mirror of
https://github.com/ggml-org/llama.cpp.git
synced 2025-10-27 08:21:30 +00:00
CUDA: replace GGML_CUDA_F16 with CUDA arch checks (#15433)
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@@ -158,7 +158,6 @@ option(GGML_CUDA "ggml: use CUDA"
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option(GGML_MUSA "ggml: use MUSA" OFF)
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option(GGML_CUDA_FORCE_MMQ "ggml: use mmq kernels instead of cuBLAS" OFF)
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option(GGML_CUDA_FORCE_CUBLAS "ggml: always use cuBLAS instead of mmq kernels" OFF)
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option(GGML_CUDA_F16 "ggml: use 16 bit floats for some calculations" OFF)
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set (GGML_CUDA_PEER_MAX_BATCH_SIZE "128" CACHE STRING
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"ggml: max. batch size for using peer access")
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option(GGML_CUDA_NO_PEER_COPY "ggml: do not use peer to peer copies" OFF)
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@@ -24,12 +24,6 @@ if (CUDAToolkit_FOUND)
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# for best performance and to also build real architectures for the most commonly used GPUs.
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if (GGML_NATIVE AND CUDAToolkit_VERSION VERSION_GREATER_EQUAL "11.6" AND CMAKE_VERSION VERSION_GREATER_EQUAL "3.24")
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set(CMAKE_CUDA_ARCHITECTURES "native")
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elseif(GGML_CUDA_F16 OR GGML_CUDA_DMMV_F16)
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if (CUDAToolkit_VERSION VERSION_GREATER_EQUAL "11.8")
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set(CMAKE_CUDA_ARCHITECTURES "60-virtual;61-virtual;70-virtual;75-virtual;80-virtual;86-real;89-real")
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else()
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set(CMAKE_CUDA_ARCHITECTURES "60-virtual;61-virtual;70-virtual;75-virtual;80-virtual;86-real")
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endif()
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else()
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if (CUDAToolkit_VERSION VERSION_GREATER_EQUAL "11.8")
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set(CMAKE_CUDA_ARCHITECTURES "50-virtual;61-virtual;70-virtual;75-virtual;80-virtual;86-real;89-real")
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@@ -91,10 +85,6 @@ if (CUDAToolkit_FOUND)
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add_compile_definitions(GGML_CUDA_NO_FA)
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endif()
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if (GGML_CUDA_F16 OR GGML_CUDA_DMMV_F16)
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add_compile_definitions(GGML_CUDA_F16)
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endif()
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if (GGML_CUDA_NO_PEER_COPY)
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add_compile_definitions(GGML_CUDA_NO_PEER_COPY)
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endif()
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@@ -206,14 +206,6 @@ static const char * cu_get_error_str(CUresult err) {
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#define GGML_CUDA_ASSUME(x)
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#endif // CUDART_VERSION >= 11010
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#ifdef GGML_CUDA_F16
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typedef half dfloat; // dequantize float
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typedef half2 dfloat2;
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#else
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typedef float dfloat; // dequantize float
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typedef float2 dfloat2;
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#endif // GGML_CUDA_F16
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#if (!defined(GGML_USE_HIP) && !defined(GGML_CUDA_NO_VMM)) || (defined(GGML_USE_HIP) && !defined(GGML_HIP_NO_VMM))
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#define GGML_USE_VMM
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#endif // (!defined(GGML_USE_HIP) && !defined(GGML_CUDA_NO_VMM)) || (defined(GGML_USE_HIP) && !defined(GGML_HIP_NO_VMM))
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@@ -559,7 +551,7 @@ static __device__ __forceinline__ float ggml_cuda_e8m0_to_fp32(uint8_t x) {
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#endif // CUDART_VERSION >= 12050
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}
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typedef void (*dequantize_kernel_t)(const void * vx, const int64_t ib, const int iqs, dfloat2 & v);
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typedef void (*dequantize_kernel_t)(const void * vx, const int64_t ib, const int iqs, float2 & v);
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static __device__ __forceinline__ float get_alibi_slope(
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const float max_bias, const uint32_t h, const uint32_t n_head_log2, const float m0, const float m1
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@@ -27,7 +27,7 @@ static __global__ void dequantize_block(const void * __restrict__ vx, dst_t * __
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const int64_t y_offset = qr == 1 ? 1 : qk/2;
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// dequantize
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dfloat2 v;
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float2 v;
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dequantize_kernel(vx, ib, iqs, v);
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const int64_t iy0 = ((i03*ne02 + i02)*ne01 + i01)*ne00 + iybs + iqs;
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@@ -42,7 +42,7 @@ static __device__ void cpy_blck_q8_0_f32(const char * cxi, char * cdsti) {
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#pragma unroll
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for (int j = 0; j < QK8_0; j += 2) {
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dfloat2 dq;
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float2 dq;
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dequantize_q8_0(cxi, 0, j, dq);
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*(cdstf + j) = dq.x;
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*(cdstf + j + 1) = dq.y;
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@@ -55,7 +55,7 @@ static __device__ void cpy_blck_q_f32(const char * cxi, char * cdsti) {
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#pragma unroll
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for (int j = 0; j < qk/2; j++) {
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dfloat2 dq;
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float2 dq;
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dequant(cxi, 0, j, dq);
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*(cdstf + j) = dq.x;
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*(cdstf + j + qk/2) = dq.y;
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@@ -1,48 +1,37 @@
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#include "common.cuh"
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static __device__ __forceinline__ void dequantize_q4_0(const void * vx, const int64_t ib, const int iqs, dfloat2 & v){
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static __device__ __forceinline__ void dequantize_q4_0(const void * vx, const int64_t ib, const int iqs, float2 & v){
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const block_q4_0 * x = (const block_q4_0 *) vx;
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const dfloat d = x[ib].d;
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const float d = x[ib].d;
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const int vui = x[ib].qs[iqs];
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v.x = vui & 0xF;
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v.y = vui >> 4;
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#ifdef GGML_CUDA_F16
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v = __hsub2(v, {8.0f, 8.0f});
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v = __hmul2(v, {d, d});
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#else
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v.x = (v.x - 8.0f) * d;
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v.y = (v.y - 8.0f) * d;
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#endif // GGML_CUDA_F16
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}
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static __device__ __forceinline__ void dequantize_q4_1(const void * vx, const int64_t ib, const int iqs, dfloat2 & v){
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static __device__ __forceinline__ void dequantize_q4_1(const void * vx, const int64_t ib, const int iqs, float2 & v){
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const block_q4_1 * x = (const block_q4_1 *) vx;
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const dfloat d = __low2half(x[ib].dm);
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const dfloat m = __high2half(x[ib].dm);
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const float2 dm = __half22float2(x[ib].dm);
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const int vui = x[ib].qs[iqs];
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v.x = vui & 0xF;
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v.y = vui >> 4;
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#ifdef GGML_CUDA_F16
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v = __hmul2(v, {d, d});
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v = __hadd2(v, {m, m});
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#else
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v.x = (v.x * d) + m;
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v.y = (v.y * d) + m;
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#endif // GGML_CUDA_F16
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v.x = (v.x * dm.x) + dm.y;
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v.y = (v.y * dm.x) + dm.y;
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}
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static __device__ __forceinline__ void dequantize_q5_0(const void * vx, const int64_t ib, const int iqs, dfloat2 & v){
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static __device__ __forceinline__ void dequantize_q5_0(const void * vx, const int64_t ib, const int iqs, float2 & v){
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const block_q5_0 * x = (const block_q5_0 *) vx;
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const dfloat d = x[ib].d;
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const float d = x[ib].d;
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uint32_t qh;
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memcpy(&qh, x[ib].qh, sizeof(qh));
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@@ -53,20 +42,14 @@ static __device__ __forceinline__ void dequantize_q5_0(const void * vx, const in
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v.x = ((x[ib].qs[iqs] & 0xf) | xh_0);
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v.y = ((x[ib].qs[iqs] >> 4) | xh_1);
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#ifdef GGML_CUDA_F16
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v = __hsub2(v, {16.0f, 16.0f});
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v = __hmul2(v, {d, d});
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#else
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v.x = (v.x - 16.0f) * d;
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v.y = (v.y - 16.0f) * d;
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#endif // GGML_CUDA_F16
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}
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static __device__ __forceinline__ void dequantize_q5_1(const void * vx, const int64_t ib, const int iqs, dfloat2 & v){
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static __device__ __forceinline__ void dequantize_q5_1(const void * vx, const int64_t ib, const int iqs, float2 & v){
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const block_q5_1 * x = (const block_q5_1 *) vx;
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const dfloat d = __low2half(x[ib].dm);
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const dfloat m = __high2half(x[ib].dm);
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const float2 dm = __half22float2(x[ib].dm);
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uint32_t qh;
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memcpy(&qh, x[ib].qh, sizeof(qh));
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@@ -77,27 +60,18 @@ static __device__ __forceinline__ void dequantize_q5_1(const void * vx, const in
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v.x = ((x[ib].qs[iqs] & 0xf) | xh_0);
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v.y = ((x[ib].qs[iqs] >> 4) | xh_1);
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#ifdef GGML_CUDA_F16
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v = __hmul2(v, {d, d});
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v = __hadd2(v, {m, m});
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#else
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v.x = (v.x * d) + m;
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v.y = (v.y * d) + m;
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#endif // GGML_CUDA_F16
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v.x = (v.x * dm.x) + dm.y;
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v.y = (v.y * dm.x) + dm.y;
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}
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static __device__ __forceinline__ void dequantize_q8_0(const void * vx, const int64_t ib, const int iqs, dfloat2 & v){
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static __device__ __forceinline__ void dequantize_q8_0(const void * vx, const int64_t ib, const int iqs, float2 & v){
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const block_q8_0 * x = (const block_q8_0 *) vx;
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const dfloat d = x[ib].d;
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const float d = x[ib].d;
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v.x = x[ib].qs[iqs + 0];
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v.y = x[ib].qs[iqs + 1];
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#ifdef GGML_CUDA_F16
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v = __hmul2(v, {d, d});
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#else
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v.x *= d;
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v.y *= d;
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#endif // GGML_CUDA_F16
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}
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@@ -32,7 +32,7 @@ static __global__ void k_get_rows(
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const int y_offset = qr == 1 ? 1 : qk/2;
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// dequantize
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dfloat2 v;
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float2 v;
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dequantize_kernel(src0_row, ib, iqs, v);
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dst_row[iybs + iqs + 0] = ggml_cuda_cast<dst_t>(v.x);
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@@ -3672,10 +3672,6 @@ static ggml_backend_feature * ggml_backend_cuda_get_features(ggml_backend_reg_t
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features.push_back({ "NO_PEER_COPY", "1" });
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#endif
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#ifdef GGML_CUDA_F16
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features.push_back({ "F16", "1" });
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#endif
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#ifdef GGML_CUDA_USE_GRAPHS
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features.push_back({ "USE_GRAPHS", "1" });
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#endif
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@@ -87,7 +87,7 @@ template <int vdr> static __device__ __forceinline__ float vec_dot_q4_1_q8_1_imp
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sumi = ggml_cuda_dp4a(vi1, u[2*i+1], sumi);
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}
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#ifdef GGML_CUDA_F16
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#ifdef FAST_FP16_AVAILABLE
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const float2 tmp = __half22float2(__hmul2(dm4, ds8));
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const float d4d8 = tmp.x;
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const float m4s8 = tmp.y;
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@@ -96,7 +96,7 @@ template <int vdr> static __device__ __forceinline__ float vec_dot_q4_1_q8_1_imp
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const float2 ds8f = __half22float2(ds8);
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const float d4d8 = dm4f.x * ds8f.x;
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const float m4s8 = dm4f.y * ds8f.y;
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#endif // GGML_CUDA_F16
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#endif // FAST_FP16_AVAILABLE
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// scale second part of sum by QI8_1/(vdr * QR4_1) to compensate for multiple threads adding it
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return sumi * d4d8 + m4s8 / (QI8_1 / (vdr * QR4_1));
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@@ -158,7 +158,7 @@ template <int vdr> static __device__ __forceinline__ float vec_dot_q5_1_q8_1_imp
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sumi = ggml_cuda_dp4a(vi1, u[2*i+1], sumi); // SIMD dot product of quantized values
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}
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#ifdef GGML_CUDA_F16
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#ifdef FAST_FP16_AVAILABLE
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const float2 tmp = __half22float2(__hmul2(dm5, ds8));
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const float d5d8 = tmp.x;
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const float m5s8 = tmp.y;
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@@ -167,7 +167,7 @@ template <int vdr> static __device__ __forceinline__ float vec_dot_q5_1_q8_1_imp
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const float2 ds8f = __half22float2(ds8);
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const float d5d8 = dm5f.x * ds8f.x;
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const float m5s8 = dm5f.y * ds8f.y;
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#endif // GGML_CUDA_F16
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#endif // FAST_FP16_AVAILABLE
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// scale second part of sum by QI5_1 / vdr to compensate for multiple threads adding it
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return sumi*d5d8 + m5s8 / (QI5_1 / vdr);
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@@ -201,7 +201,7 @@ template <int vdr> static __device__ __forceinline__ float vec_dot_q8_1_q8_1_imp
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sumi = ggml_cuda_dp4a(v[i], u[i], sumi);
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}
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#ifdef GGML_CUDA_F16
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#ifdef FAST_FP16_AVAILABLE
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const float2 tmp = __half22float2(__hmul2(dm8, ds8));
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const float d8d8 = tmp.x;
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const float m8s8 = tmp.y;
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@@ -210,7 +210,7 @@ template <int vdr> static __device__ __forceinline__ float vec_dot_q8_1_q8_1_imp
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const float2 ds8f = __half22float2(ds8);
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const float d8d8 = dm8f.x * ds8f.x;
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const float m8s8 = dm8f.y * ds8f.y;
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#endif // GGML_CUDA_F16
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#endif // FAST_FP16_AVAILABLE
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// scale second part of sum by QI8_1/ vdr to compensate for multiple threads adding it
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return sumi*d8d8 + m8s8 / (QI8_1 / vdr);
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@@ -96,10 +96,6 @@ if (MUSAToolkit_FOUND)
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add_compile_definitions(GGML_CUDA_NO_FA)
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endif()
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if (GGML_CUDA_F16 OR GGML_CUDA_DMMV_F16)
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add_compile_definitions(GGML_CUDA_F16)
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endif()
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if (GGML_CUDA_NO_PEER_COPY)
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add_compile_definitions(GGML_CUDA_NO_PEER_COPY)
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endif()
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