Jeff Bolz
b3ad3a0191
* vulkan: support SET_ROWS Add variants of the copy_to_quant shader that do the SET_ROWS operation. Change these shaders to spread the work across the workgroup. The memory access pattern is probably not great (one thread per quant block), but should be fine for now. * vulkan: optimize set_rows Larger workgroups for non-quant types. Set "norepeat" (there is manual repeat logic). Use fastmod.
294 lines
7.9 KiB
Plaintext
294 lines
7.9 KiB
Plaintext
#version 450
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#if RTE16
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#extension GL_EXT_spirv_intrinsics : enable
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spirv_execution_mode(capabilities = [4467], 4462, 16); // RoundingModeRTE, 16 bits
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#endif // RTE16
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#include "types.comp"
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#if defined(SET_ROWS) && QUANT_K == 1
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layout(local_size_x = 512, local_size_y = 1, local_size_z = 1) in;
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const uint BLOCK_SIZE = 512;
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#else
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layout(local_size_x = 32, local_size_y = 1, local_size_z = 1) in;
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const uint BLOCK_SIZE = 32;
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#endif
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layout (binding = 0) readonly buffer S {float data_s[];};
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#if defined(SET_ROWS)
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#include "generic_binary_head.comp"
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layout (binding = 1) readonly buffer C {uvec2 data_i[];};
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layout (binding = 2) writeonly buffer Q {A_TYPE data_q[];};
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#else
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#include "generic_unary_head.comp"
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layout (binding = 1) writeonly buffer Q {A_TYPE data_q[];};
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#endif
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#if defined(DATA_A_Q4_0)
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void quantize(uint dst_idx, uint src_idx)
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{
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float amax = 0.0;
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float vmax = 0.0;
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[[unroll]] for (int j = 0; j < QUANT_K_Q4_0; ++j) {
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const float v = data_s[src_idx + j];
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if (amax < abs(v)) {
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amax = abs(v);
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vmax = v;
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}
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}
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const float d = vmax / -8;
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const float id = (d != 0.0) ? 1.0/d : 0.0;
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data_q[dst_idx].d = float16_t(d);
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[[unroll]] for (int j = 0; j < QUANT_K_Q4_0/2; ++j) {
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const float x0 = data_s[src_idx + 0 + j]*id;
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const float x1 = data_s[src_idx + QUANT_K_Q4_0/2 + j]*id;
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const uint xi0 = min(15, int(x0 + 8.5));
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const uint xi1 = min(15, int(x1 + 8.5));
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data_q[dst_idx].qs[j] = uint8_t(xi0 | (xi1 << 4));
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}
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}
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#endif
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#if defined(DATA_A_Q4_1)
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void quantize(uint dst_idx, uint src_idx)
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{
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float vmin = 1.0/0.0;
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float vmax = -vmin;
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[[unroll]] for (int j = 0; j < QUANT_K_Q4_1; ++j) {
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const float v = data_s[src_idx + j];
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if (v < vmin) vmin = v;
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if (v > vmax) vmax = v;
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}
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const float d = (vmax - vmin) / ((1 << 4) - 1);
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const float id = (d != 0.0) ? 1.0/d : 0.0;
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data_q[dst_idx].d = float16_t(d);
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data_q[dst_idx].m = float16_t(vmin);
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[[unroll]] for (int j = 0; j < QUANT_K_Q4_1/2; ++j) {
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const float x0 = (data_s[src_idx + 0 + j] - vmin)*id;
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const float x1 = (data_s[src_idx + QUANT_K_Q4_1/2 + j] - vmin)*id;
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const uint xi0 = min(15, int(x0 + 0.5));
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const uint xi1 = min(15, int(x1 + 0.5));
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data_q[dst_idx].qs[j] = uint8_t(xi0 | (xi1 << 4));
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}
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}
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#endif
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#if defined(DATA_A_Q5_0)
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void quantize(uint dst_idx, uint src_idx)
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{
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float amax = 0.0;
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float vmax = 0.0;
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[[unroll]] for (int j = 0; j < QUANT_K_Q5_0; ++j) {
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const float v = data_s[src_idx + j];
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if (amax < abs(v)) {
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amax = abs(v);
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vmax = v;
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}
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}
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const float d = vmax / -16;
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const float id = (d != 0.0) ? 1.0/d : 0.0;
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data_q[dst_idx].d = float16_t(d);
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uint32_t qh = 0;
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[[unroll]] for (int j = 0; j < QUANT_K_Q5_0/2; ++j) {
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const float x0 = data_s[src_idx + 0 + j]*id;
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const float x1 = data_s[src_idx + QUANT_K_Q5_0/2 + j]*id;
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const uint xi0 = min(31, int(x0 + 16.5));
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const uint xi1 = min(31, int(x1 + 16.5));
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data_q[dst_idx].qs[j] = uint8_t((xi0 & 0xf) | ((xi1 & 0xf) << 4));
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qh |= ((xi0 & 0x10u) >> 4) << (j + 0);
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qh |= ((xi1 & 0x10u) >> 4) << (j + QUANT_K_Q5_0/2);
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}
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data_q[dst_idx].qh[0] = uint16_t(qh & 0xFFFF);
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data_q[dst_idx].qh[1] = uint16_t(qh >> 16);
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}
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#endif
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#if defined(DATA_A_Q5_1)
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void quantize(uint dst_idx, uint src_idx)
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{
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float min = data_s[src_idx + 0];
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float max = min;
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[[unroll]] for (int j = 1; j < QUANT_K_Q5_1; ++j) {
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const float v = data_s[src_idx + j];
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min = v < min ? v : min;
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max = v > max ? v : max;
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}
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const float d = (max - min) / 31;
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const float id = (d != 0) ? 1.0/d : 0.0;
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data_q[dst_idx].d = float16_t(d);
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data_q[dst_idx].m = float16_t(min);
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uint32_t qh = 0;
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[[unroll]] for (int j = 0; j < QUANT_K_Q5_1/2; ++j) {
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const float x0 = (data_s[src_idx + 0 + j] - min)*id;
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const float x1 = (data_s[src_idx + QUANT_K_Q5_1/2 + j] - min)*id;
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const uint xi0 = uint(x0 + 0.5);
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const uint xi1 = uint(x1 + 0.5);
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data_q[dst_idx].qs[j] = uint8_t((xi0 & 0xf) | ((xi1 & 0xf) << 4));
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qh |= ((xi0 & 0x10u) >> 4) << (j + 0);
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qh |= ((xi1 & 0x10u) >> 4) << (j + QUANT_K_Q5_1/2);
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}
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data_q[dst_idx].qh = qh;
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}
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#endif
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#if defined(DATA_A_Q8_0)
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void quantize(uint dst_idx, uint src_idx)
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{
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float amax = 0.0; // absolute max
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[[unroll]] for (int j = 0; j < QUANT_K_Q8_0; j++) {
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const float v = data_s[src_idx + j];
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amax = max(amax, abs(v));
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}
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const float d = amax / ((1 << 7) - 1);
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const float id = (d != 0.0) ? 1.0/d : 0.0;
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data_q[dst_idx].d = float16_t(d);
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[[unroll]] for (int j = 0; j < QUANT_K_Q8_0; ++j) {
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const float x0 = data_s[src_idx + j]*id;
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data_q[dst_idx].qs[j] = int8_t(round(x0));
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}
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}
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#endif
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#if defined(DATA_A_IQ4_NL)
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uint best_index(float x) {
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if (x <= kvalues_iq4nl[0]) return 0;
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if (x >= kvalues_iq4nl[15]) return 15;
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int ml = 0, mu = 15;
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while (mu-ml > 1) {
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int mav = (ml+mu)/2;
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if (x < kvalues_iq4nl[mav]) mu = mav; else ml = mav;
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}
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return x - kvalues_iq4nl[mu-1] < kvalues_iq4nl[mu] - x ? mu-1 : mu;
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}
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void quantize(uint dst_idx, uint src_idx)
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{
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float amax = 0.0;
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float vmax = 0.0;
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[[unroll]] for (int j = 0; j < QUANT_K_IQ4_NL; ++j) {
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const float v = data_s[src_idx + j];
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if (amax < abs(v)) {
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amax = abs(v);
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vmax = v;
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}
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}
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float d = vmax / kvalues_iq4nl[0];
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const float id = (d != 0.0) ? 1.0/d : 0.0;
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float sumqx = 0, sumq2 = 0;
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[[unroll]] for (int j = 0; j < QUANT_K_IQ4_NL/2; ++j) {
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const float x0 = data_s[src_idx + 0 + j]*id;
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const float x1 = data_s[src_idx + QUANT_K_IQ4_NL/2 + j]*id;
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const uint xi0 = best_index(x0);
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const uint xi1 = best_index(x1);
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data_q[dst_idx].qs[j] = uint8_t(xi0 | (xi1 << 4));
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const float v0 = kvalues_iq4nl[xi0];
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const float v1 = kvalues_iq4nl[xi1];
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const float w0 = data_s[src_idx + 0 + j]*data_s[src_idx + 0 + j];
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const float w1 = data_s[src_idx + QUANT_K_IQ4_NL/2 + j]*data_s[src_idx + QUANT_K_IQ4_NL/2 + j];
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sumqx += w0*v0*data_s[src_idx + j] + w1*v1*data_s[src_idx + QUANT_K_IQ4_NL/2 + j];
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sumq2 += w0*v0*v0 + w1*v1*v1;
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}
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data_q[dst_idx].d = float16_t(sumq2 > 0 ? sumqx/sumq2 : d);
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}
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#endif
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#if defined(DATA_A_F32) || defined(DATA_A_F16)
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void quantize(uint dst_idx, uint src_idx)
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{
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data_q[dst_idx] = A_TYPE(data_s[src_idx]);
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}
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#endif
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#if defined(DATA_A_BF16)
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void quantize(uint dst_idx, uint src_idx)
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{
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data_q[dst_idx] = A_TYPE(fp32_to_bf16(data_s[src_idx]));
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}
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#endif
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#if defined(SET_ROWS)
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void main() {
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#ifdef NEEDS_INIT_IQ_SHMEM
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init_iq_shmem(gl_WorkGroupSize);
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#endif
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const uint idx = ((gl_WorkGroupID.z * 262144 + gl_WorkGroupID.y * 512 + gl_WorkGroupID.x) * BLOCK_SIZE + gl_LocalInvocationID.x) * QUANT_K;
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if (idx >= p.ne) {
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return;
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}
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uint i00, i01, i02, i03;
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get_indices(idx, i00, i01, i02, i03);
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uint i12 = fastmod(i03, p.ne12);
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uint i11 = fastmod(i02, p.ne11);
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uint i10 = i01;
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uint i1 = data_i[src1_idx(i10, i11, i12, 0) + get_boffset()].x;
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uint src0_idx = src0_idx(i00, i01, i02, i03) + get_aoffset();
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uint dst_idx = dst_idx(i00 / QUANT_K, i1, i02, i03) + get_doffset();
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quantize(dst_idx, src0_idx);
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}
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#else
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void main() {
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#ifdef NEEDS_INIT_IQ_SHMEM
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init_iq_shmem(gl_WorkGroupSize);
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#endif
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const uint idx = (gl_WorkGroupID.z * 262144 + gl_WorkGroupID.y * 512 + gl_WorkGroupID.x * 32 + gl_LocalInvocationID.x) * QUANT_K;
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if (idx >= p.ne) {
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return;
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}
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uint dst_idx = dst_idx_quant(idx, QUANT_K);
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uint src_idx = get_aoffset() + src0_idx(idx);
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quantize(dst_idx, src_idx);
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}
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#endif
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