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author | Kawrakow <48489457+ikawrakow@users.noreply.github.com> | 2024-02-24 16:23:52 +0200 |
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committer | GitHub <noreply@github.com> | 2024-02-24 16:23:52 +0200 |
commit | 4c4cb30736582cacb1a164a9d4bc8e17b1014be7 (patch) | |
tree | 5f953370b3124531d9cbb9b9d5cfdb264ddf60bc /ggml.c | |
parent | 525213d2f5da1eaf4b922b6b792cb52b2c613368 (diff) |
IQ3_S: a much better alternative to Q3_K (#5676)
* iq4_nl: squash commits for easier rebase
* Basics (quantize, dequantize)
* CUDA dequantize and dot product
* Slightly faster CUDA dot product (120 t/s)
* Switch to 6-bit scales
* Scalar dot product
* AVX2 dot product
* ARM_NEON dot product
* Works on metal, but still slow
* Slightly better Metal dot product
* Another small Metal improvement
* Metal dot product is getting there
* Faster CUDA dot product
* Add 1/8 ffn_down layers as Q5_K when no imatrix has been provided
* Report the actual bpw
* Add _xs mix that is 4.05 bpw for non-MoE models
* Remove IQ4_XS for now, slightly adjust kvalues_iq4nl
* AVX2 dot product uses Q8_0 instead of Q8_K
* Add to test-backend-ops
* Minor fix
* Also use use Q5_K for attn_output in MoE models
* Fixes after merging latest master
* Switching to blocks of 32
* AVX2 for blocks of 32
* Scaler dot product for blocks of 32
* ARM_NEON dot product for blocks of 32
* Metal kernels for blocks of 32
* Slightly faster Metal kernels
* Resurrecting iq3_xs
After all the experimentation, nothing was better than this.
* Minor PPL improvement via a block scale fudge factor
* Minor improvement via 3 neighbours
* iq3_xs: working scalar and AVX2 dot products
* iq3_xs: ARM_NEON dot product - works but extremely slow (10 t/s)
* iq3_xs: working Metal implementation
* Adding IQ3_M - IQ3_XS mix with mostly Q4_K
* iiq3_xs: a 3.4375 bpw variant
* iq3_xs: make CUDA work for new version
* iq3_xs: make scalar and AVX2 work for new version
* iq3_s: make ARM_NEON work with new version
* iq3_xs: make new version work on metal
Performance is very similar to Q3_K_S
* iq3_xs: tiny Metal speed improvement
* iq3_xs: tiny Metal speed improvement
* Fix stupid warning
* Q3_K_XS now uses a mix of IQ3_XS and IQ3_XXS
* iq3_xs: rename to iq3_s
* iq3_s: make tests pass
* Move Q3_K_XS mix to 3.25 bpw
* Attempt to fix failing tests
* Another attempt to fix the Windows builds
* Attempt to fix ROCm
* ROCm again
* iq3_s: partial fix for QK_K = 64
* iq3_s: make it work on metal for QK_K = 64
Pleasent surprise: the coding was super-block size independent,
so all it took was to delete some QK_K == 256 guards.
* Will this fix ROCm?
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
Diffstat (limited to 'ggml.c')
-rw-r--r-- | ggml.c | 31 |
1 files changed, 31 insertions, 0 deletions
@@ -678,6 +678,18 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = { .vec_dot_type = GGML_TYPE_Q8_K, .nrows = 1, }, + [GGML_TYPE_IQ3_S] = { + .type_name = "iq3_s", + .blck_size = QK_K, + .type_size = sizeof(block_iq3_s), + .is_quantized = true, + .to_float = (ggml_to_float_t) dequantize_row_iq3_s, + .from_float = quantize_row_iq3_s, + .from_float_reference = (ggml_from_float_t)quantize_row_iq3_s_reference, + .vec_dot = ggml_vec_dot_iq3_s_q8_K, + .vec_dot_type = GGML_TYPE_Q8_K, + .nrows = 1, + }, [GGML_TYPE_IQ1_S] = { .type_name = "iq1_s", .blck_size = QK_K, @@ -2304,6 +2316,7 @@ enum ggml_type ggml_ftype_to_ggml_type(enum ggml_ftype ftype) { case GGML_FTYPE_MOSTLY_IQ3_XXS: wtype = GGML_TYPE_IQ3_XXS; break; case GGML_FTYPE_MOSTLY_IQ1_S: wtype = GGML_TYPE_IQ1_S; break; case GGML_FTYPE_MOSTLY_IQ4_NL: wtype = GGML_TYPE_IQ4_NL; break; + case GGML_FTYPE_MOSTLY_IQ3_S: wtype = GGML_TYPE_IQ3_S; break; case GGML_FTYPE_UNKNOWN: wtype = GGML_TYPE_COUNT; break; case GGML_FTYPE_MOSTLY_Q4_1_SOME_F16: wtype = GGML_TYPE_COUNT; break; } @@ -7738,6 +7751,7 @@ static void ggml_compute_forward_add( case GGML_TYPE_IQ3_XXS: case GGML_TYPE_IQ1_S: case GGML_TYPE_IQ4_NL: + case GGML_TYPE_IQ3_S: { ggml_compute_forward_add_q_f32(params, dst); } break; @@ -8017,6 +8031,7 @@ static void ggml_compute_forward_add1( case GGML_TYPE_IQ3_XXS: case GGML_TYPE_IQ1_S: case GGML_TYPE_IQ4_NL: + case GGML_TYPE_IQ3_S: { ggml_compute_forward_add1_q_f32(params, dst); } break; @@ -8141,6 +8156,7 @@ static void ggml_compute_forward_acc( case GGML_TYPE_IQ3_XXS: case GGML_TYPE_IQ1_S: case GGML_TYPE_IQ4_NL: + case GGML_TYPE_IQ3_S: default: { GGML_ASSERT(false); @@ -11039,6 +11055,7 @@ static void ggml_compute_forward_out_prod( case GGML_TYPE_IQ3_XXS: case GGML_TYPE_IQ1_S: case GGML_TYPE_IQ4_NL: + case GGML_TYPE_IQ3_S: { ggml_compute_forward_out_prod_q_f32(params, dst); } break; @@ -11227,6 +11244,7 @@ static void ggml_compute_forward_set( case GGML_TYPE_IQ3_XXS: case GGML_TYPE_IQ1_S: case GGML_TYPE_IQ4_NL: + case GGML_TYPE_IQ3_S: default: { GGML_ASSERT(false); @@ -11429,6 +11447,7 @@ static void ggml_compute_forward_get_rows( case GGML_TYPE_IQ3_XXS: case GGML_TYPE_IQ1_S: case GGML_TYPE_IQ4_NL: + case GGML_TYPE_IQ3_S: { ggml_compute_forward_get_rows_q(params, dst); } break; @@ -12129,6 +12148,7 @@ static void ggml_compute_forward_alibi( case GGML_TYPE_IQ3_XXS: case GGML_TYPE_IQ1_S: case GGML_TYPE_IQ4_NL: + case GGML_TYPE_IQ3_S: case GGML_TYPE_Q8_K: case GGML_TYPE_I8: case GGML_TYPE_I16: @@ -12212,6 +12232,7 @@ static void ggml_compute_forward_clamp( case GGML_TYPE_IQ3_XXS: case GGML_TYPE_IQ1_S: case GGML_TYPE_IQ4_NL: + case GGML_TYPE_IQ3_S: case GGML_TYPE_Q8_K: case GGML_TYPE_I8: case GGML_TYPE_I16: @@ -19463,6 +19484,7 @@ void ggml_quantize_init(enum ggml_type type) { case GGML_TYPE_IQ2_XS: case GGML_TYPE_IQ1_S: iq2xs_init_impl(type); break; case GGML_TYPE_IQ3_XXS: iq3xs_init_impl(256); break; + case GGML_TYPE_IQ3_S: iq3xs_init_impl(512); break; default: // nothing break; } @@ -19737,6 +19759,15 @@ size_t ggml_quantize_chunk(enum ggml_type type, const float * src, void * dst, i result = quantize_iq3_xxs(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix); GGML_ASSERT(result == row_size * nrows); } break; + case GGML_TYPE_IQ3_S: + { + GGML_ASSERT(start % QK_K == 0); + GGML_ASSERT(start % n_per_row == 0); + size_t start_row = start / n_per_row; + size_t row_size = ggml_row_size(type, n_per_row); + result = quantize_iq3_s(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix); + GGML_ASSERT(result == row_size * nrows); + } break; case GGML_TYPE_IQ1_S: { GGML_ASSERT(start % QK_K == 0); |