| 1 | #include "convert.cuh" |
| 2 | #include "dequantize.cuh" |
| 3 | |
| 4 | #include <cstdint> |
| 5 | |
| 6 | #define CUDA_Q8_0_NE_ALIGN 2048 |
| 7 | |
| 8 | template <int qk, int qr, dequantize_kernel_t dequantize_kernel, typename dst_t> |
| 9 | static __global__ void dequantize_block(const void * __restrict__ vx, dst_t * __restrict__ y, |
| 10 | const int64_t ne00, const int64_t ne01, const int64_t ne02, |
| 11 | const int64_t s01, const int64_t s02, const int64_t s03) { |
| 12 | const int64_t i00 = 2 * (int64_t(blockDim.x)*blockIdx.x + threadIdx.x); |
| 13 | |
| 14 | if (i00 >= ne00) { |
| 15 | return; |
| 16 | } |
| 17 | |
| 18 | const int64_t i01 = blockIdx.y; |
| 19 | const int64_t i02 = blockIdx.z % ne02; |
| 20 | const int64_t i03 = blockIdx.z / ne02; |
| 21 | |
| 22 | const int64_t ibx0 = i03*s03 + i02*s02 + i01*s01; |
| 23 | |
| 24 | const int64_t ib = ibx0 + i00/qk; // block index |
| 25 | const int64_t iqs = (i00%qk)/qr; // quant index |
| 26 | const int64_t iybs = i00 - i00%qk; // y block start index |
| 27 | const int64_t y_offset = qr == 1 ? 1 : qk/2; |
| 28 | |
| 29 | // dequantize |
| 30 | float2 v; |
| 31 | dequantize_kernel(vx, ib, iqs, v); |
| 32 | |
| 33 | const int64_t iy0 = ((i03*ne02 + i02)*ne01 + i01)*ne00 + iybs + iqs; |
| 34 | y[iy0 + 0] = ggml_cuda_cast<dst_t>(v.x); |
| 35 | y[iy0 + y_offset] = ggml_cuda_cast<dst_t>(v.y); |
| 36 | } |
| 37 | |
| 38 | template <bool need_check> |
| 39 | static __global__ void dequantize_block_q8_0_f16(const void * __restrict__ vx, half * __restrict__ y, const int64_t k) { |
| 40 | #if __CUDA_ARCH__ >= GGML_CUDA_CC_PASCAL |
| 41 | constexpr int nint = CUDA_Q8_0_NE_ALIGN/sizeof(int) + WARP_SIZE; |
| 42 | |
| 43 | const int64_t i0 = CUDA_Q8_0_NE_ALIGN*blockIdx.x; |
| 44 | const int * x0 = ((int *) vx) + blockIdx.x * nint; |
| 45 | half2 * y2 = (half2 *) (y + i0); |
| 46 | |
| 47 | __shared__ int vals[nint]; |
| 48 | |
| 49 | #pragma unroll |
| 50 | for (int ix0 = 0; ix0 < nint; ix0 += WARP_SIZE) { |
| 51 | if (need_check && i0*sizeof(block_q8_0)/QK8_0 + sizeof(int)*(ix0 + threadIdx.x) >= k*sizeof(block_q8_0)/QK8_0) { |
| 52 | break; |
| 53 | } |
| 54 | |
| 55 | const int ix = ix0 + threadIdx.x; |
| 56 | vals[ix] = x0[ix]; |
| 57 | } |
| 58 | |
| 59 | __syncthreads(); |
| 60 | |
| 61 | #pragma unroll |
| 62 | for (int iy = 0; iy < CUDA_Q8_0_NE_ALIGN; iy += 2*WARP_SIZE) { |
| 63 | if (need_check && i0 + iy + 2*threadIdx.x >= k) { |
| 64 | return; |
| 65 | } |
| 66 | |
| 67 | const half * b0 = ((const half *) vals) + (sizeof(block_q8_0)/sizeof(half)) * ((iy + 2*threadIdx.x)/QK8_0); |
| 68 | const half d = *b0; |
| 69 | const char2 qs = ((const char2 *) (b0 + 1))[threadIdx.x % (QK8_0/2)]; |
| 70 | |
| 71 | y2[iy/2 + threadIdx.x] = __hmul2(make_half2(qs.x, qs.y), __half2half2(d)); |
| 72 | } |
| 73 | #else |
| 74 | GGML_UNUSED_VARS(vx, y, k); |
| 75 | NO_DEVICE_CODE; |
| 76 | #endif // __CUDA_ARCH__ >= GGML_CUDA_CC_PASCAL |
| 77 | } |
| 78 | |
| 79 | template<typename dst_t> |
| 80 | static __global__ void dequantize_block_q4_0(const void * __restrict__ vx, dst_t * __restrict__ yy, int nb32) { |
| 81 | |
| 82 | const int64_t i = blockIdx.x; |
| 83 | |
| 84 | // assume 32 threads |
| 85 | const int64_t tid = threadIdx.x; |
| 86 | const int64_t il = tid/8; |
| 87 | const int64_t ir = tid%8; |
| 88 | const int64_t ib = 8*i + ir; |
| 89 | if (ib >= nb32) { |
| 90 | return; |
| 91 | } |
| 92 | |
| 93 | dst_t * y = yy + 256*i + 32*ir + 4*il; |
| 94 | |
| 95 | const block_q4_0 * x = (const block_q4_0 *)vx + ib; |
| 96 | const float d = __half2float(x->d); |
| 97 | const float dm = -8*d; |
| 98 | |
| 99 | const uint8_t * q = x->qs + 4*il; |
| 100 | |
| 101 | for (int l = 0; l < 4; ++l) { |
| 102 | y[l+ 0] = d * (q[l] & 0xF) + dm; |
| 103 | y[l+16] = d * (q[l] >> 4) + dm; |
| 104 | } |
| 105 | } |
| 106 | |
| 107 | template<typename dst_t> |
| 108 | static __global__ void dequantize_block_q4_1(const void * __restrict__ vx, dst_t * __restrict__ yy, int nb32) { |
| 109 | |
| 110 | const int64_t i = blockIdx.x; |
| 111 | |
| 112 | // assume 32 threads |
| 113 | const int64_t tid = threadIdx.x; |
| 114 | const int64_t il = tid/8; |
| 115 | const int64_t ir = tid%8; |
| 116 | const int64_t ib = 8*i + ir; |
| 117 | if (ib >= nb32) { |
| 118 | return; |
| 119 | } |
| 120 | |
| 121 | dst_t * y = yy + 256*i + 32*ir + 4*il; |
| 122 | |
| 123 | const block_q4_1 * x = (const block_q4_1 *)vx + ib; |
| 124 | const float2 d = __half22float2(x->dm); |
| 125 | |
| 126 | const uint8_t * q = x->qs + 4*il; |
| 127 | |
| 128 | for (int l = 0; l < 4; ++l) { |
| 129 | y[l+ 0] = d.x * (q[l] & 0xF) + d.y; |
| 130 | y[l+16] = d.x * (q[l] >> 4) + d.y; |
| 131 | } |
| 132 | } |
| 133 | |
| 134 | //================================== k-quants |
| 135 | |
| 136 | template<typename dst_t> |
| 137 | static __global__ void dequantize_block_q2_K(const void * __restrict__ vx, dst_t * __restrict__ yy) { |
| 138 | |
| 139 | const int64_t i = blockIdx.x; |
| 140 | const block_q2_K * x = (const block_q2_K *) vx; |
| 141 | |
| 142 | const int64_t tid = threadIdx.x; |
| 143 | const int64_t n = tid/32; |
| 144 | const int64_t l = tid - 32*n; |
| 145 | const int64_t is = 8*n + l/16; |
| 146 | |
| 147 | const uint8_t q = x[i].qs[32*n + l]; |
| 148 | dst_t * y = yy + i*QK_K + 128*n; |
| 149 | |
| 150 | float dall = __low2half(x[i].dm); |
| 151 | float dmin = __high2half(x[i].dm); |
| 152 | y[l+ 0] = dall * (x[i].scales[is+0] & 0xF) * ((q >> 0) & 3) - dmin * (x[i].scales[is+0] >> 4); |
| 153 | y[l+32] = dall * (x[i].scales[is+2] & 0xF) * ((q >> 2) & 3) - dmin * (x[i].scales[is+2] >> 4); |
| 154 | y[l+64] = dall * (x[i].scales[is+4] & 0xF) * ((q >> 4) & 3) - dmin * (x[i].scales[is+4] >> 4); |
| 155 | y[l+96] = dall * (x[i].scales[is+6] & 0xF) * ((q >> 6) & 3) - dmin * (x[i].scales[is+6] >> 4); |
| 156 | } |
| 157 | |
| 158 | template<typename dst_t> |
| 159 | static __global__ void dequantize_block_q3_K(const void * __restrict__ vx, dst_t * __restrict__ yy) { |
| 160 | |
| 161 | const int64_t i = blockIdx.x; |
| 162 | const block_q3_K * x = (const block_q3_K *) vx; |
| 163 | |
| 164 | const int64_t r = threadIdx.x/4; |
| 165 | const int64_t tid = r/2; |
| 166 | const int64_t is0 = r%2; |
| 167 | const int64_t l0 = 16*is0 + 4*(threadIdx.x%4); |
| 168 | const int64_t n = tid / 4; |
| 169 | const int64_t j = tid - 4*n; |
| 170 | |
| 171 | uint8_t m = 1 << (4*n + j); |
| 172 | int64_t is = 8*n + 2*j + is0; |
| 173 | int shift = 2*j; |
| 174 | |
| 175 | int8_t us = is < 4 ? (x[i].scales[is-0] & 0xF) | (((x[i].scales[is+8] >> 0) & 3) << 4) : |
| 176 | is < 8 ? (x[i].scales[is-0] & 0xF) | (((x[i].scales[is+4] >> 2) & 3) << 4) : |
| 177 | is < 12 ? (x[i].scales[is-8] >> 4) | (((x[i].scales[is+0] >> 4) & 3) << 4) : |
| 178 | (x[i].scales[is-8] >> 4) | (((x[i].scales[is-4] >> 6) & 3) << 4); |
| 179 | float d_all = x[i].d; |
| 180 | float dl = d_all * (us - 32); |
| 181 | |
| 182 | dst_t * y = yy + i*QK_K + 128*n + 32*j; |
| 183 | const uint8_t * q = x[i].qs + 32*n; |
| 184 | const uint8_t * hm = x[i].hmask; |
| 185 | |
| 186 | for (int l = l0; l < l0+4; ++l) y[l] = dl * ((int8_t)((q[l] >> shift) & 3) - ((hm[l] & m) ? 0 : 4)); |
| 187 | } |
| 188 | |
| 189 | static inline __device__ void get_scale_min_k4(int j, const uint8_t * q, uint8_t & d, uint8_t & m) { |
| 190 | if (j < 4) { |
| 191 | d = q[j] & 63; m = q[j + 4] & 63; |
| 192 | } else { |
| 193 | d = (q[j+4] & 0xF) | ((q[j-4] >> 6) << 4); |
| 194 | m = (q[j+4] >> 4) | ((q[j-0] >> 6) << 4); |
| 195 | } |
| 196 | } |
| 197 | |
| 198 | template<typename dst_t> |
| 199 | static __global__ void dequantize_block_q4_K(const void * __restrict__ vx, dst_t * __restrict__ yy) { |
| 200 | const block_q4_K * x = (const block_q4_K *) vx; |
| 201 | |
| 202 | const int64_t i = blockIdx.x; |
| 203 | |
| 204 | // assume 32 threads |
| 205 | const int64_t tid = threadIdx.x; |
| 206 | const int64_t il = tid/8; |
| 207 | const int64_t ir = tid%8; |
| 208 | const int64_t is = 2*il; |
| 209 | const int64_t n = 4; |
| 210 | |
| 211 | dst_t * y = yy + i*QK_K + 64*il + n*ir; |
| 212 | |
| 213 | const float dall = __low2half(x[i].dm); |
| 214 | const float dmin = __high2half(x[i].dm); |
| 215 | |
| 216 | const uint8_t * q = x[i].qs + 32*il + n*ir; |
| 217 | |
| 218 | uint8_t sc, m; |
| 219 | get_scale_min_k4(is + 0, x[i].scales, sc, m); |
| 220 | const float d1 = dall * sc; const float m1 = dmin * m; |
| 221 | get_scale_min_k4(is + 1, x[i].scales, sc, m); |
| 222 | const float d2 = dall * sc; const float m2 = dmin * m; |
| 223 | for (int l = 0; l < n; ++l) { |
| 224 | y[l + 0] = d1 * (q[l] & 0xF) - m1; |
| 225 | y[l +32] = d2 * (q[l] >> 4) - m2; |
| 226 | } |
| 227 | } |
| 228 | |
| 229 | template<typename dst_t> |
| 230 | static __global__ void dequantize_block_q5_K(const void * __restrict__ vx, dst_t * __restrict__ yy) { |
| 231 | const block_q5_K * x = (const block_q5_K *) vx; |
| 232 | |
| 233 | const int64_t i = blockIdx.x; |
| 234 | |
| 235 | // assume 64 threads - this is very slightly better than the one below |
| 236 | const int64_t tid = threadIdx.x; |
| 237 | const int64_t il = tid/16; // il is in 0...3 |
| 238 | const int64_t ir = tid%16; // ir is in 0...15 |
| 239 | const int64_t is = 2*il; // is is in 0...6 |
| 240 | |
| 241 | dst_t * y = yy + i*QK_K + 64*il + 2*ir; |
| 242 | |
| 243 | const float dall = __low2half(x[i].dm); |
| 244 | const float dmin = __high2half(x[i].dm); |
| 245 | |
| 246 | const uint8_t * ql = x[i].qs + 32*il + 2*ir; |
| 247 | const uint8_t * qh = x[i].qh + 2*ir; |
| 248 | |
| 249 | uint8_t sc, m; |
| 250 | get_scale_min_k4(is + 0, x[i].scales, sc, m); |
| 251 | const float d1 = dall * sc; const float m1 = dmin * m; |
| 252 | get_scale_min_k4(is + 1, x[i].scales, sc, m); |
| 253 | const float d2 = dall * sc; const float m2 = dmin * m; |
| 254 | |
| 255 | uint8_t hm = 1 << (2*il); |
| 256 | y[ 0] = d1 * ((ql[ 0] & 0xF) + (qh[ 0] & hm ? 16 : 0)) - m1; |
| 257 | y[ 1] = d1 * ((ql[ 1] & 0xF) + (qh[ 1] & hm ? 16 : 0)) - m1; |
| 258 | hm <<= 1; |
| 259 | y[32] = d2 * ((ql[ 0] >> 4) + (qh[ 0] & hm ? 16 : 0)) - m2; |
| 260 | y[33] = d2 * ((ql[ 1] >> 4) + (qh[ 1] & hm ? 16 : 0)) - m2; |
| 261 | } |
| 262 | |
| 263 | template<typename dst_t> |
| 264 | static __global__ void dequantize_block_q6_K(const void * __restrict__ vx, dst_t * __restrict__ yy) { |
| 265 | const block_q6_K * x = (const block_q6_K *) vx; |
| 266 | |
| 267 | const int64_t i = blockIdx.x; |
| 268 | |
| 269 | // assume 64 threads - this is very slightly better than the one below |
| 270 | const int64_t tid = threadIdx.x; |
| 271 | const int64_t ip = tid/32; // ip is 0 or 1 |
| 272 | const int64_t il = tid - 32*ip; // 0...32 |
| 273 | const int64_t is = 8*ip + il/16; |
| 274 | |
| 275 | dst_t * y = yy + i*QK_K + 128*ip + il; |
| 276 | |
| 277 | const float d = x[i].d; |
| 278 | |
| 279 | const uint8_t * ql = x[i].ql + 64*ip + il; |
| 280 | const uint8_t qh = x[i].qh[32*ip + il]; |
| 281 | const int8_t * sc = x[i].scales + is; |
| 282 | |
| 283 | y[ 0] = d * sc[0] * ((int8_t)((ql[ 0] & 0xF) | (((qh >> 0) & 3) << 4)) - 32); |
| 284 | y[32] = d * sc[2] * ((int8_t)((ql[32] & 0xF) | (((qh >> 2) & 3) << 4)) - 32); |
| 285 | y[64] = d * sc[4] * ((int8_t)((ql[ 0] >> 4) | (((qh >> 4) & 3) << 4)) - 32); |
| 286 | y[96] = d * sc[6] * ((int8_t)((ql[32] >> 4) | (((qh >> 6) & 3) << 4)) - 32); |
| 287 | } |
| 288 | |
| 289 | template<typename dst_t> |
| 290 | static __global__ void dequantize_block_iq2_xxs(const void * __restrict__ vx, dst_t * __restrict__ yy) { |
| 291 | |
| 292 | const int64_t i = blockIdx.x; |
| 293 | const block_iq2_xxs * x = (const block_iq2_xxs *) vx; |
| 294 | |
| 295 | const int64_t tid = threadIdx.x; |
| 296 | const int64_t il = tid/8; // 0...3 |
| 297 | const int64_t ib = tid%8; // 0...7 |
| 298 | dst_t * y = yy + i*QK_K + 32*ib + 8*il; |
| 299 | const uint16_t * q2 = x[i].qs + 4*ib; |
| 300 | const uint8_t * aux8 = (const uint8_t *)q2; |
| 301 | const uint8_t * grid = (const uint8_t *)(iq2xxs_grid + aux8[il]); |
| 302 | const uint32_t aux32 = q2[2] | (q2[3] << 16); |
| 303 | const float d = (float)x[i].d * (0.5f + (aux32 >> 28)) * 0.25f; |
| 304 | const uint8_t signs = ksigns_iq2xs[(aux32 >> 7*il) & 127]; |
| 305 | for (int j = 0; j < 8; ++j) y[j] = d * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f); |
| 306 | } |
| 307 | |
| 308 | template<typename dst_t> |
| 309 | static __global__ void dequantize_block_iq2_xs(const void * __restrict__ vx, dst_t * __restrict__ yy) { |
| 310 | |
| 311 | const int64_t i = blockIdx.x; |
| 312 | const block_iq2_xs * x = (const block_iq2_xs *) vx; |
| 313 | |
| 314 | const int64_t tid = threadIdx.x; |
| 315 | const int64_t il = tid/8; // 0...3 |
| 316 | const int64_t ib = tid%8; // 0...7 |
| 317 | dst_t * y = yy + i*QK_K + 32*ib + 8*il; |
| 318 | const uint16_t * q2 = x[i].qs + 4*ib; |
| 319 | const uint8_t * grid = (const uint8_t *)(iq2xs_grid + (q2[il] & 511)); |
| 320 | const float d = (float)x[i].d * (0.5f + ((x[i].scales[ib] >> 4*(il/2)) & 0xf)) * 0.25f; |
| 321 | const uint8_t signs = ksigns_iq2xs[q2[il] >> 9]; |
| 322 | for (int j = 0; j < 8; ++j) y[j] = d * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f); |
| 323 | } |
| 324 | |
| 325 | template<typename dst_t> |
| 326 | static __global__ void dequantize_block_iq2_s(const void * __restrict__ vx, dst_t * __restrict__ yy) { |
| 327 | |
| 328 | const int64_t i = blockIdx.x; |
| 329 | const block_iq2_s * x = (const block_iq2_s *) vx; |
| 330 | |
| 331 | const int64_t tid = threadIdx.x; |
| 332 | const int64_t il = tid/8; // 0...3 |
| 333 | const int64_t ib = tid%8; // 0...7 |
| 334 | dst_t * y = yy + i*QK_K + 32*ib + 8*il; |
| 335 | const uint8_t * grid = (const uint8_t *)(iq2s_grid + (x[i].qs[4*ib+il] | ((x[i].qh[ib] << (8-2*il)) & 0x300))); |
| 336 | const float d = (float)x[i].d * (0.5f + ((x[i].scales[ib] >> 4*(il/2)) & 0xf)) * 0.25f; |
| 337 | const uint8_t signs = x[i].qs[QK_K/8+4*ib+il]; |
| 338 | for (int j = 0; j < 8; ++j) y[j] = d * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f); |
| 339 | } |
| 340 | |
| 341 | template<typename dst_t> |
| 342 | static __global__ void dequantize_block_iq3_xxs(const void * __restrict__ vx, dst_t * __restrict__ yy) { |
| 343 | |
| 344 | const int64_t i = blockIdx.x; |
| 345 | const block_iq3_xxs * x = (const block_iq3_xxs *) vx; |
| 346 | |
| 347 | const int64_t tid = threadIdx.x; |
| 348 | const int64_t il = tid/8; // 0...3 |
| 349 | const int64_t ib = tid%8; // 0...7 |
| 350 | dst_t * y = yy + i*QK_K + 32*ib + 8*il; |
| 351 | const uint8_t * q3 = x[i].qs + 8*ib; |
| 352 | const uint16_t * gas = (const uint16_t *)(x[i].qs + QK_K/4) + 2*ib; |
| 353 | const uint8_t * grid1 = (const uint8_t *)(iq3xxs_grid + q3[2*il+0]); |
| 354 | const uint8_t * grid2 = (const uint8_t *)(iq3xxs_grid + q3[2*il+1]); |
| 355 | const uint32_t aux32 = gas[0] | (gas[1] << 16); |
| 356 | const float d = (float)x[i].d * (0.5f + (aux32 >> 28)) * 0.5f; |
| 357 | const uint8_t signs = ksigns_iq2xs[(aux32 >> 7*il) & 127]; |
| 358 | for (int j = 0; j < 4; ++j) { |
| 359 | y[j+0] = d * grid1[j] * (signs & kmask_iq2xs[j+0] ? -1.f : 1.f); |
| 360 | y[j+4] = d * grid2[j] * (signs & kmask_iq2xs[j+4] ? -1.f : 1.f); |
| 361 | } |
| 362 | } |
| 363 | |
| 364 | template<typename dst_t> |
| 365 | static __global__ void dequantize_block_iq3_s(const void * __restrict__ vx, dst_t * __restrict__ yy) { |
| 366 | |
| 367 | const int64_t i = blockIdx.x; |
| 368 | const block_iq3_s * x = (const block_iq3_s *) vx; |
| 369 | |
| 370 | const int64_t tid = threadIdx.x; |
| 371 | const int64_t il = tid/8; // 0...3 |
| 372 | const int64_t ib = tid%8; // 0...7 |
| 373 | dst_t * y = yy + i*QK_K + 32*ib + 8*il; |
| 374 | const uint8_t * qs = x[i].qs + 8*ib; |
| 375 | const uint8_t * grid1 = (const uint8_t *)(iq3s_grid + (qs[2*il+0] | ((x[i].qh[ib] << (8-2*il)) & 256))); |
| 376 | const uint8_t * grid2 = (const uint8_t *)(iq3s_grid + (qs[2*il+1] | ((x[i].qh[ib] << (7-2*il)) & 256))); |
| 377 | const float d = (float)x[i].d * (1 + 2*((x[i].scales[ib/2] >> 4*(ib%2)) & 0xf)); |
| 378 | const uint8_t signs = x[i].signs[4*ib + il]; |
| 379 | for (int j = 0; j < 4; ++j) { |
| 380 | y[j+0] = d * grid1[j] * (signs & kmask_iq2xs[j+0] ? -1.f : 1.f); |
| 381 | y[j+4] = d * grid2[j] * (signs & kmask_iq2xs[j+4] ? -1.f : 1.f); |
| 382 | } |
| 383 | } |
| 384 | |
| 385 | template<typename dst_t> |
| 386 | static __global__ void dequantize_block_iq1_s(const void * __restrict__ vx, dst_t * __restrict__ yy) { |
| 387 | |
| 388 | const int64_t i = blockIdx.x; |
| 389 | const block_iq1_s * x = (const block_iq1_s *) vx; |
| 390 | |
| 391 | const int64_t tid = threadIdx.x; |
| 392 | const int64_t il = tid/8; // 0...3 |
| 393 | const int64_t ib = tid%8; // 0...7 |
| 394 | dst_t * y = yy + i*QK_K + 32*ib + 8*il; |
| 395 | const float delta = x[i].qh[ib] & 0x8000 ? -1 - IQ1S_DELTA : -1 + IQ1S_DELTA; |
| 396 | const float d = (float)x[i].d * (2*((x[i].qh[ib] >> 12) & 7) + 1); |
| 397 | uint32_t grid32[2]; const int8_t * q = (const int8_t *)grid32; |
| 398 | grid32[0] = iq1s_grid_gpu[x[i].qs[4*ib+il] | (((x[i].qh[ib] >> 3*il) & 7) << 8)]; |
| 399 | grid32[1] = (grid32[0] >> 4) & 0x0f0f0f0f; |
| 400 | grid32[0] &= 0x0f0f0f0f; |
| 401 | for (int j = 0; j < 8; ++j) { |
| 402 | y[j] = d * (q[j] + delta); |
| 403 | } |
| 404 | } |
| 405 | |
| 406 | template<typename dst_t> |
| 407 | static __global__ void dequantize_block_iq1_m(const void * __restrict__ vx, dst_t * __restrict__ yy) { |
| 408 | |
| 409 | const int64_t i = blockIdx.x; |
| 410 | const block_iq1_m * x = (const block_iq1_m *) vx; |
| 411 | |
| 412 | const int64_t tid = threadIdx.x; |
| 413 | const int64_t il = tid/8; // 0...3 |
| 414 | const int64_t ib = tid%8; // 0...7 |
| 415 | dst_t * y = yy + i*QK_K + 32*ib + 8*il; |
| 416 | const uint16_t * sc = (const uint16_t *)x[i].scales; |
| 417 | iq1m_scale_t scale; |
| 418 | scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000); |
| 419 | const int64_t ib16 = 2*ib + il/2; // sc[ib16/4] >> 3*(ib16%4) -> sc[ib/2] >> 3*((2*ib+il/2)%4); |
| 420 | const float d = (float)scale.f16 * (2*((sc[ib16/4] >> 3*(ib16%4)) & 0x7) + 1); |
| 421 | const float delta = x[i].qh[2*ib+il/2] & (0x08 << 4*(il%2)) ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA; |
| 422 | uint32_t grid32[2]; const int8_t * q = (const int8_t *)grid32; |
| 423 | grid32[0] = iq1s_grid_gpu[x[i].qs[4*ib+il] | (((x[i].qh[2*ib+il/2] >> 4*(il%2)) & 7) << 8)]; |
| 424 | grid32[1] = (grid32[0] >> 4) & 0x0f0f0f0f; |
| 425 | grid32[0] &= 0x0f0f0f0f; |
| 426 | for (int j = 0; j < 8; ++j) { |
| 427 | y[j] = d * (q[j] + delta); |
| 428 | } |
| 429 | } |
| 430 | |
| 431 | template<typename dst_t> |
| 432 | static __global__ void dequantize_block_iq4_nl(const void * __restrict__ vx, dst_t * __restrict__ yy) { |
| 433 | |
| 434 | const int64_t i = blockIdx.x; |
| 435 | const block_iq4_nl * x = (const block_iq4_nl *) vx + i*(QK_K/QK4_NL); |
| 436 | |
| 437 | const int64_t tid = threadIdx.x; |
| 438 | const int64_t il = tid/8; // 0...3 |
| 439 | const int64_t ib = tid%8; // 0...7 |
| 440 | dst_t * y = yy + i*QK_K + 32*ib + 4*il; |
| 441 | const uint8_t * q4 = x[ib].qs + 4*il; |
| 442 | const float d = (float)x[ib].d; |
| 443 | for (int j = 0; j < 4; ++j) { |
| 444 | y[j+ 0] = d * kvalues_iq4nl[q4[j] & 0xf]; |
| 445 | y[j+16] = d * kvalues_iq4nl[q4[j] >> 4]; |
| 446 | } |
| 447 | } |
| 448 | |
| 449 | template<typename dst_t> |
| 450 | static __global__ void dequantize_block_iq4_xs(const void * __restrict__ vx, dst_t * __restrict__ yy) { |
| 451 | const int64_t i = blockIdx.x; |
| 452 | const block_iq4_xs * x = (const block_iq4_xs *)vx; |
| 453 | |
| 454 | const int64_t tid = threadIdx.x; |
| 455 | const int64_t il = tid/8; // 0...3 |
| 456 | const int64_t ib = tid%8; // 0...7 |
| 457 | dst_t * y = yy + i*QK_K + 32*ib + 4*il; |
| 458 | const uint8_t * q4 = x[i].qs + 16*ib + 4*il; |
| 459 | const float d = (float)x[i].d * ((((x[i].scales_l[ib/2] >> 4*(ib%2)) & 0xf) | (((x[i].scales_h >> 2*ib) & 3) << 4)) - 32); |
| 460 | for (int j = 0; j < 4; ++j) { |
| 461 | y[j+ 0] = d * kvalues_iq4nl[q4[j] & 0xf]; |
| 462 | y[j+16] = d * kvalues_iq4nl[q4[j] >> 4]; |
| 463 | } |
| 464 | } |
| 465 | |
| 466 | template<typename dst_t> |
| 467 | static __global__ void dequantize_block_mxfp4(const void * __restrict__ vx, dst_t * __restrict__ yy) { |
| 468 | |
| 469 | const int64_t i = blockIdx.x; |
| 470 | const block_mxfp4 * x = (const block_mxfp4 *) vx + i*(QK_K/QK_MXFP4); |
| 471 | |
| 472 | const int64_t tid = threadIdx.x; |
| 473 | const int64_t il = tid/8; // 0...3 |
| 474 | const int64_t ib = tid%8; // 0...7 |
| 475 | dst_t * y = yy + i*QK_K + 32*ib + 4*il; |
| 476 | const uint8_t * q4 = x[ib].qs + 4*il; |
| 477 | const float d = ggml_cuda_e8m0_to_fp32(x[ib].e); |
| 478 | for (int j = 0; j < 4; ++j) { |
| 479 | y[j+ 0] = d * kvalues_mxfp4[q4[j] & 0xf]*0.5f; |
| 480 | y[j+16] = d * kvalues_mxfp4[q4[j] >> 4]*0.5f; |
| 481 | } |
| 482 | } |
| 483 | |
| 484 | template <int qk, int qr, dequantize_kernel_t dequantize_kernel, typename dst_t> |
| 485 | static void dequantize_block_cuda(const void * vx, dst_t * y, |
| 486 | const int64_t ne00, const int64_t ne01, const int64_t ne02, const int64_t ne03, |
| 487 | const int64_t s01, const int64_t s02, const int64_t s03, cudaStream_t stream) { |
| 488 | const dim3 num_blocks((ne00 + 2*CUDA_DEQUANTIZE_BLOCK_SIZE - 1) / (2*CUDA_DEQUANTIZE_BLOCK_SIZE), ne01, ne02*ne03); |
| 489 | dequantize_block<qk, qr, dequantize_kernel><<<gridDim: num_blocks, CUDA_DEQUANTIZE_BLOCK_SIZE, sharedMem: 0, stream>>> |
| 490 | (vx, y, ne00, ne01, ne02, s01, s02, s03); |
| 491 | } |
| 492 | |
| 493 | template <int qk, int qr, dequantize_kernel_t dequantize_kernel, typename dst_t> |
| 494 | static void dequantize_block_cont_cuda(const void * __restrict__ vx, dst_t * __restrict__ y, const int64_t k, cudaStream_t stream) { |
| 495 | dequantize_block_cuda<qk, qr, dequantize_kernel, dst_t>(vx, y, k, 1, 1, 1, k/qk, k/qk, k/qk, stream); |
| 496 | } |
| 497 | |
| 498 | static void dequantize_block_q8_0_f16_cuda(const void * __restrict__ vx, half * __restrict__ y, const int64_t k, cudaStream_t stream) { |
| 499 | const int num_blocks = (k + CUDA_Q8_0_NE_ALIGN - 1) / CUDA_Q8_0_NE_ALIGN; |
| 500 | if (k % CUDA_Q8_0_NE_ALIGN == 0) { |
| 501 | const bool need_check = false; |
| 502 | dequantize_block_q8_0_f16<need_check><<<gridDim: num_blocks, WARP_SIZE, sharedMem: 0, stream>>>(vx, y, k); |
| 503 | } else { |
| 504 | const bool need_check = true; |
| 505 | dequantize_block_q8_0_f16<need_check><<<gridDim: num_blocks, WARP_SIZE, sharedMem: 0, stream>>>(vx, y, k); |
| 506 | } |
| 507 | } |
| 508 | |
| 509 | template<typename dst_t> |
| 510 | static void dequantize_row_q2_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { |
| 511 | const int nb = k / QK_K; |
| 512 | dequantize_block_q2_K<<<gridDim: nb, blockDim: 64, sharedMem: 0, stream>>>(vx, y); |
| 513 | } |
| 514 | |
| 515 | template<typename dst_t> |
| 516 | static void dequantize_row_q3_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { |
| 517 | const int nb = k / QK_K; |
| 518 | dequantize_block_q3_K<<<gridDim: nb, blockDim: 64, sharedMem: 0, stream>>>(vx, y); |
| 519 | } |
| 520 | |
| 521 | template<typename dst_t> |
| 522 | static void dequantize_row_q4_0_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { |
| 523 | const int nb32 = k / 32; |
| 524 | const int nb = (k + 255) / 256; |
| 525 | dequantize_block_q4_0<<<gridDim: nb, blockDim: 32, sharedMem: 0, stream>>>(vx, y, nb32); |
| 526 | } |
| 527 | |
| 528 | template<typename dst_t> |
| 529 | static void dequantize_row_q4_1_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { |
| 530 | const int nb32 = k / 32; |
| 531 | const int nb = (k + 255) / 256; |
| 532 | dequantize_block_q4_1<<<gridDim: nb, blockDim: 32, sharedMem: 0, stream>>>(vx, y, nb32); |
| 533 | } |
| 534 | |
| 535 | template<typename dst_t> |
| 536 | static void dequantize_row_q4_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { |
| 537 | const int nb = k / QK_K; |
| 538 | dequantize_block_q4_K<<<gridDim: nb, blockDim: 32, sharedMem: 0, stream>>>(vx, y); |
| 539 | } |
| 540 | |
| 541 | template<typename dst_t> |
| 542 | static void dequantize_row_q5_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { |
| 543 | const int nb = k / QK_K; |
| 544 | dequantize_block_q5_K<<<gridDim: nb, blockDim: 64, sharedMem: 0, stream>>>(vx, y); |
| 545 | } |
| 546 | |
| 547 | template<typename dst_t> |
| 548 | static void dequantize_row_q6_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { |
| 549 | const int nb = k / QK_K; |
| 550 | dequantize_block_q6_K<<<gridDim: nb, blockDim: 64, sharedMem: 0, stream>>>(vx, y); |
| 551 | } |
| 552 | |
| 553 | template<typename dst_t> |
| 554 | static void dequantize_row_iq2_xxs_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { |
| 555 | const int nb = k / QK_K; |
| 556 | dequantize_block_iq2_xxs<<<gridDim: nb, blockDim: 32, sharedMem: 0, stream>>>(vx, y); |
| 557 | } |
| 558 | |
| 559 | template<typename dst_t> |
| 560 | static void dequantize_row_iq2_xs_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { |
| 561 | const int nb = k / QK_K; |
| 562 | dequantize_block_iq2_xs<<<gridDim: nb, blockDim: 32, sharedMem: 0, stream>>>(vx, y); |
| 563 | } |
| 564 | |
| 565 | template<typename dst_t> |
| 566 | static void dequantize_row_iq2_s_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { |
| 567 | const int nb = k / QK_K; |
| 568 | dequantize_block_iq2_s<<<gridDim: nb, blockDim: 32, sharedMem: 0, stream>>>(vx, y); |
| 569 | } |
| 570 | |
| 571 | template<typename dst_t> |
| 572 | static void dequantize_row_iq3_xxs_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { |
| 573 | const int nb = k / QK_K; |
| 574 | dequantize_block_iq3_xxs<<<gridDim: nb, blockDim: 32, sharedMem: 0, stream>>>(vx, y); |
| 575 | } |
| 576 | |
| 577 | template<typename dst_t> |
| 578 | static void dequantize_row_iq3_s_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { |
| 579 | const int nb = k / QK_K; |
| 580 | dequantize_block_iq3_s<<<gridDim: nb, blockDim: 32, sharedMem: 0, stream>>>(vx, y); |
| 581 | } |
| 582 | |
| 583 | template<typename dst_t> |
| 584 | static void dequantize_row_iq1_s_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { |
| 585 | const int nb = k / QK_K; |
| 586 | dequantize_block_iq1_s<<<gridDim: nb, blockDim: 32, sharedMem: 0, stream>>>(vx, y); |
| 587 | } |
| 588 | |
| 589 | template<typename dst_t> |
| 590 | static void dequantize_row_iq4_nl_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { |
| 591 | const int nb = (k + QK_K - 1) / QK_K; |
| 592 | dequantize_block_iq4_nl<<<gridDim: nb, blockDim: 32, sharedMem: 0, stream>>>(vx, y); |
| 593 | } |
| 594 | |
| 595 | template<typename dst_t> |
| 596 | static void dequantize_row_iq1_m_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { |
| 597 | const int nb = k / QK_K; |
| 598 | dequantize_block_iq1_m<<<gridDim: nb, blockDim: 32, sharedMem: 0, stream>>>(vx, y); |
| 599 | } |
| 600 | |
| 601 | template<typename dst_t> |
| 602 | static void dequantize_row_iq4_xs_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { |
| 603 | const int nb = (k + QK_K - 1) / QK_K; |
| 604 | dequantize_block_iq4_xs<<<gridDim: nb, blockDim: 32, sharedMem: 0, stream>>>(vx, y); |
| 605 | } |
| 606 | |
| 607 | template<typename dst_t> |
| 608 | static void dequantize_row_mxfp4_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { |
| 609 | const int nb = (k + QK_K - 1) / QK_K; |
| 610 | dequantize_block_mxfp4<<<gridDim: nb, blockDim: 32, sharedMem: 0, stream>>>(vx, y); |
| 611 | } |
| 612 | |
| 613 | template <typename src_t, typename dst_t> |
| 614 | static __global__ void convert_unary( |
| 615 | const void * __restrict__ vx, dst_t * __restrict__ y, const int64_t ne00, const int64_t ne01, const int64_t ne02, |
| 616 | const int64_t s01, const int64_t s02, const int64_t s03) { |
| 617 | const int64_t i00 = (int64_t)blockDim.x*blockIdx.x + threadIdx.x; |
| 618 | |
| 619 | if (i00 >= ne00) { |
| 620 | return; |
| 621 | } |
| 622 | |
| 623 | const int64_t i01 = blockIdx.y; |
| 624 | const int64_t i02 = blockIdx.z % ne02; |
| 625 | const int64_t i03 = blockIdx.z / ne02; |
| 626 | |
| 627 | const src_t * x = (const src_t *) vx; |
| 628 | |
| 629 | const int64_t ix = i03*s03 + i02*s02 + i01*s01 + i00; |
| 630 | const int64_t iy = ((i03*ne02 + i02)*ne01 + i01)*ne00 + i00; |
| 631 | y[iy] = ggml_cuda_cast<dst_t>(x[ix]); |
| 632 | } |
| 633 | |
| 634 | template <typename src_t, typename dst_t> |
| 635 | static void convert_unary_cuda(const void * vx, dst_t * y, |
| 636 | const int64_t ne00, const int64_t ne01, const int64_t ne02, const int64_t ne03, |
| 637 | const int64_t s01, const int64_t s02, const int64_t s03, cudaStream_t stream) { |
| 638 | const dim3 num_blocks((ne00 + CUDA_DEQUANTIZE_BLOCK_SIZE - 1) / CUDA_DEQUANTIZE_BLOCK_SIZE, ne01, ne02*ne03); |
| 639 | convert_unary<src_t><<<gridDim: num_blocks, CUDA_DEQUANTIZE_BLOCK_SIZE, sharedMem: 0, stream>>> |
| 640 | (vx, y, ne00, ne01, ne02, s01, s02, s03); |
| 641 | } |
| 642 | |
| 643 | template <typename src_t, typename dst_t> |
| 644 | static void convert_unary_cont_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { |
| 645 | convert_unary_cuda<src_t>(vx, y, k, 1, 1, 1, k, k, k, stream); |
| 646 | } |
| 647 | |
| 648 | to_bf16_cuda_t ggml_get_to_bf16_cuda(ggml_type type) { |
| 649 | switch (type) { |
| 650 | case GGML_TYPE_F32: |
| 651 | return convert_unary_cont_cuda<float>; |
| 652 | case GGML_TYPE_F16: |
| 653 | return convert_unary_cont_cuda<half>; |
| 654 | default: |
| 655 | return nullptr; |
| 656 | } |
| 657 | } |
| 658 | |
| 659 | to_fp16_cuda_t ggml_get_to_fp16_cuda(ggml_type type) { |
| 660 | switch (type) { |
| 661 | case GGML_TYPE_Q4_0: |
| 662 | return dequantize_row_q4_0_cuda; |
| 663 | case GGML_TYPE_Q4_1: |
| 664 | return dequantize_row_q4_1_cuda; |
| 665 | case GGML_TYPE_Q5_0: |
| 666 | return dequantize_block_cont_cuda<QK5_0, QR5_0, dequantize_q5_0>; |
| 667 | case GGML_TYPE_Q5_1: |
| 668 | return dequantize_block_cont_cuda<QK5_1, QR5_1, dequantize_q5_1>; |
| 669 | case GGML_TYPE_Q8_0: |
| 670 | if (fp16_available(ggml_cuda_info().devices[ggml_cuda_get_device()].cc)) { |
| 671 | return dequantize_block_q8_0_f16_cuda; |
| 672 | } |
| 673 | return dequantize_block_cont_cuda<QK8_0, QR8_0, dequantize_q8_0>; |
| 674 | case GGML_TYPE_Q2_K: |
| 675 | return dequantize_row_q2_K_cuda; |
| 676 | case GGML_TYPE_Q3_K: |
| 677 | return dequantize_row_q3_K_cuda; |
| 678 | case GGML_TYPE_Q4_K: |
| 679 | return dequantize_row_q4_K_cuda; |
| 680 | case GGML_TYPE_Q5_K: |
| 681 | return dequantize_row_q5_K_cuda; |
| 682 | case GGML_TYPE_Q6_K: |
| 683 | return dequantize_row_q6_K_cuda; |
| 684 | case GGML_TYPE_IQ2_XXS: |
| 685 | return dequantize_row_iq2_xxs_cuda; |
| 686 | case GGML_TYPE_IQ2_XS: |
| 687 | return dequantize_row_iq2_xs_cuda; |
| 688 | case GGML_TYPE_IQ2_S: |
| 689 | return dequantize_row_iq2_s_cuda; |
| 690 | case GGML_TYPE_IQ3_XXS: |
| 691 | return dequantize_row_iq3_xxs_cuda; |
| 692 | case GGML_TYPE_IQ1_S: |
| 693 | return dequantize_row_iq1_s_cuda; |
| 694 | case GGML_TYPE_IQ1_M: |
| 695 | return dequantize_row_iq1_m_cuda; |
| 696 | case GGML_TYPE_IQ4_NL: |
| 697 | return dequantize_row_iq4_nl_cuda; |
| 698 | case GGML_TYPE_IQ4_XS: |
| 699 | return dequantize_row_iq4_xs_cuda; |
| 700 | case GGML_TYPE_IQ3_S: |
| 701 | return dequantize_row_iq3_s_cuda; |
| 702 | case GGML_TYPE_MXFP4: |
| 703 | return dequantize_row_mxfp4_cuda; |
| 704 | case GGML_TYPE_F32: |
| 705 | return convert_unary_cont_cuda<float>; |
| 706 | case GGML_TYPE_BF16: |
| 707 | return convert_unary_cont_cuda<nv_bfloat16>; |
| 708 | default: |
| 709 | return nullptr; |
| 710 | } |
| 711 | } |
| 712 | |
| 713 | to_fp32_cuda_t ggml_get_to_fp32_cuda(ggml_type type) { |
| 714 | switch (type) { |
| 715 | case GGML_TYPE_Q4_0: |
| 716 | return dequantize_row_q4_0_cuda; |
| 717 | case GGML_TYPE_Q4_1: |
| 718 | return dequantize_row_q4_1_cuda; |
| 719 | case GGML_TYPE_Q5_0: |
| 720 | return dequantize_block_cont_cuda<QK5_0, QR5_0, dequantize_q5_0>; |
| 721 | case GGML_TYPE_Q5_1: |
| 722 | return dequantize_block_cont_cuda<QK5_1, QR5_1, dequantize_q5_1>; |
| 723 | case GGML_TYPE_Q8_0: |
| 724 | return dequantize_block_cont_cuda<QK8_0, QR8_0, dequantize_q8_0>; |
| 725 | case GGML_TYPE_Q2_K: |
| 726 | return dequantize_row_q2_K_cuda; |
| 727 | case GGML_TYPE_Q3_K: |
| 728 | return dequantize_row_q3_K_cuda; |
| 729 | case GGML_TYPE_Q4_K: |
| 730 | return dequantize_row_q4_K_cuda; |
| 731 | case GGML_TYPE_Q5_K: |
| 732 | return dequantize_row_q5_K_cuda; |
| 733 | case GGML_TYPE_Q6_K: |
| 734 | return dequantize_row_q6_K_cuda; |
| 735 | case GGML_TYPE_IQ2_XXS: |
| 736 | return dequantize_row_iq2_xxs_cuda; |
| 737 | case GGML_TYPE_IQ2_XS: |
| 738 | return dequantize_row_iq2_xs_cuda; |
| 739 | case GGML_TYPE_IQ2_S: |
| 740 | return dequantize_row_iq2_s_cuda; |
| 741 | case GGML_TYPE_IQ3_XXS: |
| 742 | return dequantize_row_iq3_xxs_cuda; |
| 743 | case GGML_TYPE_IQ1_S: |
| 744 | return dequantize_row_iq1_s_cuda; |
| 745 | case GGML_TYPE_IQ1_M: |
| 746 | return dequantize_row_iq1_m_cuda; |
| 747 | case GGML_TYPE_IQ4_NL: |
| 748 | return dequantize_row_iq4_nl_cuda; |
| 749 | case GGML_TYPE_IQ4_XS: |
| 750 | return dequantize_row_iq4_xs_cuda; |
| 751 | case GGML_TYPE_IQ3_S: |
| 752 | return dequantize_row_iq3_s_cuda; |
| 753 | case GGML_TYPE_MXFP4: |
| 754 | return dequantize_row_mxfp4_cuda; |
| 755 | case GGML_TYPE_F16: |
| 756 | return convert_unary_cont_cuda<half>; |
| 757 | case GGML_TYPE_BF16: |
| 758 | return convert_unary_cont_cuda<nv_bfloat16>; |
| 759 | default: |
| 760 | return nullptr; |
| 761 | } |
| 762 | } |
| 763 | |
| 764 | to_fp16_nc_cuda_t ggml_get_to_fp16_nc_cuda(ggml_type type) { |
| 765 | switch (type) { |
| 766 | case GGML_TYPE_F32: |
| 767 | return convert_unary_cuda<float>; |
| 768 | case GGML_TYPE_Q4_0: |
| 769 | return dequantize_block_cuda<QK4_0, QR4_0, dequantize_q4_0>; |
| 770 | case GGML_TYPE_Q4_1: |
| 771 | return dequantize_block_cuda<QK4_1, QR4_1, dequantize_q4_1>; |
| 772 | case GGML_TYPE_Q5_0: |
| 773 | return dequantize_block_cuda<QK5_0, QR5_0, dequantize_q5_0>; |
| 774 | case GGML_TYPE_Q5_1: |
| 775 | return dequantize_block_cuda<QK5_1, QR5_1, dequantize_q5_1>; |
| 776 | case GGML_TYPE_Q8_0: |
| 777 | return dequantize_block_cuda<QK8_0, QR8_0, dequantize_q8_0>; |
| 778 | case GGML_TYPE_BF16: |
| 779 | return convert_unary_cuda<nv_bfloat16>; |
| 780 | default: |
| 781 | return nullptr; |
| 782 | } |
| 783 | } |
| 784 | |
| 785 | to_bf16_nc_cuda_t ggml_get_to_bf16_nc_cuda(ggml_type type) { |
| 786 | switch (type) { |
| 787 | case GGML_TYPE_F32: |
| 788 | return convert_unary_cuda<float, nv_bfloat16>; |
| 789 | case GGML_TYPE_Q4_0: |
| 790 | return dequantize_block_cuda<QK4_0, QR4_0, dequantize_q4_0>; |
| 791 | case GGML_TYPE_Q4_1: |
| 792 | return dequantize_block_cuda<QK4_1, QR4_1, dequantize_q4_1>; |
| 793 | case GGML_TYPE_Q5_0: |
| 794 | return dequantize_block_cuda<QK5_0, QR5_0, dequantize_q5_0>; |
| 795 | case GGML_TYPE_Q5_1: |
| 796 | return dequantize_block_cuda<QK5_1, QR5_1, dequantize_q5_1>; |
| 797 | case GGML_TYPE_Q8_0: |
| 798 | return dequantize_block_cuda<QK8_0, QR8_0, dequantize_q8_0>; |
| 799 | case GGML_TYPE_F16: |
| 800 | return convert_unary_cuda<half, nv_bfloat16>; |
| 801 | default: |
| 802 | return nullptr; |
| 803 | } |
| 804 | } |
| 805 | |
| 806 | to_fp32_nc_cuda_t ggml_get_to_fp32_nc_cuda(ggml_type type) { |
| 807 | switch (type) { |
| 808 | case GGML_TYPE_F16: |
| 809 | return convert_unary_cuda<half, float>; |
| 810 | case GGML_TYPE_Q4_0: |
| 811 | return dequantize_block_cuda<QK4_0, QR4_0, dequantize_q4_0>; |
| 812 | case GGML_TYPE_Q4_1: |
| 813 | return dequantize_block_cuda<QK4_1, QR4_1, dequantize_q4_1>; |
| 814 | case GGML_TYPE_Q5_0: |
| 815 | return dequantize_block_cuda<QK5_0, QR5_0, dequantize_q5_0>; |
| 816 | case GGML_TYPE_Q5_1: |
| 817 | return dequantize_block_cuda<QK5_1, QR5_1, dequantize_q5_1>; |
| 818 | case GGML_TYPE_Q8_0: |
| 819 | return dequantize_block_cuda<QK8_0, QR8_0, dequantize_q8_0>; |
| 820 | case GGML_TYPE_BF16: |
| 821 | return convert_unary_cuda<nv_bfloat16, float>; |
| 822 | default: |
| 823 | return nullptr; |
| 824 | } |
| 825 | } |
| 826 | |