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CUDA: MMQ code deduplication + iquant support (#8495)

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* CUDA: MMQ code deduplication + iquant support

* 1 less parallel job for CI build
This commit is contained in:
Johannes Gäßler 2024-07-20 22:25:26 +02:00 committed by GitHub
parent 07283b1a90
commit 69c487f4ed
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GPG Key ID: B5690EEEBB952194
11 changed files with 800 additions and 639 deletions
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2
.github/workflows/build.yml vendored
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@ -860,7 +860,7 @@ jobs:
mkdir build
cd build
cmake .. -DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_CUDA=ON -DBUILD_SHARED_LIBS=ON
cmake --build . --config Release -j ${env:NUMBER_OF_PROCESSORS}
cmake --build . --config Release -j $((${env:NUMBER_OF_PROCESSORS} - 1))
- name: Determine tag name
id: tag

24
ggml/src/ggml-cuda/mmq.cu
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@ -59,6 +59,24 @@ void ggml_cuda_op_mul_mat_q(
case GGML_TYPE_Q6_K:
mul_mat_q_case<GGML_TYPE_Q6_K>(ctx, args, stream);
break;
case GGML_TYPE_IQ2_XXS:
mul_mat_q_case<GGML_TYPE_IQ2_XXS>(ctx, args, stream);
break;
case GGML_TYPE_IQ2_XS:
mul_mat_q_case<GGML_TYPE_IQ2_XS>(ctx, args, stream);
break;
case GGML_TYPE_IQ2_S:
mul_mat_q_case<GGML_TYPE_IQ2_S>(ctx, args, stream);
break;
case GGML_TYPE_IQ3_XXS:
mul_mat_q_case<GGML_TYPE_IQ3_XXS>(ctx, args, stream);
break;
case GGML_TYPE_IQ3_S:
mul_mat_q_case<GGML_TYPE_IQ3_S>(ctx, args, stream);
break;
case GGML_TYPE_IQ1_S:
mul_mat_q_case<GGML_TYPE_IQ1_S>(ctx, args, stream);
break;
case GGML_TYPE_IQ4_XS:
mul_mat_q_case<GGML_TYPE_IQ4_XS>(ctx, args, stream);
break;
@ -93,6 +111,12 @@ bool ggml_cuda_should_use_mmq(enum ggml_type type, int cc, int64_t ne11) {
case GGML_TYPE_Q4_K:
case GGML_TYPE_Q5_K:
case GGML_TYPE_Q6_K:
case GGML_TYPE_IQ2_XXS:
case GGML_TYPE_IQ2_XS:
case GGML_TYPE_IQ2_S:
case GGML_TYPE_IQ3_XXS:
case GGML_TYPE_IQ3_S:
case GGML_TYPE_IQ1_S:
case GGML_TYPE_IQ4_XS:
case GGML_TYPE_IQ4_NL:
mmq_supported = true;

1359
ggml/src/ggml-cuda/mmq.cuh
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File diff suppressed because it is too large Load Diff

3
ggml/src/ggml-cuda/template-instances/generate_cu_files.py
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@ -23,7 +23,8 @@ SOURCE_FATTN_WMMA_CASE = "DECL_FATTN_WMMA_F16_CASE({head_size}, {cols_per_block}
TYPES_MMQ = [
"GGML_TYPE_Q4_0", "GGML_TYPE_Q4_1", "GGML_TYPE_Q5_0", "GGML_TYPE_Q5_1", "GGML_TYPE_Q8_0",
"GGML_TYPE_Q2_K", "GGML_TYPE_Q3_K", "GGML_TYPE_Q4_K", "GGML_TYPE_Q5_K", "GGML_TYPE_Q6_K",
"GGML_TYPE_IQ4_NL", "GGML_TYPE_IQ4_XS"
"GGML_TYPE_IQ2_XXS", "GGML_TYPE_IQ2_XS", "GGML_TYPE_IQ2_S", "GGML_TYPE_IQ3_XXS", "GGML_TYPE_IQ3_S",
"GGML_TYPE_IQ1_S", "GGML_TYPE_IQ4_NL", "GGML_TYPE_IQ4_XS"
]
SOURCE_MMQ = """// This file has been autogenerated by generate_cu_files.py, do not edit manually.

5
ggml/src/ggml-cuda/template-instances/mmq-instance-iq1_s.cu Normal file
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@ -0,0 +1,5 @@
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../mmq.cuh"
DECL_MMQ_CASE(GGML_TYPE_IQ1_S);

5
ggml/src/ggml-cuda/template-instances/mmq-instance-iq2_s.cu Normal file
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@ -0,0 +1,5 @@
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../mmq.cuh"
DECL_MMQ_CASE(GGML_TYPE_IQ2_S);

5
ggml/src/ggml-cuda/template-instances/mmq-instance-iq2_xs.cu Normal file
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@ -0,0 +1,5 @@
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../mmq.cuh"
DECL_MMQ_CASE(GGML_TYPE_IQ2_XS);

5
ggml/src/ggml-cuda/template-instances/mmq-instance-iq2_xxs.cu Normal file
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@ -0,0 +1,5 @@
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../mmq.cuh"
DECL_MMQ_CASE(GGML_TYPE_IQ2_XXS);

5
ggml/src/ggml-cuda/template-instances/mmq-instance-iq3_s.cu Normal file
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@ -0,0 +1,5 @@
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../mmq.cuh"
DECL_MMQ_CASE(GGML_TYPE_IQ3_S);

5
ggml/src/ggml-cuda/template-instances/mmq-instance-iq3_xxs.cu Normal file
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@ -0,0 +1,5 @@
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../mmq.cuh"
DECL_MMQ_CASE(GGML_TYPE_IQ3_XXS);

21
ggml/src/ggml-cuda/vecdotq.cuh
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@ -188,6 +188,27 @@ template <int vdr> static __device__ __forceinline__ float vec_dot_q8_1_q8_1_imp
return sumi*d8d8 + m8s8 / (QI8_1 / vdr);
}
template <int vdr> static __device__ __forceinline__ float vec_dot_q8_0_16_q8_1_impl(
const int * v, const int * u, const float * d8_0, const float & d8_1) {
float sumf = 0.0f;
#pragma unroll
for (int i0 = 0; i0 < vdr; i0 += QI8_0/2) {
int sumi = 0;
#pragma unroll
for (int i = i0; i < i0 + QI8_0/2; ++i) {
// SIMD dot product of quantized values
sumi = ggml_cuda_dp4a(v[i], u[i], sumi);
}
sumf += d8_0[i0/(QI8_0/2)]*sumi;
}
return d8_1*sumf;
}
#define VDR_Q2_K_Q8_1_MMVQ 1
#define VDR_Q2_K_Q8_1_MMQ 4