ikawrakow/ik_llama.cpp
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q8_k_r8: fastest matrix multiplication known to human kind

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We get PP-512(LLaMA-3.1-8B) = 370 t/s on a Ryzen-7950X!
This commit is contained in:
Iwan Kawrakow
2024-12-13 18:21:08 +02:00
parent 12f962dd24
commit 93a85c62bb
10 changed files with 242 additions and 7 deletions
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16
src/llama.cpp
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@@ -3843,6 +3843,7 @@ struct llama_model_loader {
case GGML_TYPE_Q5_K_R4: ftype = LLAMA_FTYPE_MOSTLY_Q5_K_R4; break;
case GGML_TYPE_Q6_K: ftype = LLAMA_FTYPE_MOSTLY_Q6_K; break;
case GGML_TYPE_Q6_K_R4: ftype = LLAMA_FTYPE_MOSTLY_Q6_K_R4; break;
case GGML_TYPE_Q8_K_R8: ftype = LLAMA_FTYPE_MOSTLY_Q8_K_R8; break;
case GGML_TYPE_IQ2_XXS: ftype = LLAMA_FTYPE_MOSTLY_IQ2_XXS; break;
case GGML_TYPE_IQ2_XS: ftype = LLAMA_FTYPE_MOSTLY_IQ2_XS; break;
case GGML_TYPE_IQ2_KS: ftype = LLAMA_FTYPE_MOSTLY_IQ2_KS; break;
@@ -4560,6 +4561,7 @@ static std::string llama_model_ftype_name(llama_ftype ftype) {
case LLAMA_FTYPE_MOSTLY_Q5_K_M: return "Q5_K - Medium";
case LLAMA_FTYPE_MOSTLY_Q6_K: return "Q6_K";
case LLAMA_FTYPE_MOSTLY_Q6_K_R4: return "Q6_K_R4";
case LLAMA_FTYPE_MOSTLY_Q8_K_R8: return "Q8_K_R8";
case LLAMA_FTYPE_MOSTLY_IQ2_XXS: return "IQ2_XXS - 2.0625 bpw";
case LLAMA_FTYPE_MOSTLY_IQ2_XS: return "IQ2_XS - 2.3125 bpw";
case LLAMA_FTYPE_MOSTLY_IQ2_KS: return "IQ2_KS - 2.1875 bpw";
@@ -15766,7 +15768,8 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
ftype == LLAMA_FTYPE_MOSTLY_IQ4_KS || ftype == LLAMA_FTYPE_MOSTLY_IQ4_KSS) && !qs.has_output) {
new_type = GGML_TYPE_IQ5_K;
}
else if (new_type != GGML_TYPE_Q8_0 && new_type != GGML_TYPE_Q8_0_R4 && new_type != GGML_TYPE_IQ6_K && new_type != GGML_TYPE_Q6_K_R4) {
else if (new_type != GGML_TYPE_Q8_0 && new_type != GGML_TYPE_Q8_0_R4 && new_type != GGML_TYPE_IQ6_K && new_type != GGML_TYPE_Q6_K_R4 &&
new_type != GGML_TYPE_Q8_K_R8) {
new_type = GGML_TYPE_Q6_K;
}
}
@@ -15812,6 +15815,9 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
else if (new_type == GGML_TYPE_Q6_K_R4) {
new_type = GGML_TYPE_Q6_K;
}
else if (new_type == GGML_TYPE_Q8_K_R8) {
new_type = GGML_TYPE_Q8_0;
}
else if (new_type == GGML_TYPE_IQ4_K_R4) {
new_type = GGML_TYPE_IQ4_K;
}
@@ -16099,7 +16105,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
new_type == GGML_TYPE_IQ6_K || new_type == GGML_TYPE_IQ4_KS || new_type == GGML_TYPE_IQ4_XS_R4 ||
new_type == GGML_TYPE_IQ2_KS || new_type == GGML_TYPE_IQ4_KSS || new_type == GGML_TYPE_Q6_K_R4 ||
new_type == GGML_TYPE_Q5_K_R4 || new_type == GGML_TYPE_Q3_K_R4 || new_type == GGML_TYPE_Q2_K_R4 ||
new_type == GGML_TYPE_IQ4_K_R4) {
new_type == GGML_TYPE_IQ4_K_R4|| new_type == GGML_TYPE_Q8_K_R8) {
int nx = tensor->ne[0];
int ny = tensor->ne[1];
if (nx % QK_K != 0) {
@@ -16144,6 +16150,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
case GGML_TYPE_Q5_K: new_type = GGML_TYPE_Q6_0; break;
case GGML_TYPE_IQ6_K:
case GGML_TYPE_Q6_K_R4:
case GGML_TYPE_Q8_K_R8:
case GGML_TYPE_Q6_K: new_type = GGML_TYPE_Q8_0; break;
default: throw std::runtime_error("\nUnsupported tensor size encountered\n");
}
@@ -16240,6 +16247,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
case LLAMA_FTYPE_MOSTLY_Q5_K_R4: default_type = GGML_TYPE_Q5_K_R4; break;
case LLAMA_FTYPE_MOSTLY_Q6_K: default_type = GGML_TYPE_Q6_K; break;
case LLAMA_FTYPE_MOSTLY_Q6_K_R4: default_type = GGML_TYPE_Q6_K_R4; break;
case LLAMA_FTYPE_MOSTLY_Q8_K_R8: default_type = GGML_TYPE_Q8_K_R8; break;
case LLAMA_FTYPE_MOSTLY_IQ2_XXS: default_type = GGML_TYPE_IQ2_XXS; break;
case LLAMA_FTYPE_MOSTLY_IQ2_XS: default_type = GGML_TYPE_IQ2_XS; break;
case LLAMA_FTYPE_MOSTLY_IQ2_KS: default_type = GGML_TYPE_IQ2_KS; break;
@@ -16660,6 +16668,10 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_Q6_K;
else chunk_size_multiplier = 4;
}
else if (new_type == GGML_TYPE_Q8_K_R8) {
if (tensor->ne[1] % 8 != 0) new_type = GGML_TYPE_Q8_0;
else chunk_size_multiplier = 8;
}
else if (new_type == GGML_TYPE_IQ2_BN_R4) {
if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_IQ2_BN;
else chunk_size_multiplier = 4;