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https://github.com/ggerganov/llama.cpp.git
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vulkan: copy iq4_nl LUT into shared memory (#10409)
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@ -10,6 +10,8 @@ layout (binding = 1) writeonly buffer D {D_TYPE data_b[];};
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void main() {
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void main() {
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const uint i = gl_WorkGroupID.x * 4 + gl_LocalInvocationID.x / 64;
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const uint i = gl_WorkGroupID.x * 4 + gl_LocalInvocationID.x / 64;
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init_iq4nl_shmem();
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const uint tid = gl_LocalInvocationID.x % 64;
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const uint tid = gl_LocalInvocationID.x % 64;
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const uint il = tid/32;
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const uint il = tid/32;
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const uint ir = tid%32;
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const uint ir = tid%32;
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@ -12,6 +12,10 @@ void main() {
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const uint i11 = (gl_GlobalInvocationID.z)/p.ne12;
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const uint i11 = (gl_GlobalInvocationID.z)/p.ne12;
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const uint i12 = (gl_GlobalInvocationID.z)%p.ne12;
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const uint i12 = (gl_GlobalInvocationID.z)%p.ne12;
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#if defined(DATA_A_IQ4_NL)
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init_iq4nl_shmem();
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#endif
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if (i00 >= p.ne00) {
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if (i00 >= p.ne00) {
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return;
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return;
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}
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}
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@ -161,6 +161,10 @@ void compute_outputs(const uint32_t first_row, const uint32_t num_rows) {
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void main() {
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void main() {
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const uint first_row = NUM_ROWS * (gl_WorkGroupID.x + gl_NumWorkGroups.x * gl_WorkGroupID.z);
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const uint first_row = NUM_ROWS * (gl_WorkGroupID.x + gl_NumWorkGroups.x * gl_WorkGroupID.z);
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#if defined(DATA_A_IQ4_NL)
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init_iq4nl_shmem();
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#endif
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// do NUM_ROWS at a time, unless there aren't enough remaining rows
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// do NUM_ROWS at a time, unless there aren't enough remaining rows
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if (first_row + NUM_ROWS <= p.stride_d) {
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if (first_row + NUM_ROWS <= p.stride_d) {
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compute_outputs(first_row, NUM_ROWS);
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compute_outputs(first_row, NUM_ROWS);
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@ -75,6 +75,10 @@ shared u16vec2 row_ids[3072];
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#endif
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#endif
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void main() {
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void main() {
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#if defined(DATA_A_IQ4_NL)
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init_iq4nl_shmem();
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#endif
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#ifdef MUL_MAT_ID
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#ifdef MUL_MAT_ID
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const uint expert_idx = gl_GlobalInvocationID.z;
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const uint expert_idx = gl_GlobalInvocationID.z;
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#else
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#else
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@ -298,10 +298,21 @@ struct block_iq4_nl_packed16
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#define A_TYPE block_iq4_nl
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#define A_TYPE block_iq4_nl
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#define A_TYPE_PACKED16 block_iq4_nl_packed16
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#define A_TYPE_PACKED16 block_iq4_nl_packed16
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const int8_t kvalues_iq4nl[16] = {
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const int8_t kvalues_iq4nl_const[16] = {
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int8_t(-127), int8_t(-104), int8_t(-83), int8_t(-65), int8_t(-49), int8_t(-35), int8_t(-22), int8_t(-10),
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int8_t(-127), int8_t(-104), int8_t(-83), int8_t(-65), int8_t(-49), int8_t(-35), int8_t(-22), int8_t(-10),
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int8_t(1), int8_t(13), int8_t(25), int8_t(38), int8_t(53), int8_t(69), int8_t(89), int8_t(113)
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int8_t(1), int8_t(13), int8_t(25), int8_t(38), int8_t(53), int8_t(69), int8_t(89), int8_t(113)
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};
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};
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shared FLOAT_TYPE kvalues_iq4nl[16];
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void init_iq4nl_shmem()
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{
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// copy the table into shared memory and sync
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if (gl_LocalInvocationIndex.x < 16) {
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kvalues_iq4nl[gl_LocalInvocationIndex.x] = FLOAT_TYPE(kvalues_iq4nl_const[gl_LocalInvocationIndex.x]);
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}
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barrier();
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}
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#endif
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#endif
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#endif // !defined(GGML_TYPES_COMP)
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#endif // !defined(GGML_TYPES_COMP)
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@ -331,11 +331,11 @@ void process_shaders() {
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shader = (tname == "f32" || tname == "f16") ? "get_rows.comp" : "get_rows_quant.comp";
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shader = (tname == "f32" || tname == "f16") ? "get_rows.comp" : "get_rows_quant.comp";
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if (tname == "f16") {
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if (tname == "f16") {
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string_to_spv("get_rows_" + tname, shader, {{data_a_key, "1"}, {"B_TYPE", "int"}, {"D_TYPE", "float16_t"}, {"OPTIMIZATION_ERROR_WORKAROUND", "1"}});
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string_to_spv("get_rows_" + tname, shader, merge_maps(base_dict, {{data_a_key, "1"}, {"B_TYPE", "int"}, {"D_TYPE", "float16_t"}, {"OPTIMIZATION_ERROR_WORKAROUND", "1"}}));
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} else {
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} else {
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string_to_spv("get_rows_" + tname, shader, {{data_a_key, "1"}, {"B_TYPE", "int"}, {"D_TYPE", "float16_t"}});
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string_to_spv("get_rows_" + tname, shader, merge_maps(base_dict, {{data_a_key, "1"}, {"B_TYPE", "int"}, {"D_TYPE", "float16_t"}}));
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}
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}
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string_to_spv("get_rows_" + tname + "_f32", shader, {{data_a_key, "1"}, {"B_TYPE", "int"}, {"D_TYPE", "float"}});
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string_to_spv("get_rows_" + tname + "_f32", shader, merge_maps(base_dict, {{data_a_key, "1"}, {"B_TYPE", "int"}, {"D_TYPE", "float"}}));
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}
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}
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}
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}
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