IQ1_M: 1.75 bpw quantization (#6302)
* iq1_m: basics * iq1_m: basics-2 * iq1_m: CUDA dequantize works Very 1st shot I get PPL = 9.76 for LLaMA-v2-7B. * iq1_m: separate shifts for each group of 8 in a block We get PPL(LLaMA-v2-7B ) = 9.2810 PPL(LLaMA-v2-13B) = 6.8105 Not bad, but slightly higher than sqrt(PPL(IQ1_S) * PPL(IQ2_XXS)) which is the expected outcome given that IQ1_M is halfway between IQ1_S and IQ2_XXS in terms of bpw. From this, we would expect PPL = 9.14 for LLaMA-v2-7B PPL = 6.63 for LLaMA-v2-13B * iq1_m: go to 3-bit scales There is slight increase in PPL, but the 0.0625 bpw reduction in size is totally worth it. We now have PPL(LLaMA-v2-7B ) = 9.4469 at 1.96 bpw PPL(LLaMA-v2-13B) = 6.8717 at 1.93 bpw PPL(LLaMA-v2-70B) = 4.8568 at 1.85 bpw * iq1_m: scalar dot product * iq1_m: AVX2 dot product * iq1_m: very slightly faster AVX2 dot product * iq1_m: ARM_NEON dot product Works, but very slow (10.5 t/s) * iq1_m: Metal - dequantize works, dot product does not * iq1_m: Metal now works About the same performance as iq1_s. * iq1_m: minor * iq1_m: checking pure iq1_m quantization It is pretty bad: PPL(LLaMA-v2-7B) = 34 if we quantize output.weight with Q4_K. * iiq1_m: slightly faster ARM_NEON dot product 10.5 t/s -> 11.65 t/s * iq1_m: faster ARM_NEON dot product 11.65 t/s -> 14.9 t/s * iq1_m: another minor ARM_NEON dot product improvement 14.9 -> 15.0 t/s * iq1_m: small PPL improvement via super-block scale adjustment After quantizing block scales redo the super-block scale fit. PPL(LLaMA-v2-7B ) = 9.3346 PPL(LLaMA-v2-13B) = 6.8419 PPL(LLaMA-v2-70B) = 4.8294 PPL(Mistral-7B ) = 8.1624 * iq1_m: adapt to CUDA refactoring * iq1_m: remove unused variable We have progressed to warnings being errors. * iq1_m: add to backend-ops tests * iq1_m: fix Windows ARM * iq1_m: use common definition of iq1m_scale_t * cuda: assert -> NO_DEVICE_CODE * iq1_M: PR comments --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
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16 changed files with 1006 additions and 125 deletions
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@ -373,7 +373,7 @@ static __global__ void dequantize_block_iq2_xxs(const void * __restrict__ vx, ds
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const uint8_t signs = ksigns_iq2xs[(aux32 >> 7*il) & 127];
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for (int j = 0; j < 8; ++j) y[j] = d * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f);
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#else
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assert(false);
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NO_DEVICE_CODE;
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#endif
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}
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@ -395,7 +395,7 @@ static __global__ void dequantize_block_iq2_xs(const void * __restrict__ vx, dst
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const uint8_t signs = ksigns_iq2xs[q2[il] >> 9];
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for (int j = 0; j < 8; ++j) y[j] = d * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f);
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#else
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assert(false);
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NO_DEVICE_CODE;
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#endif
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}
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@ -416,7 +416,7 @@ static __global__ void dequantize_block_iq2_s(const void * __restrict__ vx, dst_
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const uint8_t signs = x[i].qs[QK_K/8+4*ib+il];
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for (int j = 0; j < 8; ++j) y[j] = d * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f);
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#else
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assert(false);
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NO_DEVICE_CODE;
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#endif
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}
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@ -444,7 +444,7 @@ static __global__ void dequantize_block_iq3_xxs(const void * __restrict__ vx, ds
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y[j+4] = d * grid2[j] * (signs & kmask_iq2xs[j+4] ? -1.f : 1.f);
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}
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#else
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assert(false);
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NO_DEVICE_CODE;
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#endif
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}
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@ -470,7 +470,7 @@ static __global__ void dequantize_block_iq3_s(const void * __restrict__ vx, dst_
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y[j+4] = d * grid2[j] * (signs & kmask_iq2xs[j+4] ? -1.f : 1.f);
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}
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#else
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assert(false);
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NO_DEVICE_CODE;
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#endif
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}
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@ -496,11 +496,42 @@ static __global__ void dequantize_block_iq1_s(const void * __restrict__ vx, dst_
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y[j] = d * (q[j] + delta);
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}
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#else
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assert(false);
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NO_DEVICE_CODE;
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#endif
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}
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template<typename dst_t>
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static __global__ void dequantize_block_iq1_m(const void * __restrict__ vx, dst_t * __restrict__ yy) {
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const int i = blockIdx.x;
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const block_iq1_m * x = (const block_iq1_m *) vx;
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const int tid = threadIdx.x;
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#if QK_K == 256
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const int il = tid/8; // 0...3
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const int ib = tid%8; // 0...7
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dst_t * y = yy + i*QK_K + 32*ib + 8*il;
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const uint16_t * sc = (const uint16_t *)x[i].scales;
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iq1m_scale_t scale;
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scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000);
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const int ib16 = 2*ib + il/2; // sc[ib16/4] >> 3*(ib16%4) -> sc[ib/2] >> 3*((2*ib+il/2)%4);
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const float d = (float)scale.f16 * (2*((sc[ib16/4] >> 3*(ib16%4)) & 0x7) + 1);
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const float delta = x[i].qh[2*ib+il/2] & (0x08 << 4*(il%2)) ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA;
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uint32_t grid32[2]; const int8_t * q = (const int8_t *)grid32;
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grid32[0] = iq1s_grid_gpu[x[i].qs[4*ib+il] | (((x[i].qh[2*ib+il/2] >> 4*(il%2)) & 7) << 8)];
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grid32[1] = (grid32[0] >> 4) & 0x0f0f0f0f;
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grid32[0] &= 0x0f0f0f0f;
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for (int j = 0; j < 8; ++j) {
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y[j] = d * (q[j] + delta);
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}
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#else
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NO_DEVICE_CODE;
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#endif
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}
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template<typename dst_t>
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static __global__ void dequantize_block_iq4_nl(const void * __restrict__ vx, dst_t * __restrict__ yy) {
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@ -658,6 +689,12 @@ static void dequantize_row_iq4_nl_cuda(const void * vx, dst_t * y, const int k,
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dequantize_block_iq4_nl<<<nb, 32, 0, stream>>>(vx, y);
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}
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template<typename dst_t>
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static void dequantize_row_iq1_m_cuda(const void * vx, dst_t * y, const int k, cudaStream_t stream) {
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const int nb = k / QK_K;
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dequantize_block_iq1_m<<<nb, 32, 0, stream>>>(vx, y);
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}
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template<typename dst_t>
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static void dequantize_row_iq4_xs_cuda(const void * vx, dst_t * y, const int k, cudaStream_t stream) {
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const int nb = (k + QK_K - 1) / QK_K;
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@ -724,6 +761,8 @@ to_fp16_cuda_t ggml_get_to_fp16_cuda(ggml_type type) {
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return dequantize_row_iq3_xxs_cuda;
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case GGML_TYPE_IQ1_S:
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return dequantize_row_iq1_s_cuda;
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case GGML_TYPE_IQ1_M:
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return dequantize_row_iq1_m_cuda;
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case GGML_TYPE_IQ4_NL:
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return dequantize_row_iq4_nl_cuda;
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case GGML_TYPE_IQ4_XS:
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@ -769,6 +808,8 @@ to_fp32_cuda_t ggml_get_to_fp32_cuda(ggml_type type) {
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return dequantize_row_iq3_xxs_cuda;
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case GGML_TYPE_IQ1_S:
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return dequantize_row_iq1_s_cuda;
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case GGML_TYPE_IQ1_M:
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return dequantize_row_iq1_m_cuda;
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case GGML_TYPE_IQ4_NL:
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return dequantize_row_iq4_nl_cuda;
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case GGML_TYPE_IQ4_XS:
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@ -282,6 +282,14 @@ static void mul_mat_vec_iq1_s_q8_1_cuda(
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(vx, vy, dst, ncols_x, nrows_x, nrows_y, ncols_y, nrows_dst, stream);
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}
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static void mul_mat_vec_iq1_m_q8_1_cuda(
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const void * vx, const void * vy, float * dst,
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const int ncols_x, const int nrows_x, const int nrows_y, const int ncols_y, const int nrows_dst, cudaStream_t stream) {
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mul_mat_vec_q_cuda<QK_K, QI1_S, block_iq1_m, 1, vec_dot_iq1_m_q8_1>
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(vx, vy, dst, ncols_x, nrows_x, nrows_y, ncols_y, nrows_dst, stream);
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}
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static void mul_mat_vec_iq4_nl_q8_1_cuda(
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const void * vx, const void * vy, float * dst,
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const int ncols_x, const int nrows_x, const int nrows_y, const int ncols_y, const int nrows_dst, cudaStream_t stream) {
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@ -373,6 +381,9 @@ void ggml_cuda_op_mul_mat_vec_q(
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case GGML_TYPE_IQ1_S:
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mul_mat_vec_iq1_s_q8_1_cuda(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, src1_padded_row_size, src1_ncols, nrows_dst, stream);
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break;
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case GGML_TYPE_IQ1_M:
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mul_mat_vec_iq1_m_q8_1_cuda(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, src1_padded_row_size, src1_ncols, nrows_dst, stream);
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break;
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case GGML_TYPE_IQ4_NL:
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mul_mat_vec_iq4_nl_q8_1_cuda(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, src1_padded_row_size, src1_ncols, nrows_dst, stream);
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break;
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@ -961,8 +961,7 @@ static __device__ __forceinline__ float vec_dot_iq2_xxs_q8_1(
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return d * (sumi1 + sumi2);
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#endif
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#else
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assert(false);
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return 0.f;
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NO_DEVICE_CODE;
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#endif
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}
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@ -1001,13 +1000,11 @@ static __device__ __forceinline__ float vec_dot_iq2_xs_q8_1(
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return d * ((0.5f + ls1) * sumi1 + (0.5f + ls2) * sumi2);
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#else
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GGML_UNUSED(ksigns64);
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assert(false);
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return 0.f;
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NO_DEVICE_CODE;
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#endif
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#else
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GGML_UNUSED(ksigns64);
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assert(false);
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return 0.f;
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NO_DEVICE_CODE;
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#endif
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}
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@ -1049,13 +1046,11 @@ static __device__ __forceinline__ float vec_dot_iq2_s_q8_1(
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return d * ((0.5f + ls1) * sumi1 + (0.5f + ls2) * sumi2);
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#else
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GGML_UNUSED(ksigns64);
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assert(false);
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return 0.f;
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NO_DEVICE_CODE;
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#endif
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#else
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GGML_UNUSED(ksigns64);
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assert(false);
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return 0.f;
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NO_DEVICE_CODE;
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#endif
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}
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@ -1085,12 +1080,10 @@ static __device__ __forceinline__ float vec_dot_iq3_xxs_q8_1(
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const float d = (float)bq2->d * (0.5f + aux32) * __low2float(bq8_1[ib32].ds) * 0.5f;
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return d * sumi;
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#else
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assert(false);
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return 0.f;
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NO_DEVICE_CODE;
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#endif
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#else
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assert(false);
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return 0.f;
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NO_DEVICE_CODE;
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#endif
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}
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@ -1119,12 +1112,10 @@ static __device__ __forceinline__ float vec_dot_iq3_s_q8_1(
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const float d = (float)bq2->d * (1 + 2*((bq2->scales[ib32/2] >> 4*(ib32%2)) & 0xf)) * __low2float(bq8_1[ib32].ds);
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return d * sumi;
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#else
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assert(false);
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return 0.f;
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NO_DEVICE_CODE;
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#endif
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#else
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assert(false);
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return 0.f;
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NO_DEVICE_CODE;
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#endif
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}
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@ -1159,8 +1150,50 @@ static __device__ __forceinline__ float vec_dot_iq1_s_q8_1(
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const float m = d1q * __high2float(bq8_1[ib32].ds);
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return d * sumi + m * delta;
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#else
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assert(false);
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return 0.f;
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NO_DEVICE_CODE;
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#endif
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}
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static __device__ __forceinline__ float vec_dot_iq1_m_q8_1(
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const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & iqs) {
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#if QK_K == 256
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const block_iq1_m * bq1 = (const block_iq1_m *) vbq;
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const int ib32 = iqs;
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int sumi[2] = {0, 0};
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float sumf[2] = {0.f, 0.f};
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#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
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const int * q8 = (const int *)bq8_1[ib32].qs;
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for (int l = 0; l < 4; ++l) {
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const int * grid = (const int *)(iq1s_grid_gpu + (bq1->qs[4*ib32+l] | (((bq1->qh[2*ib32+l/2] >> 4*(l%2)) & 7) << 8)));
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int grid0 = grid[0] & 0x0f0f0f0f;
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int grid1 = (grid[0] >> 4) & 0x0f0f0f0f;
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sumi[l/2] = __dp4a(q8[2*l+1], grid1, __dp4a(q8[2*l+0], grid0, sumi[l/2]));
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const float delta = (bq1->qh[2*ib32+l/2] >> 4*(l%2)) & 0x08 ? -1-IQ1M_DELTA : -1+IQ1M_DELTA;
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const int sumy = __dp4a(q8[2*l+1], 0x01010101, __dp4a(q8[2*l+0], 0x01010101, 0));
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sumf[l/2] += delta*sumy;
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}
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#else
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const int8_t * q8 = bq8_1[ib32].qs;
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for (int l = 0; l < 4; ++l) {
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const uint8_t * grid = (const uint8_t *)(iq1s_grid_gpu + (bq1->qs[4*ib32+l] | (((bq1->qh[ib32] >> 3*l) & 7) << 8)));
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int sumy = 0;
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for (int j = 0; j < 4; ++j) {
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sumi[l/2] += q8[j] * (grid[j] & 0xf) + q8[j+4] * (grid[j] >> 4);
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sumy += q8[j] + q8[j+4];
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}
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const float delta = (bq1->qh[2*ib32+l/2] >> 4*(l%2)) & 0x08 ? -1-IQ1M_DELTA : -1+IQ1M_DELTA;
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sumf[l/2] += delta*sumy;
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q8 += 8;
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}
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#endif
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iq1m_scale_t scale;
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const uint16_t * sc = (const uint16_t *)bq1->scales;
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scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000);
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const float d = (float)scale.f16 * __low2float (bq8_1[ib32].ds);
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return d * ((sumi[0] + sumf[0]) * (2*((sc[ib32/2] >> 6*(ib32%2)) & 0x7) + 1) + (sumi[1] + sumf[1]) * (2*((sc[ib32/2] >> (6*(ib32%2)+3)) & 0x7) + 1));
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#else
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NO_DEVICE_CODE;
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#endif
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}
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@ -1223,27 +1256,6 @@ static __device__ __forceinline__ float vec_dot_iq4_xs_q8_1(
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const block_iq4_xs * bq4 = (const block_iq4_xs *) vbq;
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const uint8_t * values = (const uint8_t *)kvalues_iq4nl;
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//// iqs is 0...7
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//const int ib64 = iqs/2;
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//const int il = iqs%2;
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//const int32_t * q8_1 = (const int *)bq8_1[2*ib64+0].qs + 2*il;
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//const int32_t * q8_2 = (const int *)bq8_1[2*ib64+1].qs + 2*il;
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//const uint32_t * q4_1 = (const uint32_t *)bq4->qs + 8*ib64 + 2*il;
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//const uint32_t * q4_2 = q4_1 + 4;
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//const int8_t ls1 = (bq4->scales_l[ib64] & 0xf) | (((bq4->scales_h >> (4*ib64+0)) & 3) << 4);
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//const int8_t ls2 = (bq4->scales_l[ib64] >> 4) | (((bq4->scales_h >> (4*ib64+2)) & 3) << 4);
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//const float d1 = (float)bq4->d * (ls1 - 32) * __low2float(bq8_1[2*ib64+0].ds);
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//const float d2 = (float)bq4->d * (ls2 - 32) * __low2float(bq8_1[2*ib64+1].ds);
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//int v1, v2;
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//int sumi1 = 0, sumi2 = 0;
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//for (int j = 0; j < 2; ++j) {
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// get_int_from_table_16(q4_1[j], values, v1, v2);
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// sumi1 = __dp4a(v2, q8_1[j+4], __dp4a(v1, q8_1[j+0], sumi1));
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// get_int_from_table_16(q4_2[j], values, v1, v2);
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// sumi2 = __dp4a(v2, q8_2[j+4], __dp4a(v1, q8_2[j+0], sumi2));
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//}
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//return d1 * sumi1 + d2 * sumi2;
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// iqs is 0...7
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const int ib32 = iqs;
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const int32_t * q8 = (const int *)bq8_1[ib32].qs;
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@ -1259,24 +1271,8 @@ static __device__ __forceinline__ float vec_dot_iq4_xs_q8_1(
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}
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return d * (sumi1 + sumi2);
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//// iqs is 0...15
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//const int ib32 = iqs/2;
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//const int il = iqs%2;
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//const int32_t * q8 = (const int *)bq8_1[ib32].qs + 2*il;
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//const uint32_t * q4 = (const uint32_t *)bq4->qs + 4*ib32 + 2*il;
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//const int8_t ls = ((bq4->scales_l[ib32/2] >> 4*(ib32%2)) & 0xf) | (((bq4->scales_h >> 2*ib32) & 3) << 4);
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//const float d = (float)bq4->d * (ls - 32) * __low2float(bq8_1[ib32].ds);
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//int v1, v2;
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//int sumi1 = 0, sumi2 = 0;
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//for (int j = 0; j < 2; ++j) {
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// get_int_from_table_16(q4[j], values, v1, v2);
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// sumi1 = __dp4a(v1, q8[j+0], sumi1);
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// sumi2 = __dp4a(v2, q8[j+4], sumi2);
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//}
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//return d * (sumi1 + sumi2);
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#else
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assert(false);
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||||
return 0.f;
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||||
NO_DEVICE_CODE;
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||||
#endif
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#else
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||||
return vec_dot_iq4_xs_q8_1(vbq, bq8_1, iqs);
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue