Merge branch 'ggerganov:master' into master

examples/common.cpp

@@ -110,7 +110,7 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
                 invalid_param = true;
                 break;
             }
-            params.seed = std::stoi(argv[i]);
+            params.seed = std::stoul(argv[i]);
         } else if (arg == "-t" || arg == "--threads") {
             if (++i >= argc) {
                 invalid_param = true;

examples/common.h

@@ -22,7 +22,7 @@
 int32_t get_num_physical_cores();
 
 struct gpt_params {
-    int32_t seed                            = -1;  // RNG seed
+    uint32_t seed                           = -1;  // RNG seed
     int32_t n_threads                       = get_num_physical_cores();
     int32_t n_predict                       = -1;  // new tokens to predict
     int32_t n_ctx                           = 512; // context size

examples/embedding/embedding.cpp

@@ -24,11 +24,11 @@ int main(int argc, char ** argv) {
 
     fprintf(stderr, "%s: build = %d (%s)\n", __func__, BUILD_NUMBER, BUILD_COMMIT);
 
-    if (params.seed < 0) {
+    if (params.seed == LLAMA_DEFAULT_SEED) {
         params.seed = time(NULL);
     }
 
-    fprintf(stderr, "%s: seed  = %d\n", __func__, params.seed);
+    fprintf(stderr, "%s: seed  = %u\n", __func__, params.seed);
 
     std::mt19937 rng(params.seed);
     if (params.random_prompt) {

examples/main/README.md

@@ -242,7 +242,7 @@ Example usage: `--logit-bias 29905-inf`
 
 ### RNG Seed
 
--   `-s SEED, --seed SEED`: Set the random number generator (RNG) seed (default: -1, < 0 = random seed).
+-   `-s SEED, --seed SEED`: Set the random number generator (RNG) seed (default: -1, -1 = random seed).
 
 The RNG seed is used to initialize the random number generator that influences the text generation process. By setting a specific seed value, you can obtain consistent and reproducible results across multiple runs with the same input and settings. This can be helpful for testing, debugging, or comparing the effects of different options on the generated text to see when they diverge. If the seed is set to a value less than 0, a random seed will be used, which will result in different outputs on each run.
 

examples/main/main.cpp

@@ -94,11 +94,11 @@ int main(int argc, char ** argv) {
 
     fprintf(stderr, "%s: build = %d (%s)\n", __func__, BUILD_NUMBER, BUILD_COMMIT);
 
-    if (params.seed < 0) {
+    if (params.seed == LLAMA_DEFAULT_SEED) {
         params.seed = time(NULL);
     }
 
-    fprintf(stderr, "%s: seed  = %d\n", __func__, params.seed);
+    fprintf(stderr, "%s: seed  = %u\n", __func__, params.seed);
 
     std::mt19937 rng(params.seed);
     if (params.random_prompt) {

examples/perplexity/perplexity.cpp

@@ -136,11 +136,11 @@ int main(int argc, char ** argv) {
 
     fprintf(stderr, "%s: build = %d (%s)\n", __func__, BUILD_NUMBER, BUILD_COMMIT);
 
-    if (params.seed < 0) {
+    if (params.seed == LLAMA_DEFAULT_SEED) {
         params.seed = time(NULL);
     }
 
-    fprintf(stderr, "%s: seed  = %d\n", __func__, params.seed);
+    fprintf(stderr, "%s: seed  = %u\n", __func__, params.seed);
 
     std::mt19937 rng(params.seed);
     if (params.random_prompt) {

examples/server/README.md

@@ -152,7 +152,7 @@ node .
 
     `mirostat_eta`: Set the Mirostat learning rate, parameter eta (default: 0.1).
 
-    `seed`: Set the random number generator (RNG) seed (default: -1, < 0 = random seed).
+    `seed`: Set the random number generator (RNG) seed (default: -1, -1 = random seed).
 
     `ignore_eos`: Ignore end of stream token and continue generating (default: false).
 

examples/train-text-from-scratch/train-text-from-scratch.cpp

@@ -2768,7 +2768,7 @@ void train_print_usage(int /*argc*/, char ** argv, const struct train_params * p
     fprintf(stderr, "  --checkpoint-in FNAME      path from which to load training checkpoint (default '%s')\n", params->fn_checkpoint_in);
     fprintf(stderr, "  --checkpoint-out FNAME     path to save training checkpoint (default '%s')\n", params->fn_checkpoint_out);
     fprintf(stderr, "  --model-out FNAME          path to save ggml model (default '%s')\n", params->fn_model_out);
-    fprintf(stderr, "  -s SEED, --seed SEED       RNG seed (default: -1, use random seed for < 0)\n");
+    fprintf(stderr, "  -s SEED, --seed SEED       RNG seed (default: -1, use random seed for -1)\n");
     fprintf(stderr, "  -c N, --ctx N              Context size used during training (default %d)\n", params->n_ctx);
     fprintf(stderr, "  --embd N                   Embedding size used for new models (default %d)\n", params->n_embd);
     fprintf(stderr, "  --mult N                   Mult size used for new models, influences feedforward size. (default %d)\n", params->n_mult);
@@ -3034,10 +3034,10 @@ int main(int argc, char ** argv) {
         return 1;
     }
 
-    if (params.seed < 0) {
+    if (params.seed == LLAMA_DEFAULT_SEED) {
         params.seed = time(NULL);
     }
-    printf("%s: seed: %d\n", __func__, params.seed);
+    printf("%s: seed: %u\n", __func__, params.seed);
     srand(params.seed);
 
     struct llama_context_params llama_params = llama_context_default_params();

ggml-opencl.cpp

@@ -21,11 +21,19 @@
 
 #define CL_DMMV_BLOCK_SIZE 32
 
+#ifndef K_QUANTS_PER_ITERATION
+#define K_QUANTS_PER_ITERATION 1
+#else
+static_assert(K_QUANTS_PER_ITERATION == 1 || K_QUANTS_PER_ITERATION == 2, "K_QUANTS_PER_ITERATION must be 1 or 2");
+#endif
+
 #define MULTILINE_QUOTE(...) #__VA_ARGS__
 static std::string program_source = MULTILINE_QUOTE(
 
 typedef char int8_t;
 typedef uchar uint8_t;
+typedef short int16_t;
+typedef ushort uint16_t;
 typedef int int32_t;
 typedef uint uint32_t;
 
@@ -175,7 +183,9 @@ void convert_f16(__global half* x, const int ib, const int iqs, float* v0, float
     *v0 = vload_half(0, &x[ib + 0]);
     *v1 = vload_half(0, &x[ib + 1]);
 }
+);
 
+static std::string k_quants_source = MULTILINE_QUOTE(
 inline void get_scale_min_k4(int j, const __global uint8_t *q, uint8_t *d, uint8_t *m)
 {
     if (j < 4)
@@ -199,7 +209,7 @@ __kernel void dequantize_block_q2_K(__global const struct block_q2_K *x, __globa
     const int is = 8 * n + l / 16;
 
     const uint8_t q = x[i].qs[32 * n + l];
-    __global float *y = yy + i * 256 + 128 * n;
+    __global float *y = yy + i * QK_K + 128 * n;
 
     const float dall = vload_half(0, &x[i].d);
     const float dmin = vload_half(0, &x[i].dmin);
@@ -231,7 +241,7 @@ __kernel void dequantize_block_q3_K(__global const struct block_q3_K *x, __globa
     float d_all = vload_half(0, &x[i].d);
     float dl = d_all * (us - 32);
 
-    __global float *y = yy + i * 256 + 128 * n + 32 * j;
+    __global float *y = yy + i * QK_K + 128 * n + 32 * j;
     const __global uint8_t *q = x[i].qs + 32 * n;
     const __global uint8_t *hm = x[i].hmask;
 
@@ -248,7 +258,7 @@ __kernel void dequantize_block_q4_K(__global const struct block_q4_K *x, __globa
     const int is = 2 * il;
     const int n = 4;
 
-    __global float *y = yy + i * 256 + 64 * il + n * ir;
+    __global float *y = yy + i * QK_K + 64 * il + n * ir;
 
     const float dall = vload_half(0, &x[i].d);
     const float dmin = vload_half(0, &x[i].dmin);
@@ -277,7 +287,7 @@ __kernel void dequantize_block_q5_K(__global const struct block_q5_K *x, __globa
     const int ir = tid % 16;
     const int is = 2 * il;
 
-    __global float *y = yy + i * 256 + 64 * il + 2 * ir;
+    __global float *y = yy + i * QK_K + 64 * il + 2 * ir;
 
     const float dall = vload_half(0, &x[i].d);
     const float dmin = vload_half(0, &x[i].dmin);
@@ -309,7 +319,7 @@ __kernel void dequantize_block_q6_K(__global const struct block_q6_K *x, __globa
     const int il = tid - 32 * ip;
     const int is = 8 * ip + il / 16;
 
-    __global float *y = yy + i * 256 + 128 * ip + il;
+    __global float *y = yy + i * QK_K + 128 * ip + il;
 
     const float d = vload_half(0, &x[i].d);
 
@@ -323,161 +333,383 @@ __kernel void dequantize_block_q6_K(__global const struct block_q6_K *x, __globa
     y[96] = d * sc[6] * ((int8_t)((ql[32] >> 4) | (((qh >> 6) & 3) << 4)) - 32);
 }
 
+__kernel void dequantize_mul_mat_vec_q2_K(__global const struct block_q2_K * xx, __local float* tmp, __global float* yy, __global float* dst, const int ncols) {
 
-void vec_dot_q2_K(__global const struct block_q2_K* x, const int ib, const int iqs, const __global float *yy, float *result) {
+    const int row = get_group_id(0);
 
-    int n = iqs / 128;
+    const int num_blocks_per_row = ncols / QK_K;
-    int r = iqs - 128 * n;
+    const int ib0 = row*num_blocks_per_row;
-    int l = r / 8;
 
-    __global const float *y = yy + 128 * n + l;
+    __global const struct block_q2_K * x = xx + ib0;
-    __global const uint8_t *q = x[ib].qs + 32 * n + l;
-    __global const uint8_t *s = x[ib].scales + 8 * n;
 
-    const float dall = vload_half(0, &x[ib].d);
+    const int tid = get_local_id(0)/K_QUANTS_PER_ITERATION;  // 0...31 or 0...15
-    const float dmin = vload_half(0, &x[ib].dmin);
+    const int ix  = get_local_id(0)%K_QUANTS_PER_ITERATION;  // 0 or 0,1
 
-    float sum = y[  0] * (dall * ((s[0] & 0xF) * ((q[ 0] >> 0) & 3)) - dmin * (s[0] >> 4))
+    const int step = 16/K_QUANTS_PER_ITERATION;
-              + y[ 32] * (dall * ((s[2] & 0xF) * ((q[ 0] >> 2) & 3)) - dmin * (s[2] >> 4))
-              + y[ 64] * (dall * ((s[4] & 0xF) * ((q[ 0] >> 4) & 3)) - dmin * (s[4] >> 4))
-              + y[ 96] * (dall * ((s[6] & 0xF) * ((q[ 0] >> 6) & 3)) - dmin * (s[6] >> 4))
-              + y[ 16] * (dall * ((s[1] & 0xF) * ((q[16] >> 0) & 3)) - dmin * (s[1] >> 4))
-              + y[ 48] * (dall * ((s[3] & 0xF) * ((q[16] >> 2) & 3)) - dmin * (s[3] >> 4))
-              + y[ 80] * (dall * ((s[5] & 0xF) * ((q[16] >> 4) & 3)) - dmin * (s[5] >> 4))
-              + y[112] * (dall * ((s[7] & 0xF) * ((q[16] >> 6) & 3)) - dmin * (s[7] >> 4));
 
-    *result = sum;
+    const int im = tid/step;                             // 0 or 1. 0 computes 0..., 1 computes 128...
-}
+    const int in = tid - step*im;                        // 0...15 or 0...7
 
-void vec_dot_q3_K(__global const struct block_q3_K* x, const int ib, const int iqs, const __global float *yy, float *result) {
+    const int l0 = K_QUANTS_PER_ITERATION*in;            // 0...15 or 0...14 in steps of 2
+    const int q_offset = 32*im + l0;
+    const int s_offset = 8*im;
+    const int y_offset = 128*im + l0;
 
-    const uint32_t kmask1 = 0x03030303;
+    tmp[16 * ix + tid] = 0;
-    const uint32_t kmask2 = 0x0f0f0f0f;
 
-    uint32_t aux[3];
+    uint32_t aux[4];
-    uint32_t utmp[4];
+    const uint8_t * d = (const uint8_t *)aux;
+    const uint8_t * m = (const uint8_t *)(aux + 2);
 
-    int n = iqs/128;
+    for (int i = ix; i < num_blocks_per_row; i += K_QUANTS_PER_ITERATION) {
-    int r = iqs - 128*n;
-    int l = r/8;
 
-    __global const float   * y = yy + 128*n + l;
+        __global const float   * y = yy + i * QK_K + y_offset;
-    __global const uint8_t * q = x[ib].qs + 32*n + l;
+        __global const uint8_t * q = x[i].qs + q_offset;
-    __global const uint8_t * hm = x[ib].hmask + l;
-    const int8_t * s = (const int8_t *)utmp + 8*n;
 
-    aux[0] = x[ib].scales[0] | x[ib].scales[1] << 8 | x[ib].scales[2] << 16 | x[ib].scales[3] << 24;
+        const float dall = vload_half(0, &x[i].d);
-    aux[1] = x[ib].scales[4] | x[ib].scales[5] << 8 | x[ib].scales[6] << 16 | x[ib].scales[7] << 24;
+        const float dmin = vload_half(0, &x[i].dmin);
-    aux[2] = x[ib].scales[8] | x[ib].scales[9] << 8 | x[ib].scales[10] << 16 | x[ib].scales[11] << 24;
 
-    utmp[3] = ((aux[1] >> 4) & kmask2) | (((aux[2] >> 6) & kmask1) << 4);
+        __global const uint32_t * a = (__global const uint32_t *)(x[i].scales + s_offset);
-    utmp[2] = ((aux[0] >> 4) & kmask2) | (((aux[2] >> 4) & kmask1) << 4);
+        aux[0] = a[0] & 0x0f0f0f0f;
-    utmp[1] = (aux[1] & kmask2) | (((aux[2] >> 2) & kmask1) << 4);
+        aux[1] = a[1] & 0x0f0f0f0f;
-    utmp[0] = (aux[0] & kmask2) | (((aux[2] >> 0) & kmask1) << 4);
+        aux[2] = (a[0] >> 4) & 0x0f0f0f0f;
+        aux[3] = (a[1] >> 4) & 0x0f0f0f0f;
 
-    const float dall = vload_half(0, &x[ib].d);
+        float sum1 = 0, sum2 = 0;
-    const uint8_t m = 1 << (4*n);
+        for (int l = 0; l < K_QUANTS_PER_ITERATION; ++l) {
+            sum1 += y[l+ 0] * d[0] * ((q[l+ 0] >> 0) & 3)
+                  + y[l+32] * d[2] * ((q[l+ 0] >> 2) & 3)
+                  + y[l+64] * d[4] * ((q[l+ 0] >> 4) & 3)
+                  + y[l+96] * d[6] * ((q[l+ 0] >> 6) & 3)
+                  + y[l+16] * d[1] * ((q[l+16] >> 0) & 3)
+                  + y[l+48] * d[3] * ((q[l+16] >> 2) & 3)
+                  + y[l+80] * d[5] * ((q[l+16] >> 4) & 3)
+                  +y[l+112] * d[7] * ((q[l+16] >> 6) & 3);
+            sum2 += y[l+ 0] * m[0] + y[l+32] * m[2] + y[l+64] * m[4] + y[ l+96] * m[6]
+                  + y[l+16] * m[1] + y[l+48] * m[3] + y[l+80] * m[5] + y[l+112] * m[7];
 
-    float sum = y[  0] * (s[0] - 32) * (((q[ 0] >> 0) & 3) - (hm[ 0] & (m << 0) ? 0 : 4))
+        }
-              + y[ 32] * (s[2] - 32) * (((q[ 0] >> 2) & 3) - (hm[ 0] & (m << 1) ? 0 : 4))
+        tmp[16 * ix + tid] += dall * sum1 - dmin * sum2;
-              + y[ 64] * (s[4] - 32) * (((q[ 0] >> 4) & 3) - (hm[ 0] & (m << 2) ? 0 : 4))
-              + y[ 96] * (s[6] - 32) * (((q[ 0] >> 6) & 3) - (hm[ 0] & (m << 3) ? 0 : 4))
-              + y[ 16] * (s[1] - 32) * (((q[16] >> 0) & 3) - (hm[16] & (m << 0) ? 0 : 4))
-              + y[ 48] * (s[3] - 32) * (((q[16] >> 2) & 3) - (hm[16] & (m << 1) ? 0 : 4))
-              + y[ 80] * (s[5] - 32) * (((q[16] >> 4) & 3) - (hm[16] & (m << 2) ? 0 : 4))
-              + y[112] * (s[7] - 32) * (((q[16] >> 6) & 3) - (hm[16] & (m << 3) ? 0 : 4));
 
-    *result = sum * dall;
-
-}
-
-void vec_dot_q4_K(__global const struct block_q4_K* x, const int ib, const int iqs, const __global float *yy, float *result) {
-
-    const int j  = iqs / 64;        // j  is in 0...3
-    const int ir = (iqs - 64*j)/2;  // ir is in 0...28 in steps of 4
-    const int is = 2*j;             // is is in 0...6 in steps of 2
-
-    __global const float   * y = yy + 64*j + ir;
-    __global const uint8_t * q = x[ib].qs + 32*j + ir;
-
-    const float dall = vload_half(0, &x[ib].d);
-    const float dmin = vload_half(0, &x[ib].dmin);
-
-    uint8_t sc, m;
-    get_scale_min_k4(is + 0, x[ib].scales, &sc, &m);
-    const float d1 = dall * sc;
-    const float m1 = dmin * m;
-    get_scale_min_k4(is + 1, x[ib].scales, &sc, &m);
-    const float d2 = dall * sc;
-    const float m2 = dmin * m;
-
-    float sum = 0;
-    for (int k = 0; k < 4; ++k) {
-        sum += y[k +  0] * (d1 * (q[k] & 0xF) - m1);
-        sum += y[k + 32] * (d2 * (q[k] >>  4) - m2);
     }
 
-    *result = sum;
+    // sum up partial sums and write back result
+    barrier(CLK_LOCAL_MEM_FENCE);
+    for (int s=16; s>0; s>>=1) {
+        if (tid < s) {
+            tmp[tid] += tmp[tid + s];
+        }
+        barrier(CLK_LOCAL_MEM_FENCE);
+    }
+    if (tid == 0) {
+        dst[row] = tmp[0];
+    }
 }
 
-void vec_dot_q5_K(__global const struct block_q5_K* x, const int ib, const int iqs, const __global float *yy, float *result) {
+__kernel void dequantize_mul_mat_vec_q3_K(__global const struct block_q3_K * xx, __local float* tmp, __global float* yy, __global float* dst, const int ncols) {
+    const uint16_t kmask1 = 0x0303;
+    const uint16_t kmask2 = 0x0f0f;
 
-    const int j  = iqs / 64;
+    const int row = get_group_id(0);
-    const int ir = (iqs - 64*j)/2;
-    const int is = 2*j;
 
-    __global const float   * y  = yy + 64*j + ir;
+    const int num_blocks_per_row = ncols / QK_K;
-    __global const uint8_t * ql = x[ib].qs + 32*j + ir;
+    const int ib0 = row*num_blocks_per_row;
-    __global const uint8_t * qh = x[ib].qh + ir;
 
-    const float dall = vload_half(0, &x[ib].d);
+    __global const struct block_q3_K * x = xx + ib0;
-    const float dmin = vload_half(0, &x[ib].dmin);
 
-    uint8_t sc, m;
+    const int tid = get_local_id(0)/K_QUANTS_PER_ITERATION;  // 0...31 or 0...16
-    get_scale_min_k4(is + 0, x[ib].scales, &sc, &m);
+    const int ix  = get_local_id(0)%K_QUANTS_PER_ITERATION;  // 0 or 0,1
-    const float d1 = dall * sc;
+
-    const float m1 = dmin * m;
+    const int n  = K_QUANTS_PER_ITERATION;               // iterations in the inner loop
-    get_scale_min_k4(is + 1, x[ib].scales, &sc, &m);
+    const int step = 16/K_QUANTS_PER_ITERATION;
-    const float d2 = dall * sc;
+    const int im = tid/step;                             // 0 or 1. 0 computes 0..., 1 computes 128...
-    const float m2 = dmin * m;
+    const int in = tid - step*im;                        // 0....15 or 0...7
+
+    const uint8_t m = 1 << (4*im);
+
+    const int l0 = n*in;                                 // 0...15 or 0...14 in steps of 2
+    const int q_offset =  32*im + l0;
+    const int y_offset = 128*im + l0;
+
+    uint16_t utmp[4];
+    const int8_t * s = (const int8_t *)utmp;
+
+    const uint16_t s_shift = 4*im;
+
+    tmp[16 * ix + tid] = 0;
+
+    for (int i = ix; i < num_blocks_per_row; i += K_QUANTS_PER_ITERATION) {
+
+        __global const float   * y  = yy + i * QK_K + y_offset;
+        __global const uint8_t * q = x[i].qs + q_offset;
+        __global const uint8_t * h = x[i].hmask + l0;
+
+        __global const uint16_t * a = (__global const uint16_t *)x[i].scales;
+        utmp[0] = ((a[0] >> s_shift) & kmask2) | (((a[4] >> (s_shift + 0)) & kmask1) << 4);
+        utmp[1] = ((a[1] >> s_shift) & kmask2) | (((a[5] >> (s_shift + 0)) & kmask1) << 4);
+        utmp[2] = ((a[2] >> s_shift) & kmask2) | (((a[4] >> (s_shift + 2)) & kmask1) << 4);
+        utmp[3] = ((a[3] >> s_shift) & kmask2) | (((a[5] >> (s_shift + 2)) & kmask1) << 4);
+
+        const float d = vload_half(0, &x[i].d);
+
+        float sum = 0;
+        for (int l = 0; l < n; ++l) {
+            sum += y[l+ 0] * (s[0] - 32) * (((q[l] >> 0) & 3) - (h[l] & (m << 0) ? 0 : 4))
+                 + y[l+32] * (s[2] - 32) * (((q[l] >> 2) & 3) - (h[l] & (m << 1) ? 0 : 4))
+                 + y[l+64] * (s[4] - 32) * (((q[l] >> 4) & 3) - (h[l] & (m << 2) ? 0 : 4))
+                 + y[l+96] * (s[6] - 32) * (((q[l] >> 6) & 3) - (h[l] & (m << 3) ? 0 : 4));
+            sum += y[l+16] * (s[1] - 32) * (((q[l+16] >> 0) & 3) - (h[l+16] & (m << 0) ? 0 : 4))
+                 + y[l+48] * (s[3] - 32) * (((q[l+16] >> 2) & 3) - (h[l+16] & (m << 1) ? 0 : 4))
+                 + y[l+80] * (s[5] - 32) * (((q[l+16] >> 4) & 3) - (h[l+16] & (m << 2) ? 0 : 4))
+                + y[l+112] * (s[7] - 32) * (((q[l+16] >> 6) & 3) - (h[l+16] & (m << 3) ? 0 : 4));
+        }
+        tmp[16 * ix + tid] += d * sum;
 
-    uint8_t hm  = 1 << is;
-    float sum = 0;
-    for (int k = 0; k < 4; ++k) {
-        sum += y[k +  0] * (d1 * ((ql[k] & 0xF) + (qh[k] & hm ? 16 : 0)) - m1);
     }
-    hm <<= 1;
-    for (int k = 0; k < 4; ++k) {
-        sum += y[k + 32] * (d2 * ((ql[k] >>  4) + (qh[k] & hm ? 16 : 0)) - m2);
-    }
-    *result = sum;
 
+    // sum up partial sums and write back result
+    barrier(CLK_LOCAL_MEM_FENCE);
+    for (int s=16; s>0; s>>=1) {
+        if (tid < s) {
+            tmp[tid] += tmp[tid + s];
+        }
+        barrier(CLK_LOCAL_MEM_FENCE);
+    }
+    if (tid == 0) {
+        dst[row] = tmp[0];
+    }
 }
 
-void vec_dot_q6_K(__global const struct block_q6_K* x, const int ib, const int iqs, const __global float *yy, float *result) {
+__kernel void dequantize_mul_mat_vec_q4_K(__global const struct block_q4_K * xx, __local float* tmp, __global float* yy, __global float* dst, const int ncols) {
 
+    //to rename it later, just to test now
+    const uint16_t kmask1 = 0x3f3f;
+    const uint16_t kmask2 = 0x0f0f;
+    const uint16_t kmask3 = 0xc0c0;
 
-    const int ip = iqs / 128;        // 0 or 1
+    const int row = get_group_id(0);
-    const int il = (iqs - 128*ip)/8; // 0...15
+    const int num_blocks_per_row = ncols / QK_K;
-    const int is = 8*ip;
+    const int ib0 = row*num_blocks_per_row;
 
-    __global const float * y = yy + 128*ip + il;
+    const int tid = get_local_id(0)/K_QUANTS_PER_ITERATION;  // 0...15
+    const int ix  = get_local_id(0)%K_QUANTS_PER_ITERATION;
 
-    const float d = vload_half(0, &x[ib].d);
+    const int step = 8/K_QUANTS_PER_ITERATION;
 
-    __global const uint8_t * ql = x[ib].ql + 64*ip + il;
+    const int il  = tid/step;     // 0...3
-    __global const uint8_t * qh = x[ib].qh + 32*ip + il;
+    const int ir  = tid - step*il;// 0...3
-    __global const int8_t  * sc = x[ib].scales + is;
+    const int n   = 2*K_QUANTS_PER_ITERATION;
 
-    *result = y[  0] * d * sc[0] * ((int8_t)((ql[ 0] & 0xF) | (((qh[ 0] >> 0) & 3) << 4)) - 32)
+    const int im = il/2;  // 0 or 1. 0 computes 0,32 + 128,160, 1 computes 64,96 + 192,224
-           + y[ 32] * d * sc[2] * ((int8_t)((ql[32] & 0xF) | (((qh[ 0] >> 2) & 3) << 4)) - 32)
+    const int in = il%2;
-           + y[ 64] * d * sc[4] * ((int8_t)((ql[ 0]  >> 4) | (((qh[ 0] >> 4) & 3) << 4)) - 32)
-           + y[ 96] * d * sc[6] * ((int8_t)((ql[32]  >> 4) | (((qh[ 0] >> 6) & 3) << 4)) - 32)
-           + y[ 16] * d * sc[1] * ((int8_t)((ql[16] & 0xF) | (((qh[16] >> 0) & 3) << 4)) - 32)
-           + y[ 48] * d * sc[3] * ((int8_t)((ql[48] & 0xF) | (((qh[16] >> 2) & 3) << 4)) - 32)
-           + y[ 80] * d * sc[5] * ((int8_t)((ql[16]  >> 4) | (((qh[16] >> 4) & 3) << 4)) - 32)
-           + y[112] * d * sc[7] * ((int8_t)((ql[48]  >> 4) | (((qh[16] >> 6) & 3) << 4)) - 32);
 
+    const int l0 = n*(2*ir + in);
+    const int q_offset = 32*im + l0;
+    const int y_offset = 64*im + l0;
+
+    uint16_t aux[4];
+    const uint8_t * sc = (const uint8_t *)aux;
+
+    __global const struct block_q4_K * x = xx + ib0;
+
+    tmp[16 * ix + tid] = 0;
+
+    for (int i = ix; i < num_blocks_per_row; i += K_QUANTS_PER_ITERATION) {
+
+        __global const uint8_t * q1 = x[i].qs + q_offset;
+        __global const uint8_t * q2 = q1 + 64;
+        __global const float   * y1 = yy + i*QK_K + y_offset;
+        __global const float   * y2 = y1 + 128;
+
+        const float dall = vload_half(0, &x[i].d);
+        const float dmin = vload_half(0, &x[i].dmin);
+
+        __global const uint16_t * a = (__global const uint16_t *)x[i].scales;
+        aux[0] = a[im+0] & kmask1;
+        aux[1] = a[im+2] & kmask1;
+        aux[2] = ((a[im+4] >> 0) & kmask2) | ((a[im+0] & kmask3) >> 2);
+        aux[3] = ((a[im+4] >> 4) & kmask2) | ((a[im+2] & kmask3) >> 2);
+
+        float4 s = (float4)(0.f);
+        float smin = 0;
+        for (int l = 0; l < n; ++l) {
+            s.x += y1[l] * (q1[l] & 0xF); s.y += y1[l+32] * (q1[l] >> 4);
+            s.z += y2[l] * (q2[l] & 0xF); s.w += y2[l+32] * (q2[l] >> 4);
+            smin += y1[l] * sc[2] + y1[l+32] * sc[3] + y2[l] * sc[6] + y2[l+32] * sc[7];
+        }
+        tmp[16 * ix + tid] += dall * (s.x * sc[0] + s.y * sc[1] + s.z * sc[4] + s.w * sc[5]) - dmin * smin;
+
+    }
+
+    // sum up partial sums and write back result
+    barrier(CLK_LOCAL_MEM_FENCE);
+    for (int s=16; s>0; s>>=1) {
+        if (tid < s) {
+            tmp[tid] += tmp[tid + s];
+        }
+        barrier(CLK_LOCAL_MEM_FENCE);
+    }
+    if (tid == 0) {
+        dst[row] = tmp[0];
+    }
+}
+
+__kernel void dequantize_mul_mat_vec_q5_K(__global const struct block_q5_K * xx, __local float* tmp, __global float* yy, __global float* dst, const int ncols) {
+
+    const uint16_t kmask1 = 0x3f3f;
+    const uint16_t kmask2 = 0x0f0f;
+    const uint16_t kmask3 = 0xc0c0;
+
+    const int row = get_group_id(0);
+    const int num_blocks_per_row = ncols / QK_K;
+    const int ib0 = row*num_blocks_per_row;
+
+    const int tid = get_local_id(0)/2;  // 0...15
+    const int ix  = get_local_id(0)%2;
+
+    const int il  = tid/4;     // 0...3
+    const int ir  = tid - 4*il;// 0...3
+    const int n   = 2;
+
+    const int im = il/2;  // 0 or 1. 0 computes 0,32 + 128,160, 1 computes 64,96 + 192,224
+    const int in = il%2;
+
+    const int l0 = n*(2*ir + in);
+    const int q_offset = 32*im + l0;
+    const int y_offset = 64*im + l0;
+
+    const uint8_t hm1  = 1 << (2*im);
+    const uint8_t hm2  = hm1 << 4;
+
+    uint16_t aux[4];
+    const uint8_t * sc = (const uint8_t *)aux;
+
+    __global const struct block_q5_K * x = xx + ib0;
+
+    tmp[16 * ix + tid] = 0;
+
+    for (int i = ix; i < num_blocks_per_row; i += 2) {
+
+        __global const uint8_t * ql1 = x[i].qs + q_offset;
+        __global const uint8_t * ql2 = ql1 + 64;
+        __global const uint8_t * qh  = x[i].qh + l0;
+        __global const float   * y1  = yy + i*QK_K + y_offset;
+        __global const float   * y2  = y1 + 128;
+
+        const float dall = vload_half(0, &x[i].d);
+        const float dmin = vload_half(0, &x[i].dmin);
+
+        __global const uint16_t * a = (__global const uint16_t *)x[i].scales;
+        aux[0] = a[im+0] & kmask1;
+        aux[1] = a[im+2] & kmask1;
+        aux[2] = ((a[im+4] >> 0) & kmask2) | ((a[im+0] & kmask3) >> 2);
+        aux[3] = ((a[im+4] >> 4) & kmask2) | ((a[im+2] & kmask3) >> 2);
+
+        float4 sum = (float4)(0.f);
+        float smin = 0;
+        for (int l = 0; l < n; ++l) {
+            sum.x += y1[l+ 0] * ((ql1[l+ 0] & 0xF) + (qh[l+ 0] & (hm1 << 0) ? 16 : 0))
+                   + y1[l+16] * ((ql1[l+16] & 0xF) + (qh[l+16] & (hm1 << 0) ? 16 : 0));
+            sum.y += y1[l+32] * ((ql1[l+ 0] >>  4) + (qh[l+ 0] & (hm1 << 1) ? 16 : 0))
+                   + y1[l+48] * ((ql1[l+16] >>  4) + (qh[l+16] & (hm1 << 1) ? 16 : 0));
+            sum.z += y2[l+ 0] * ((ql2[l+ 0] & 0xF) + (qh[l+ 0] & (hm2 << 0) ? 16 : 0))
+                   + y2[l+16] * ((ql2[l+16] & 0xF) + (qh[l+16] & (hm2 << 0) ? 16 : 0));
+            sum.w += y2[l+32] * ((ql2[l+ 0] >>  4) + (qh[l+ 0] & (hm2 << 1) ? 16 : 0))
+                   + y2[l+48] * ((ql2[l+16] >>  4) + (qh[l+16] & (hm2 << 1) ? 16 : 0));
+            smin += (y1[l] + y1[l+16]) * sc[2] + (y1[l+32] + y1[l+48]) * sc[3]
+                  + (y2[l] + y2[l+16]) * sc[6] + (y2[l+32] + y2[l+48]) * sc[7];
+        }
+        tmp[16 * ix + tid] += dall * (sum.x * sc[0] + sum.y * sc[1] + sum.z * sc[4] + sum.w * sc[5]) - dmin * smin;
+
+    }
+
+    // sum up partial sums and write back result
+    barrier(CLK_LOCAL_MEM_FENCE);
+    for (int s=16; s>0; s>>=1) {
+        if (tid < s) {
+            tmp[tid] += tmp[tid + s];
+        }
+        barrier(CLK_LOCAL_MEM_FENCE);
+    }
+    if (tid == 0) {
+        dst[row] = tmp[0];
+    }
+}
+
+__kernel void dequantize_mul_mat_vec_q6_K(__global const struct block_q6_K * xx, __local float* tmp, __global const float * yy, __global float * dst, const int ncols) {
+
+    const int row = get_group_id(0);
+
+    const int num_blocks_per_row = ncols / QK_K;
+    const int ib0 = row*num_blocks_per_row;
+
+    __global const struct block_q6_K * x = xx + ib0;
+
+    const int tid = get_local_id(0)/K_QUANTS_PER_ITERATION;  // 0...31 or 0...16
+    const int ix  = get_local_id(0)%K_QUANTS_PER_ITERATION;  // 0 or 0, 1
+
+    const int step = 16/K_QUANTS_PER_ITERATION;          // 16 or 8
+
+    const int im = tid/step;                             // 0 or 1. 0 computes 0..., 1 computes 128...
+    const int in = tid - step*im;                        // 0...15 or 0...7
+
+#if K_QUANTS_PER_ITERATION == 1
+    const int l0 = K_QUANTS_PER_ITERATION*in;            // 0...15
+    const int is = 0;
+#else
+    const int l0 = 4 * in;                               // 0, 4, 8, ..., 28
+    const int is = in / 4;
+#endif
+    const int ql_offset = 64*im + l0;
+    const int qh_offset = 32*im + l0;
+    const int s_offset  =  8*im + is;
+    const int y_offset = 128*im + l0;
+
+    tmp[16 * ix + tid] = 0; // partial sum for thread in warp
+
+    for (int i = ix; i < num_blocks_per_row; i += K_QUANTS_PER_ITERATION) {
+
+        __global const float   * y  = yy + i * QK_K + y_offset;
+        __global const uint8_t * ql = x[i].ql + ql_offset;
+        __global const uint8_t * qh = x[i].qh + qh_offset;
+        __global const int8_t  * s  = x[i].scales + s_offset;
+
+        const float d = vload_half(0, &x[i].d);
+
+#if K_QUANTS_PER_ITERATION == 1
+        float sum = y[ 0] * s[0] * d * ((int8_t)((ql[ 0] & 0xF) | ((qh[ 0] & 0x03) << 4)) - 32)
+                  + y[16] * s[1] * d * ((int8_t)((ql[16] & 0xF) | ((qh[16] & 0x03) << 4)) - 32)
+                  + y[32] * s[2] * d * ((int8_t)((ql[32] & 0xF) | ((qh[ 0] & 0x0c) << 2)) - 32)
+                  + y[48] * s[3] * d * ((int8_t)((ql[48] & 0xF) | ((qh[16] & 0x0c) << 2)) - 32)
+                  + y[64] * s[4] * d * ((int8_t)((ql[ 0]  >> 4) | ((qh[ 0] & 0x30) >> 0)) - 32)
+                  + y[80] * s[5] * d * ((int8_t)((ql[16]  >> 4) | ((qh[16] & 0x30) >> 0)) - 32)
+                  + y[96] * s[6] * d * ((int8_t)((ql[32]  >> 4) | ((qh[ 0] & 0xc0) >> 2)) - 32)
+                  +y[112] * s[7] * d * ((int8_t)((ql[48]  >> 4) | ((qh[16] & 0xc0) >> 2)) - 32);
+        tmp[16 * ix + tid] += sum;
+#else
+        float sum = 0;
+        for (int l = 0; l < 4; ++l) {
+            sum += y[l+ 0] * s[0] * d * ((int8_t)((ql[l+ 0] & 0xF) | (((qh[l] >> 0) & 3) << 4)) - 32)
+                 + y[l+32] * s[2] * d * ((int8_t)((ql[l+32] & 0xF) | (((qh[l] >> 2) & 3) << 4)) - 32)
+                 + y[l+64] * s[4] * d * ((int8_t)((ql[l+ 0]  >> 4) | (((qh[l] >> 4) & 3) << 4)) - 32)
+                 + y[l+96] * s[6] * d * ((int8_t)((ql[l+32]  >> 4) | (((qh[l] >> 6) & 3) << 4)) - 32);
+        }
+        tmp[16 * ix + tid] += sum;
+#endif
+
+    }
+
+    // sum up partial sums and write back result
+    barrier(CLK_LOCAL_MEM_FENCE);
+    for (int s=16; s>0; s>>=1) {
+        if (tid < s) {
+            tmp[tid] += tmp[tid + s];
+        }
+        barrier(CLK_LOCAL_MEM_FENCE);
+    }
+    if (tid == 0) {
+        dst[row] = tmp[0];
+    }
 }
 
 );
@@ -549,44 +781,6 @@ __kernel void KERNEL_NAME(__global X_TYPE* x, __local float* tmp, __global float
 }
 );
 
-std::string dequant_mul_mat_vec_k_template = MULTILINE_QUOTE(
-__kernel void KERNEL_NAME(__global X_TYPE* x, __local float* tmp, __global float* y, __global float* dst, const int ncols) {
-    const int block_size = get_local_size(0);
-    const int row = get_group_id(0);
-    const int tid = get_local_id(0);
-
-    const int iter_stride = 256;
-    const int vals_per_iter = iter_stride / block_size;
-    const int num_blocks_per_row = ncols / 256;
-    const int ib0 = row*num_blocks_per_row;
-
-    tmp[tid] = 0;
-
-    for (int i = 0; i < ncols; i += iter_stride) {
-        const int col = i + vals_per_iter*tid;
-        const int ib = ib0 + col/256; // x block index
-        const int iqs = col%256; // x quant index
-        const int iybs = col - col%256; // y block start index
-
-        // dequantize
-        float v;
-        DOT_KERNEL(x, ib, iqs, y + iybs, &v);
-        tmp[tid] += v;
-    }
-
-    // sum up partial sums and write back result
-    barrier(CLK_LOCAL_MEM_FENCE);
-    for (int s=block_size/2; s>0; s>>=1) {
-        if (tid < s) {
-            tmp[tid] += tmp[tid + s];
-        }
-        barrier(CLK_LOCAL_MEM_FENCE);
-    }
-    if (tid == 0) {
-        dst[row] = tmp[0];
-    }
-}
-);
 
 std::string mul_template = MULTILINE_QUOTE(
 __kernel void KERNEL_NAME(__global TYPE* x, const int x_offset, __global TYPE* y, const int y_offset, __global TYPE* dst, const int dst_offset, const int ky) {
@@ -649,18 +843,6 @@ std::array<std::string, 2> mul_str_values = {
     "mul_f32", "float"
 };
 
-std::array<std::string, 3> dmmv_k_str_keys = {
-    "KERNEL_NAME", "X_TYPE", "DOT_KERNEL"
-};
-
-std::array<std::string, 15> dmmv_k_str_values = {
-    "dequantize_mul_mat_vec_q2_K", "struct block_q2_K", "vec_dot_q2_K",
-    "dequantize_mul_mat_vec_q3_K", "struct block_q3_K", "vec_dot_q3_K",
-    "dequantize_mul_mat_vec_q4_K", "struct block_q4_K", "vec_dot_q4_K",
-    "dequantize_mul_mat_vec_q5_K", "struct block_q5_K", "vec_dot_q5_K",
-    "dequantize_mul_mat_vec_q6_K", "struct block_q6_K", "vec_dot_q6_K",
-};
-
 std::string& replace(std::string& s, const std::string& from, const std::string& to) {
     size_t pos = 0;
     while ((pos = s.find(from, pos)) != std::string::npos) {
@@ -673,6 +855,7 @@ std::string& replace(std::string& s, const std::string& from, const std::string&
 std::string generate_kernels() {
     std::stringstream src;
     src << program_source << '\n';
+    src << k_quants_source << '\n';
     for (size_t i = 0; i < dequant_str_values.size(); i += dequant_str_keys.size()) {
         std::string dequant_kernel = dequant_template;
         std::string dmmv_kernel = dequant_mul_mat_vec_template;
@@ -690,13 +873,6 @@ std::string generate_kernels() {
         }
         src << mul_kernel << '\n';
     }
-    for (size_t i = 0; i < dmmv_k_str_values.size(); i += dmmv_k_str_keys.size()) {
-        std::string dmmv_k_kernel = dequant_mul_mat_vec_k_template;
-        for (size_t j = 0; j < dmmv_k_str_keys.size(); j++) {
-            replace(dmmv_k_kernel, dmmv_k_str_keys[j], dmmv_k_str_values[i + j]);
-        }
-        src << dmmv_k_kernel << '\n';
-    }
 
     return src.str();
 }
@@ -729,10 +905,11 @@ static cl_program build_program_from_source(cl_context ctx, cl_device_id dev, co
         exit(1);
     }
 
-    const char* compile_opts = "-cl-mad-enable -cl-unsafe-math-optimizations -cl-finite-math-only -cl-fast-relaxed-math "
+    std::string compile_opts = "-cl-mad-enable -cl-unsafe-math-optimizations -cl-finite-math-only -cl-fast-relaxed-math "
-                               "-DQK4_0=32 -DQR4_0=2 -DQK4_1=32 -DQR4_1=2 -DQK5_0=32 -DQR5_0=2 -DQK5_1=32 -DQR5_1=2 -DQK8_0=32 -DQR8_0=1";
+                               "-DQK4_0=32 -DQR4_0=2 -DQK4_1=32 -DQR4_1=2 -DQK5_0=32 -DQR5_0=2 -DQK5_1=32 -DQR5_1=2 -DQK8_0=32 -DQR8_0=1 "
+                               "-DQK_K=256 -DK_QUANTS_PER_ITERATION=" + std::to_string(K_QUANTS_PER_ITERATION);
 
-    err = clBuildProgram(p, 0, NULL, compile_opts, NULL, NULL);
+    err = clBuildProgram(p, 0, NULL, compile_opts.c_str(), NULL, NULL);
     if(err < 0) {
 
         clGetProgramBuildInfo(p, dev, CL_PROGRAM_BUILD_LOG, 0, NULL, &log_size);

llama.cpp

@@ -777,7 +777,7 @@ static bool kv_cache_init(
 
 struct llama_context_params llama_context_default_params() {
     struct llama_context_params result = {
-        /*.seed                        =*/ -1,
+        /*.seed                        =*/ LLAMA_DEFAULT_SEED,
         /*.n_ctx                       =*/ 512,
         /*.n_batch                     =*/ 512,
         /*.gpu_layers                  =*/ 0,
@@ -2541,7 +2541,7 @@ struct llama_context * llama_new_context_with_model(
 
     llama_context * ctx = new llama_context(*model, model->vocab);
 
-    if (params.seed < 0) {
+    if (params.seed == LLAMA_DEFAULT_SEED) {
         params.seed = time(NULL);
     }
 
@@ -2974,8 +2974,8 @@ int llama_get_kv_cache_token_count(const struct llama_context * ctx) {
 
 #define LLAMA_MAX_RNG_STATE (64*1024)
 
-void llama_set_rng_seed(struct llama_context * ctx, int seed) {
+void llama_set_rng_seed(struct llama_context * ctx, uint32_t seed) {
-    if (seed < 0) {
+    if (seed == LLAMA_DEFAULT_SEED) {
         seed = time(NULL);
     }
     ctx->rng.seed(seed);

llama.h

@@ -46,6 +46,8 @@
 #define LLAMA_SESSION_MAGIC          LLAMA_FILE_MAGIC_GGSN
 #define LLAMA_SESSION_VERSION        1
 
+#define LLAMA_DEFAULT_SEED           0xFFFFFFFF
+
 #if defined(GGML_USE_CUBLAS) || defined(GGML_USE_CLBLAST) || defined(GGML_USE_METAL)
 // Defined when llama.cpp is compiled with support for offloading model layers to GPU.
 #define LLAMA_SUPPORTS_GPU_OFFLOAD
@@ -81,11 +83,11 @@ extern "C" {
     typedef void (*llama_progress_callback)(float progress, void *ctx);
 
    struct llama_context_params {
-        int seed;                              // RNG seed, -1 for random
+        uint32_t seed;                         // RNG seed, -1 for random
-        int n_ctx;                             // text context
+        int32_t  n_ctx;                        // text context
-        int n_batch;                           // prompt processing batch size
+        int32_t  n_batch;                      // prompt processing batch size
-        int n_gpu_layers;                      // number of layers to store in VRAM
+        int32_t  n_gpu_layers;                 // number of layers to store in VRAM
-        int main_gpu;                          // the GPU that is used for scratch and small tensors
+        int32_t  main_gpu;                     // the GPU that is used for scratch and small tensors
         float tensor_split[LLAMA_MAX_DEVICES]; // how to split layers across multiple GPUs
         // called with a progress value between 0 and 1, pass NULL to disable
         llama_progress_callback progress_callback;
@@ -196,7 +198,7 @@ extern "C" {
     LLAMA_API int llama_get_kv_cache_token_count(const struct llama_context * ctx);
 
     // Sets the current rng seed.
-    LLAMA_API void llama_set_rng_seed(struct llama_context * ctx, int seed);
+    LLAMA_API void llama_set_rng_seed(struct llama_context * ctx, uint32_t seed);
 
     // Returns the maximum size in bytes of the state (rng, logits, embedding
     // and kv_cache) - will often be smaller after compacting tokens