||||
const uint ib_k = ib / 8;
|
||||
const uint iqs_k = (ib % 8) * 8 + iqs;
|
||||
|
||||
const uint qs_idx = (iqs_k / 32) * 8 + (iqs_k % 8);
|
||||
const uint qs_shift = ((iqs_k % 32) / 8) * 2;
|
||||
|
||||
return int32_t((data_a_packed32[ib_k].qs[qs_idx] >> qs_shift) & 0x03030303);
|
||||
}
|
||||
|
||||
uint8_t get_scale(uint ib, uint iqs) {
|
||||
const uint ib_k = ib / 8;
|
||||
const uint iqs_k = (ib % 8) * 8 + iqs;
|
||||
|
||||
return data_a[ib_k].scales[iqs_k / 4];
|
||||
}
|
||||
|
||||
ACC_TYPE mul_q8_1(const int32_t sum_d, const int32_t sum_m, const vec2 dma, const vec2 dsb, const int32_t sum_divisor) {
|
||||
return ACC_TYPE(dsb.x * (dma.x * float(sum_d) - dma.y * float(sum_m)));
|
||||
}
|
||||
|
||||
#ifdef MMQ_SHMEM
|
||||
void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
|
||||
const uint ib_k = ib / 8;
|
||||
const uint iqs_k = (ib % 8) * 8 + iqs * QUANT_R_MMQ;
|
||||
|
||||
const uint qs_idx = (iqs_k / 32) * 8 + (iqs_k % 8);
|
||||
const uint qs_shift = ((iqs_k % 32) / 8) * 2;
|
||||
|
||||
// Repack 4x4 quants into one int
|
||||
const uint32_t vals0 = (data_a_packed32[ib_k].qs[qs_idx ] >> qs_shift) & 0x03030303;
|
||||
const uint32_t vals1 = (data_a_packed32[ib_k].qs[qs_idx + 1] >> qs_shift) & 0x03030303;
|
||||
const uint32_t vals2 = (data_a_packed32[ib_k].qs[qs_idx + 2] >> qs_shift) & 0x03030303;
|
||||
const uint32_t vals3 = (data_a_packed32[ib_k].qs[qs_idx + 3] >> qs_shift) & 0x03030303;
|
||||
|
||||
buf_a[buf_ib].qs[iqs] = vals0 | (vals1 << 2) | (vals2 << 4) | (vals3 << 6);
|
||||
|
||||
if (iqs == 0) {
|
||||
buf_a[buf_ib].dm = FLOAT_TYPE_VEC2(data_a_packed32[ib_k].dm);
|
||||
buf_a[buf_ib].scales = unpack8(data_a_packed16[ib_k].scales[iqs_k / 8]);
|
||||
}
|
||||
}
|
||||
|
||||
void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
|
||||
cache_a[reg_ib].dm = buf_a[buf_ib].dm;
|
||||
cache_a[reg_ib].scales = buf_a[buf_ib].scales;
|
||||
|
||||
[[unroll]] for (uint iqs = 0; iqs < 2; iqs++) {
|
||||
cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
|
||||
}
|
||||
}
|
||||
|
||||
ACC_TYPE mmq_dot_product(const uint ib_a) {
|
||||
int32_t sum_d = 0;
|
||||
int32_t sum_m = 0;
|
||||
|
||||
[[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
|
||||
const uint8_t scale = cache_a[ib_a].scales[iqs / 4];
|
||||
const int32_t scale_m = int32_t(scale >> 4) * 0x01010101; // Duplicate 8-bit value across 32-bits.
|
||||
const int32_t qs_a = int32_t((cache_a[ib_a].qs[iqs / 4] >> ((iqs % 4) * 2)) & 0x03030303);
|
||||
|
||||
sum_d += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]) * (scale & 0xF);
|
||||
sum_m += dotPacked4x8EXT(scale_m, cache_b.qs[iqs]);
|
||||
}
|
||||
|
||||
return mul_q8_1(sum_d, sum_m, cache_a[ib_a].dm, cache_b.ds, 1);
|
||||
}
|
||||
#endif // MMQ_SHMEM
|
||||
#endif
|
||||
|
||||
#if defined(DATA_A_Q3_K)
|
||||
// 2-byte loads for Q3_K blocks (110 bytes)
|
||||
#ifdef MMQ_SHMEM
|
||||
void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
|
||||
const uint ib_k = ib / 8;
|
||||
const uint hm_idx = iqs * QUANT_R_MMQ;
|
||||
const uint iqs_k = (ib % 8) * 8 + hm_idx;
|
||||
|
||||
const uint qs_idx = (iqs_k / 32) * 8 + (iqs_k % 8);
|
||||
const uint qs_shift = ((iqs_k % 32) / 8) * 2;
|
||||
const uint hm_shift = iqs_k / 8;
|
||||
|
||||
// Repack 2x4 quants into one int
|
||||
// Add the 3rd bit instead of subtracting it to allow packing the quants
|
||||
const i8vec2 vals00 = unpack8(int16_t((data_a_packed16[ib_k].qs[qs_idx * 2 ] >> qs_shift) & uint16_t(0x0303))) |
|
||||
unpack8(int16_t(((data_a_packed16[ib_k].hmask[hm_idx * 2 ] >> hm_shift) & uint16_t(0x0101)) << 2));
|
||||
const i8vec2 vals01 = unpack8(int16_t((data_a_packed16[ib_k].qs[qs_idx * 2 + 1 ] >> qs_shift) & uint16_t(0x0303))) |
|
||||
unpack8(int16_t(((data_a_packed16[ib_k].hmask[hm_idx * 2 + 1] >> hm_shift) & uint16_t(0x0101)) << 2));
|
||||
const i8vec2 vals10 = unpack8(int16_t((data_a_packed16[ib_k].qs[qs_idx * 2 + 2 ] >> qs_shift) & uint16_t(0x0303))) |
|
||||
unpack8(int16_t(((data_a_packed16[ib_k].hmask[hm_idx * 2 + 2] >> hm_shift) & uint16_t(0x0101)) << 2));
|
||||
const i8vec2 vals11 = unpack8(int16_t((data_a_packed16[ib_k].qs[qs_idx * 2 + 3 ] >> qs_shift) & uint16_t(0x0303))) |
|
||||
unpack8(int16_t(((data_a_packed16[ib_k].hmask[hm_idx * 2 + 3] >> hm_shift) & uint16_t(0x0101)) << 2));
|
||||
buf_a[buf_ib].qs[iqs] = pack32(u8vec4(vals00.x, vals00.y, vals01.x, vals01.y)) |
|
||||
(pack32(u8vec4(vals10.x, vals10.y, vals11.x, vals11.y)) << 4);
|
||||
|
||||
if (iqs == 0) {
|
||||
const uint is = iqs_k / 4;
|
||||
const i8vec2 scales = i8vec2(unpack8(((data_a_packed16[ib_k].scales[(is % 8 ) / 2] >> (4 * (is / 8))) & 0x0F0F) |
|
||||
(((data_a_packed16[ib_k].scales[(8 + (is % 4)) / 2] >> (2 * (is / 4))) & 0x0303) << 4)));
|
||||
|
||||
buf_a[buf_ib].d_scales = FLOAT_TYPE(data_a_packed16[ib_k].d) * FLOAT_TYPE_VEC2(scales - 32);
|
||||
}
|
||||
}
|
||||
|
||||
void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
|
||||
cache_a[reg_ib].d_scales = buf_a[buf_ib].d_scales;
|
||||
|
||||
[[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
|
||||
cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
|
||||
}
|
||||
}
|
||||
|
||||
ACC_TYPE mmq_dot_product(const uint ib_a) {
|
||||
float result = 0.0;
|
||||
int32_t q_sum = 0;
|
||||
|
||||
[[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
|
||||
// Subtract 4 from the quants to correct the 3rd bit offset
|
||||
const int32_t qs_a = pack32(unpack8(int32_t((cache_a[ib_a].qs[iqs / 2] >> ((iqs % 2) * 4)) & 0x0F0F0F0F)) - int8_t(4));
|
||||
|
||||
q_sum += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]);
|
||||
}
|
||||
result += float(cache_a[ib_a].d_scales[0]) * float(q_sum);
|
||||
q_sum = 0;
|
||||
|
||||
[[unroll]] for (uint iqs = 4; iqs < 8; iqs++) {
|
||||
const int32_t qs_a = pack32(unpack8(int32_t((cache_a[ib_a].qs[iqs / 2] >> ((iqs % 2) * 4)) & 0x0F0F0F0F)) - int8_t(4));
|
||||
|
||||
q_sum += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]);
|
||||
}
|
||||
result += float(cache_a[ib_a].d_scales[1]) * float(q_sum);
|
||||
|
||||
return ACC_TYPE(cache_b.ds.x * result);
|
||||
}
|
||||
#endif // MMQ_SHMEM
|
||||
#endif
|
||||
|
||||
#if defined(DATA_A_Q4_K) || defined(DATA_A_Q5_K)
|
||||
// 4-byte loads for Q4_K blocks (144 bytes) and Q5_K blocks (176 bytes)
|
||||
ACC_TYPE mul_q8_1(const int32_t q_sum, const vec2 dma, const vec2 dsb, const int32_t sum_divisor) {
|
||||
return ACC_TYPE(dsb.x * dma.x * float(q_sum) - dma.y * dsb.y);
|
||||
}
|
||||
|
||||
#ifdef MMQ_SHMEM
|
||||
void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
|
||||
const uint ib_k = ib / 8;
|
||||
const uint iqs_k = (ib % 8) * 8 + iqs * QUANT_R_MMQ;
|
||||
|
||||
const uint qs_idx = (iqs_k / 16) * 8 + (iqs_k % 8);
|
||||
const uint qs_shift = ((iqs_k % 16) / 8) * 4;
|
||||
|
||||
// Repack 2x4 quants into one int
|
||||
#if defined(DATA_A_Q4_K)
|
||||
const uint32_t vals0 = (data_a_packed32[ib_k].qs[qs_idx ] >> qs_shift) & 0x0F0F0F0F;
|
||||
const uint32_t vals1 = (data_a_packed32[ib_k].qs[qs_idx + 1] >> qs_shift) & 0x0F0F0F0F;
|
||||
|
||||
buf_a[buf_ib].qs[iqs] = vals0 | (vals1 << 4);
|
||||
#else // defined(DATA_A_Q5_K)
|
||||
const uint qh_idx = iqs * QUANT_R_MMQ;
|
||||
const uint qh_shift = iqs_k / 8;
|
||||
|
||||
buf_a[buf_ib].qs[iqs] = int32_t(((data_a_packed32[ib_k].qs[qs_idx] >> qs_shift) & 0x0F0F0F0F) |
|
||||
(((data_a_packed32[ib_k].qh[qh_idx] >> qh_shift) & 0x01010101) << 4));
|
||||
#endif
|
||||
|
||||
|
||||
if (iqs == 0) {
|
||||
// Scale index
|
||||
const uint is = iqs_k / 8;
|
||||
u8vec2 scale_dm;
|
||||
if (is < 4) {
|
||||
scale_dm = u8vec2(data_a[ib_k].scales[is] & 0x3F, data_a[ib_k].scales[is + 4] & 0x3F);
|
||||
} else {
|
||||
scale_dm = u8vec2((data_a[ib_k].scales[is+4] & 0xF) | ((data_a[ib_k].scales[is-4] & 0xC0) >> 2),
|
||||
(data_a[ib_k].scales[is+4] >> 4) | ((data_a[ib_k].scales[is ] & 0xC0) >> 2));
|
||||
}
|
||||
|
||||
buf_a[buf_ib].dm = FLOAT_TYPE_VEC2(data_a_packed32[ib_k].dm) * FLOAT_TYPE_VEC2(scale_dm);
|
||||
}
|
||||
}
|
||||
|
||||
void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
|
||||
cache_a[reg_ib].dm = buf_a[buf_ib].dm;
|
||||
|
||||
[[unroll]] for (uint iqs = 0; iqs < 8 / QUANT_R_MMQ; iqs++) {
|
||||
cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
|
||||
}
|
||||
}
|
||||
|
||||
ACC_TYPE mmq_dot_product(const uint ib_a) {
|
||||
int32_t q_sum = 0;
|
||||
|
||||
[[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
|
||||
#if defined(DATA_A_Q4_K)
|
||||
const int32_t qs_a = int32_t((cache_a[ib_a].qs[iqs / 2] >> ((iqs % 2) * 4)) & 0x0F0F0F0F);
|
||||
#else // defined(DATA_A_Q5_K)
|
||||
const int32_t qs_a = cache_a[ib_a].qs[iqs];
|
||||
#endif
|
||||
|
||||
q_sum += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]);
|
||||
}
|
||||
|
||||
return mul_q8_1(q_sum, cache_a[ib_a].dm, cache_b.ds, 1);
|
||||
}
|
||||
#endif // MMQ_SHMEM
|
||||
#endif
|
||||
|
||||
#ifdef MMQ_SHMEM
|
||||
void block_b_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
|
||||
const uint ib_outer = ib / 4;
|
||||
const uint ib_inner = ib % 4;
|
||||
|
||||
if (iqs == 0) {
|
||||
buf_b[buf_ib].ds = FLOAT_TYPE_VEC2(data_b[ib_outer].ds[ib_inner]);
|
||||
}
|
||||
|
||||
const ivec4 values = data_b[ib_outer].qs[ib_inner * 2 + iqs];
|
||||
buf_b[buf_ib].qs[iqs * 4 ] = values.x;
|
||||
buf_b[buf_ib].qs[iqs * 4 + 1] = values.y;
|
||||
buf_b[buf_ib].qs[iqs * 4 + 2] = values.z;
|
||||
buf_b[buf_ib].qs[iqs * 4 + 3] = values.w;
|
||||
}
|
||||
|
||||
void block_b_to_registers(const uint ib) {
|
||||
cache_b.ds = buf_b[ib].ds;
|
||||
[[unroll]] for (uint iqs = 0; iqs < BK / 4; iqs++) {
|
||||
cache_b.qs[iqs] = buf_b[ib].qs[iqs];
|
||||
}
|
||||
}
|
||||
#endif
|
||||
|
||||
#if defined(DATA_A_Q6_K)
|
||||
// 2-byte loads for Q6_K blocks (210 bytes)
|
||||
#ifdef MMQ_SHMEM
|
||||
void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
|
||||
const uint ib_k = ib / 8;
|
||||
const uint iqs_k = (ib % 8) * 8 + iqs;
|
||||
|
||||
const uint ql_idx = (iqs_k / 32) * 16 + iqs_k % 16;
|
||||
const uint ql_shift = ((iqs_k % 32) / 16) * 4;
|
||||
|
||||
const uint qh_idx = (iqs_k / 32) * 8 + iqs;
|
||||
const uint qh_shift = ((iqs_k % 32) / 8) * 2;
|
||||
|
||||
const i8vec2 vals00 = (unpack8(int16_t((data_a_packed16[ib_k].ql[ql_idx * 2 ] >> ql_shift) & uint16_t(0x0F0F))) |
|
||||
unpack8(int16_t(((data_a_packed16[ib_k].qh[qh_idx * 2 ] >> qh_shift) & uint16_t(0x0303)) << 4))) - int8_t(32);
|
||||
const i8vec2 vals01 = (unpack8(int16_t((data_a_packed16[ib_k].ql[ql_idx * 2 + 1] >> ql_shift) & uint16_t(0x0F0F))) |
|
||||
unpack8(int16_t(((data_a_packed16[ib_k].qh[qh_idx * 2 + 1] >> qh_shift) & uint16_t(0x0303)) << 4))) - int8_t(32);
|
||||
buf_a[buf_ib].qs[iqs] = pack32(i8vec4(vals00.x, vals00.y, vals01.x, vals01.y));
|
||||
|
||||
if (iqs == 0) {
|
||||
const uint is = iqs_k / 4;
|
||||
const i8vec2 scales = unpack8(data_a_packed16[ib_k].scales[is / 2]);
|
||||
|
||||
buf_a[buf_ib].d_scales = FLOAT_TYPE(data_a_packed16[ib_k].d) * FLOAT_TYPE_VEC2(scales);
|
||||
}
|
||||
}
|
||||
|
||||
void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
|
||||
cache_a[reg_ib].d_scales = buf_a[buf_ib].d_scales;
|
||||
|
||||
[[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
|
||||
cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
|
||||
}
|
||||
}
|
||||
|
||||
ACC_TYPE mmq_dot_product(const uint ib_a) {
|
||||
float result = 0.0;
|
||||
int32_t q_sum = 0;
|
||||
|
||||
[[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
|
||||
const int32_t qs_a = cache_a[ib_a].qs[iqs];
|
||||
|
||||
q_sum += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]);
|
||||
}
|
||||
result += float(cache_a[ib_a].d_scales[0]) * float(q_sum);
|
||||
q_sum = 0;
|
||||
|
||||
[[unroll]] for (uint iqs = 4; iqs < 8; iqs++) {
|
||||
const int32_t qs_a = cache_a[ib_a].qs[iqs];
|
||||
|
||||
q_sum += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]);
|
||||
}
|
||||
result += float(cache_a[ib_a].d_scales[1]) * float(q_sum);
|
||||
|
||||
return ACC_TYPE(cache_b.ds.x * result);
|
||||
}
|
||||
#endif // MMQ_SHMEM
|
||||
#endif
|
||||
|
||||
#if defined(DATA_A_Q4_0) || defined(DATA_A_Q5_0) || defined(DATA_A_Q8_0) || defined(DATA_A_IQ1_S) || defined(DATA_A_IQ2_XXS) || defined(DATA_A_IQ2_XS) || defined(DATA_A_IQ2_S) || defined(DATA_A_IQ3_XXS) || defined(DATA_A_IQ3_S) || defined(DATA_A_IQ4_XS) || defined(DATA_A_IQ4_NL)
|
||||
@@ -103,3 +568,10 @@ FLOAT_TYPE_VEC2 get_dm(uint ib) {
|
||||
return FLOAT_TYPE_VEC2(data_a_packed32[ib].dm);
|
||||
}
|
||||
#endif
|
||||
|
||||
#if defined(DATA_A_Q2_K)
|
||||
FLOAT_TYPE_VEC2 get_dm(uint ib) {
|
||||
const uint ib_k = ib / 8;
|
||||
return FLOAT_TYPE_VEC2(data_a_packed32[ib_k].dm);
|
||||
}
|
||||
#endif
|
||||
|
||||
@@ -0,0 +1,78 @@
|
||||
#if defined(DATA_A_Q4_0)
|
||||
#define QUANT_R_MMQ 2
|
||||
struct block_a_cache {
|
||||
uint32_t qs[16/4];
|
||||
FLOAT_TYPE dm;
|
||||
};
|
||||
#elif defined(DATA_A_Q4_1)
|
||||
#define QUANT_R_MMQ 2
|
||||
struct block_a_cache {
|
||||
uint32_t qs[16/4];
|
||||
FLOAT_TYPE_VEC2 dm;
|
||||
};
|
||||
#elif defined(DATA_A_Q5_0)
|
||||
#define QUANT_R_MMQ 2
|
||||
struct block_a_cache {
|
||||
uint32_t qs[16/4];
|
||||
uint32_t qh;
|
||||
FLOAT_TYPE dm;
|
||||
};
|
||||
#elif defined(DATA_A_Q5_1)
|
||||
#define QUANT_R_MMQ 2
|
||||
struct block_a_cache {
|
||||
uint32_t qs[16/4];
|
||||
uint32_t qh;
|
||||
FLOAT_TYPE_VEC2 dm;
|
||||
};
|
||||
#elif defined(DATA_A_Q8_0)
|
||||
#define QUANT_R_MMQ 1
|
||||
// AMD likes 4, Intel likes 1 and Nvidia likes 2
|
||||
// #define BK_STEP 1
|
||||
struct block_a_cache {
|
||||
int32_t qs[32/4];
|
||||
FLOAT_TYPE dm;
|
||||
};
|
||||
#elif defined(DATA_A_MXFP4)
|
||||
#define QUANT_R_MMQ 2
|
||||
struct block_a_cache {
|
||||
int32_t qs[8];
|
||||
FLOAT_TYPE d;
|
||||
};
|
||||
#elif defined(DATA_A_Q2_K)
|
||||
#define QUANT_R_MMQ 4
|
||||
struct block_a_cache {
|
||||
uint32_t qs[2];
|
||||
u8vec2 scales;
|
||||
FLOAT_TYPE_VEC2 dm;
|
||||
};
|
||||
#elif defined(DATA_A_Q3_K)
|
||||
#define QUANT_R_MMQ 2
|
||||
struct block_a_cache {
|
||||
uint32_t qs[4];
|
||||
FLOAT_TYPE_VEC2 d_scales;
|
||||
};
|
||||
#elif defined(DATA_A_Q4_K)
|
||||
#define QUANT_R_MMQ 2
|
||||
struct block_a_cache {
|
||||
uint32_t qs[4];
|
||||
FLOAT_TYPE_VEC2 dm;
|
||||
};
|
||||
#elif defined(DATA_A_Q5_K)
|
||||
#define QUANT_R_MMQ 1
|
||||
struct block_a_cache {
|
||||
int32_t qs[8];
|
||||
FLOAT_TYPE_VEC2 dm;
|
||||
};
|
||||
#elif defined(DATA_A_Q6_K)
|
||||
#define QUANT_R_MMQ 1
|
||||
struct block_a_cache {
|
||||
int32_t qs[8];
|
||||
FLOAT_TYPE_VEC2 d_scales;
|
||||
};
|
||||
#endif
|
||||
|
||||
struct block_b_cache
|
||||
{
|
||||
int32_t qs[8];
|
||||
FLOAT_TYPE_VEC2 ds;
|
||||
};
|
||||
@@ -10,6 +10,7 @@ layout (binding = 0) readonly buffer X {A_TYPE data_a[];};
|
||||
layout (binding = 1) readonly buffer Y {int data_pos[];};
|
||||
layout (binding = 2) readonly buffer Z {float data_ff[];};
|
||||
layout (binding = 3) writeonly buffer D {D_TYPE data_d[];};
|
||||
layout (binding = 4) readonly buffer I {uvec2 data_i[];}; // indices for set_rows
|
||||
|
||||
layout (push_constant) uniform parameter {
|
||||
uint ncols;
|
||||
@@ -27,6 +28,7 @@ layout (push_constant) uniform parameter {
|
||||
uint s2;
|
||||
int sections[4];
|
||||
uint is_back;
|
||||
uint set_rows_stride;
|
||||
} p;
|
||||
|
||||
float rope_yarn_ramp(const float low, const float high, const uint i0) {
|
||||
|
||||
@@ -16,12 +16,19 @@ void main() {
|
||||
const uint row_x = row_dst % ne1;
|
||||
const uint channel_x = row_dst / ne1;
|
||||
|
||||
const uint idst = row_dst*ne0 + i0/2;
|
||||
uint idst = row_dst*ne0 + i0/2;
|
||||
const uint ix = channel_x*p.s2 + row_x*p.s1 + i0/2;
|
||||
|
||||
// Fusion optimization: ROPE + VIEW + SET_ROWS..
|
||||
// The rope output is viewed as a 1D tensor and offset based on a row index in data_i.
|
||||
if (p.set_rows_stride != 0) {
|
||||
idst = row_x*ne0 + i0/2;
|
||||
idst += data_i[channel_x].x * p.set_rows_stride;
|
||||
}
|
||||
|
||||
if (i0 >= p.n_dims) {
|
||||
data_d[idst + i0/2 + 0] = data_a[ix + i0/2 + 0];
|
||||
data_d[idst + i0/2 + 1] = data_a[ix + i0/2 + 1];
|
||||
data_d[idst + i0/2 + 0] = D_TYPE(data_a[ix + i0/2 + 0]);
|
||||
data_d[idst + i0/2 + 1] = D_TYPE(data_a[ix + i0/2 + 1]);
|
||||
|
||||
return;
|
||||
}
|
||||
|
||||
@@ -16,12 +16,19 @@ void main() {
|
||||
const uint row_x = row_dst % ne1;
|
||||
const uint channel_x = row_dst / ne1;
|
||||
|
||||
const uint idst = row_dst*ne0 + i0;
|
||||
uint idst = row_dst*ne0 + i0;
|
||||
const uint ix = channel_x*p.s2 + row_x*p.s1 + i0;
|
||||
|
||||
// Fusion optimization: ROPE + VIEW + SET_ROWS..
|
||||
// The rope output is viewed as a 1D tensor and offset based on a row index in data_i.
|
||||
if (p.set_rows_stride != 0) {
|
||||
idst = row_x*ne0 + i0;
|
||||
idst += data_i[channel_x].x * p.set_rows_stride;
|
||||
}
|
||||
|
||||
if (i0 >= p.n_dims) {
|
||||
data_d[idst + 0] = data_a[ix + 0];
|
||||
data_d[idst + 1] = data_a[ix + 1];
|
||||
data_d[idst + 0] = D_TYPE(data_a[ix + 0]);
|
||||
data_d[idst + 1] = D_TYPE(data_a[ix + 1]);
|
||||
|
||||
return;
|
||||
}
|
||||
|
||||
@@ -11,6 +11,8 @@ layout (push_constant) uniform parameter
|
||||
{
|
||||
uint n_rows;
|
||||
uint n_expert_used;
|
||||
float clamp_min;
|
||||
float clamp_max;
|
||||
};
|
||||
|
||||
layout(local_size_x_id = 0, local_size_y = 4, local_size_z = 1) in;
|
||||
@@ -18,6 +20,7 @@ layout(local_size_x_id = 0, local_size_y = 4, local_size_z = 1) in;
|
||||
layout(constant_id = 0) const uint WARP_SIZE = 32;
|
||||
layout(constant_id = 1) const uint n_experts = 512;
|
||||
layout(constant_id = 2) const bool with_norm = true;
|
||||
layout(constant_id = 3) const bool late_softmax = false;
|
||||
|
||||
const uint experts_per_thread = (n_experts > WARP_SIZE) ? n_experts / WARP_SIZE : 1;
|
||||
|
||||
@@ -25,6 +28,52 @@ layout (binding = 0, std430) readonly buffer Logits {float logits[];};
|
||||
layout (binding = 1, std430) writeonly buffer Weights {float weights[];};
|
||||
layout (binding = 2, std430) writeonly buffer Ids {uint ids[];};
|
||||
|
||||
const float INFINITY = 1.0 / 0.0;
|
||||
|
||||
// Warp-local softmax used for both the pre-top-k logits and the post-top-k delayed path.
|
||||
void softmax_warp_inplace(inout float vals[experts_per_thread], const uint limit, const uint lane, const bool use_limit) {
|
||||
float max_val = -INFINITY;
|
||||
|
||||
[[unroll]]
|
||||
for (int i = 0; i < experts_per_thread; i++) {
|
||||
const uint idx = lane + i * WARP_SIZE;
|
||||
const bool is_active = !use_limit || (idx < limit);
|
||||
if (is_active) {
|
||||
max_val = max(max_val, vals[i]);
|
||||
}
|
||||
}
|
||||
|
||||
max_val = subgroupMax(max_val);
|
||||
|
||||
float sum = 0.f;
|
||||
|
||||
[[unroll]]
|
||||
for (int i = 0; i < experts_per_thread; i++) {
|
||||
const uint idx = lane + i * WARP_SIZE;
|
||||
const bool is_active = !use_limit || (idx < limit);
|
||||
if (is_active) {
|
||||
const float val = exp(vals[i] - max_val);
|
||||
vals[i] = val;
|
||||
sum += val;
|
||||
} else {
|
||||
vals[i] = 0.f;
|
||||
}
|
||||
}
|
||||
|
||||
sum = subgroupAdd(sum);
|
||||
|
||||
const float inv_sum = 1.0f / sum;
|
||||
|
||||
[[unroll]]
|
||||
for (int i = 0; i < experts_per_thread; i++) {
|
||||
const uint idx = lane + i * WARP_SIZE;
|
||||
const bool is_active = !use_limit || (idx < limit);
|
||||
if (is_active) {
|
||||
vals[i] *= inv_sum;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
void main() {
|
||||
const uint row = gl_WorkGroupID.x * gl_WorkGroupSize.y + gl_LocalInvocationID.y;
|
||||
if (row >= n_rows) {
|
||||
@@ -35,43 +84,16 @@ void main() {
|
||||
const uint weights_offset = n_expert_used * row;
|
||||
const uint ids_offset = n_experts * row;
|
||||
|
||||
float logits_r[experts_per_thread];
|
||||
|
||||
const float INFINITY = 1.0 / 0.0;
|
||||
float wt[experts_per_thread];
|
||||
|
||||
[[unroll]]
|
||||
for (uint i = 0; i < n_experts; i += WARP_SIZE) {
|
||||
const uint expert = i + gl_LocalInvocationID.x;
|
||||
logits_r[i / WARP_SIZE] = n_experts % WARP_SIZE == 0 || expert < n_experts ? logits[logits_offset + expert] : -INFINITY;
|
||||
const uint expert = i + gl_LocalInvocationID.x;
|
||||
wt[i / WARP_SIZE] = (n_experts % WARP_SIZE == 0 || expert < n_experts) ? logits[logits_offset + expert] : -INFINITY;
|
||||
}
|
||||
|
||||
float max_val = logits_r[0];
|
||||
|
||||
[[unroll]]
|
||||
for (int i = 1; i < experts_per_thread; i++) {
|
||||
const float val = logits_r[i];
|
||||
max_val = max(val, max_val);
|
||||
}
|
||||
|
||||
max_val = subgroupMax(max_val);
|
||||
|
||||
float wt[experts_per_thread];
|
||||
float tmp = 0.f;
|
||||
|
||||
[[unroll]]
|
||||
for (int i = 0; i < experts_per_thread; i++) {
|
||||
const float val = logits_r[i];
|
||||
wt[i] = exp(val - max_val);
|
||||
tmp += wt[i];
|
||||
}
|
||||
|
||||
tmp = subgroupAdd(tmp);
|
||||
|
||||
const float inv_sum = 1.0f / tmp;
|
||||
|
||||
[[unroll]]
|
||||
for (int i = 0; i < experts_per_thread; i++) {
|
||||
wt[i] = wt[i] * inv_sum;
|
||||
if (!late_softmax) {
|
||||
softmax_warp_inplace(wt, n_experts, gl_LocalInvocationID.x, false);
|
||||
}
|
||||
|
||||
// at this point, each thread holds a portion of softmax,
|
||||
@@ -82,6 +104,11 @@ void main() {
|
||||
|
||||
float output_weights[experts_per_thread];
|
||||
|
||||
[[unroll]]
|
||||
for (int i = 0; i < experts_per_thread; i++) {
|
||||
output_weights[i] = 0.f;
|
||||
}
|
||||
|
||||
for (int k = 0; k < n_expert_used; k++) {
|
||||
float max_val = wt[0];
|
||||
uint max_expert = gl_LocalInvocationID.x;
|
||||
@@ -121,6 +148,7 @@ void main() {
|
||||
|
||||
if (with_norm) {
|
||||
wt_sum = subgroupAdd(wt_sum);
|
||||
wt_sum = clamp(wt_sum, clamp_min, clamp_max);
|
||||
const float inv_sum = 1.0f / wt_sum;
|
||||
|
||||
[[unroll]]
|
||||
@@ -129,6 +157,10 @@ void main() {
|
||||
}
|
||||
}
|
||||
|
||||
if (late_softmax) {
|
||||
softmax_warp_inplace(output_weights, n_expert_used, gl_LocalInvocationID.x, true);
|
||||
}
|
||||
|
||||
[[unroll]]
|
||||
for (uint i = 0; i < experts_per_thread; ++i) {
|
||||
uint idx = i * WARP_SIZE + gl_LocalInvocationID.x;
|
||||
|
||||
@@ -66,6 +66,7 @@ struct block_q4_0_packed16
|
||||
#define QUANT_AUXF 1
|
||||
#define A_TYPE block_q4_0
|
||||
#define A_TYPE_PACKED16 block_q4_0_packed16
|
||||
#define DATA_A_QUANT_LEGACY
|
||||
#endif
|
||||
|
||||
#define QUANT_K_Q4_1 32
|
||||
@@ -98,6 +99,7 @@ struct block_q4_1_packed32
|
||||
#define A_TYPE block_q4_1
|
||||
#define A_TYPE_PACKED16 block_q4_1_packed16
|
||||
#define A_TYPE_PACKED32 block_q4_1_packed32
|
||||
#define DATA_A_QUANT_LEGACY
|
||||
#endif
|
||||
|
||||
#define QUANT_K_Q5_0 32
|
||||
@@ -123,6 +125,7 @@ struct block_q5_0_packed16
|
||||
#define QUANT_AUXF 1
|
||||
#define A_TYPE block_q5_0
|
||||
#define A_TYPE_PACKED16 block_q5_0_packed16
|
||||
#define DATA_A_QUANT_LEGACY
|
||||
#endif
|
||||
|
||||
#define QUANT_K_Q5_1 32
|
||||
@@ -158,6 +161,7 @@ struct block_q5_1_packed32
|
||||
#define A_TYPE block_q5_1
|
||||
#define A_TYPE_PACKED16 block_q5_1_packed16
|
||||
#define A_TYPE_PACKED32 block_q5_1_packed32
|
||||
#define DATA_A_QUANT_LEGACY
|
||||
#endif
|
||||
|
||||
#define QUANT_K_Q8_0 32
|
||||
@@ -186,6 +190,7 @@ struct block_q8_0_packed32
|
||||
#define A_TYPE block_q8_0
|
||||
#define A_TYPE_PACKED16 block_q8_0_packed16
|
||||
#define A_TYPE_PACKED32 block_q8_0_packed32
|
||||
#define DATA_A_QUANT_LEGACY
|
||||
#endif
|
||||
|
||||
#define QUANT_K_Q8_1 32
|
||||
@@ -226,21 +231,21 @@ struct block_q2_K
|
||||
{
|
||||
uint8_t scales[QUANT_K_Q2_K/16];
|
||||
uint8_t qs[QUANT_K_Q2_K/4];
|
||||
f16vec2 d;
|
||||
f16vec2 dm;
|
||||
};
|
||||
|
||||
struct block_q2_K_packed16
|
||||
{
|
||||
uint16_t scales[QUANT_K_Q2_K/16/2];
|
||||
uint16_t qs[QUANT_K_Q2_K/4/2];
|
||||
f16vec2 d;
|
||||
f16vec2 dm;
|
||||
};
|
||||
|
||||
struct block_q2_K_packed32
|
||||
{
|
||||
uint32_t scales[QUANT_K_Q2_K/16/4];
|
||||
uint32_t qs[QUANT_K_Q2_K/4/4];
|
||||
f16vec2 d;
|
||||
f16vec2 dm;
|
||||
};
|
||||
|
||||
#if defined(DATA_A_Q2_K)
|
||||
@@ -249,6 +254,8 @@ struct block_q2_K_packed32
|
||||
#define A_TYPE block_q2_K
|
||||
#define A_TYPE_PACKED16 block_q2_K_packed16
|
||||
#define A_TYPE_PACKED32 block_q2_K_packed32
|
||||
#define SCALES_PER_32 2
|
||||
#define DATA_A_QUANT_K
|
||||
#endif
|
||||
|
||||
#define QUANT_K_Q3_K 256
|
||||
@@ -274,27 +281,28 @@ struct block_q3_K_packed16
|
||||
#define QUANT_R 1
|
||||
#define A_TYPE block_q3_K
|
||||
#define A_TYPE_PACKED16 block_q3_K_packed16
|
||||
#define DATA_A_QUANT_K
|
||||
#endif
|
||||
|
||||
#define QUANT_K_Q4_K 256
|
||||
|
||||
struct block_q4_K
|
||||
{
|
||||
f16vec2 d;
|
||||
f16vec2 dm;
|
||||
uint8_t scales[3*QUANT_K_Q4_K/64];
|
||||
uint8_t qs[QUANT_K_Q4_K/2];
|
||||
};
|
||||
|
||||
struct block_q4_K_packed16
|
||||
{
|
||||
f16vec2 d;
|
||||
f16vec2 dm;
|
||||
uint16_t scales[3*QUANT_K_Q4_K/64/2];
|
||||
uint16_t qs[QUANT_K_Q4_K/2/2];
|
||||
};
|
||||
|
||||
struct block_q4_K_packed32
|
||||
{
|
||||
f16vec2 d;
|
||||
f16vec2 dm;
|
||||
uint32_t scales[3*QUANT_K_Q4_K/64/4];
|
||||
uint32_t qs[QUANT_K_Q4_K/2/4];
|
||||
};
|
||||
@@ -310,13 +318,14 @@ struct block_q4_K_packed128
|
||||
#define A_TYPE block_q4_K
|
||||
#define A_TYPE_PACKED16 block_q4_K_packed16
|
||||
#define A_TYPE_PACKED32 block_q4_K_packed32
|
||||
#define DATA_A_QUANT_K
|
||||
#endif
|
||||
|
||||
#define QUANT_K_Q5_K 256
|
||||
|
||||
struct block_q5_K
|
||||
{
|
||||
f16vec2 d;
|
||||
f16vec2 dm;
|
||||
uint8_t scales[12];
|
||||
uint8_t qh[QUANT_K_Q5_K/8];
|
||||
uint8_t qs[QUANT_K_Q5_K/2];
|
||||
@@ -324,12 +333,20 @@ struct block_q5_K
|
||||
|
||||
struct block_q5_K_packed16
|
||||
{
|
||||
f16vec2 d;
|
||||
f16vec2 dm;
|
||||
uint16_t scales[12/2];
|
||||
uint16_t qh[QUANT_K_Q5_K/8/2];
|
||||
uint16_t qs[QUANT_K_Q5_K/2/2];
|
||||
};
|
||||
|
||||
struct block_q5_K_packed32
|
||||
{
|
||||
f16vec2 dm;
|
||||
uint32_t scales[12/4];
|
||||
uint32_t qh[QUANT_K_Q5_K/8/4];
|
||||
uint32_t qs[QUANT_K_Q5_K/2/4];
|
||||
};
|
||||
|
||||
struct block_q5_K_packed128
|
||||
{
|
||||
uvec4 q5k[11];
|
||||
@@ -340,6 +357,8 @@ struct block_q5_K_packed128
|
||||
#define QUANT_R 1
|
||||
#define A_TYPE block_q5_K
|
||||
#define A_TYPE_PACKED16 block_q5_K_packed16
|
||||
#define A_TYPE_PACKED32 block_q5_K_packed32
|
||||
#define DATA_A_QUANT_K
|
||||
#endif
|
||||
|
||||
#define QUANT_K_Q6_K 256
|
||||
@@ -356,7 +375,7 @@ struct block_q6_K_packed16
|
||||
{
|
||||
uint16_t ql[QUANT_K_Q6_K/2/2];
|
||||
uint16_t qh[QUANT_K_Q6_K/4/2];
|
||||
int8_t scales[QUANT_K_Q6_K/16];
|
||||
int16_t scales[QUANT_K_Q6_K/16/2];
|
||||
float16_t d;
|
||||
};
|
||||
|
||||
@@ -365,6 +384,7 @@ struct block_q6_K_packed16
|
||||
#define QUANT_R 1
|
||||
#define A_TYPE block_q6_K
|
||||
#define A_TYPE_PACKED16 block_q6_K_packed16
|
||||
#define DATA_A_QUANT_K
|
||||
#endif
|
||||
|
||||
// IQuants
|
||||
@@ -1363,18 +1383,11 @@ struct block_mxfp4
|
||||
uint8_t qs[QUANT_K_MXFP4/2];
|
||||
};
|
||||
|
||||
//struct block_mxfp4_packed16
|
||||
//{
|
||||
// uint8_t e;
|
||||
// uint16_t qs[QUANT_K_MXFP4/2/2];
|
||||
//};
|
||||
|
||||
#if defined(DATA_A_MXFP4)
|
||||
#define QUANT_K QUANT_K_MXFP4
|
||||
#define QUANT_R QUANT_R_MXFP4
|
||||
#define QUANT_AUXF 1
|
||||
#define A_TYPE block_mxfp4
|
||||
//#define A_TYPE_PACKED16 block_mxfp4_packed16
|
||||
#endif
|
||||
|
||||
#if defined(DATA_A_IQ4_NL) || defined(DATA_A_IQ4_XS)
|
||||
@@ -1397,12 +1410,12 @@ void init_iq_shmem(uvec3 wgsize)
|
||||
#endif
|
||||
|
||||
#if defined(DATA_A_MXFP4)
|
||||
const FLOAT_TYPE kvalues_mxfp4_const[16] = {
|
||||
FLOAT_TYPE(0.0f), FLOAT_TYPE(0.5f), FLOAT_TYPE(1.0f), FLOAT_TYPE(1.5f), FLOAT_TYPE(2.0f), FLOAT_TYPE(3.0f), FLOAT_TYPE(4.0f), FLOAT_TYPE(6.0f),
|
||||
FLOAT_TYPE(-0.0f), FLOAT_TYPE(-0.5f), FLOAT_TYPE(-1.0f), FLOAT_TYPE(-1.5f), FLOAT_TYPE(-2.0f), FLOAT_TYPE(-3.0f), FLOAT_TYPE(-4.0f), FLOAT_TYPE(-6.0f)
|
||||
const int8_t kvalues_mxfp4_const[16] = {
|
||||
int8_t(0), int8_t(1), int8_t(2), int8_t(3), int8_t(4), int8_t(6), int8_t(8), int8_t(12),
|
||||
int8_t(0), int8_t(-1), int8_t(-2), int8_t(-3), int8_t(-4), int8_t(-6), int8_t(-8), int8_t(-12),
|
||||
};
|
||||
|
||||
shared FLOAT_TYPE kvalues_mxfp4[16];
|
||||
shared int8_t kvalues_mxfp4[16];
|
||||
|
||||
#define NEEDS_INIT_IQ_SHMEM
|
||||
void init_iq_shmem(uvec3 wgsize)
|
||||
|
||||
@@ -566,7 +566,8 @@ void matmul_shaders(bool fp16, MatMulIdType matmul_id_type, bool coopmat, bool c
|
||||
}
|
||||
|
||||
#if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
|
||||
if (!coopmat && !coopmat2 && matmul_id_type == MatMulIdType::NONE && is_legacy_quant(tname)) {
|
||||
// Integer dot mmq performs better with f32 accumulators
|
||||
if (!f16acc && !coopmat && !coopmat2 && (is_legacy_quant(tname) || is_k_quant(tname) || tname == "mxfp4")) {
|
||||
string_to_spv(shader_name + "_" + tname + "_q8_1", "mul_mmq.comp", merge_maps(merge_maps(base_dict, float_type_dict), {{data_a_key, "1"}, {"D_TYPE", "float"},}), fp16, coopmat, coopmat2, f16acc);
|
||||
}
|
||||
#endif
|
||||
@@ -574,7 +575,7 @@ void matmul_shaders(bool fp16, MatMulIdType matmul_id_type, bool coopmat, bool c
|
||||
}
|
||||
|
||||
void process_shaders() {
|
||||
std::map<std::string, std::string> base_dict = {{"FLOAT_TYPE", "float"}};
|
||||
std::map<std::string, std::string> base_dict = {{"FLOAT_TYPE", "float"}, {"FLOAT_TYPE_VEC2", "vec2"}};
|
||||
|
||||
// matmul
|
||||
for (const MatMulIdType& matmul_id_type : {MatMulIdType::NONE, MatMulIdType::DEFAULT, MatMulIdType::SUBGROUP}) {
|
||||
@@ -841,10 +842,14 @@ void process_shaders() {
|
||||
string_to_spv("rope_norm_f32", "rope_norm.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
|
||||
string_to_spv("rope_norm_f16", "rope_norm.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}});
|
||||
string_to_spv("rope_norm_f16_rte", "rope_norm.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}, {"RTE16", "1"}});
|
||||
string_to_spv("rope_norm_f32_f16", "rope_norm.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float16_t"}});
|
||||
string_to_spv("rope_norm_f32_f16_rte", "rope_norm.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float16_t"}, {"RTE16", "1"}});
|
||||
|
||||
string_to_spv("rope_neox_f32", "rope_neox.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
|
||||
string_to_spv("rope_neox_f16", "rope_neox.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}});
|
||||
string_to_spv("rope_neox_f16_rte", "rope_neox.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}, {"RTE16", "1"}});
|
||||
string_to_spv("rope_neox_f32_f16", "rope_neox.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float16_t"}});
|
||||
string_to_spv("rope_neox_f32_f16_rte", "rope_neox.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float16_t"}, {"RTE16", "1"}});
|
||||
|
||||
string_to_spv("rope_multi_f32", "rope_multi.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
|
||||
string_to_spv("rope_multi_f16", "rope_multi.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}});
|
||||
|
||||
Reference in New Issue
Block a user