Convert vector to f16 for dequantize mul mat vec (#1913)
* Convert vector to f16 for dmmv * compile option * Added compilation option description to README * Changed cmake CUDA_ARCHITECTURES from "OFF" to "native"
This commit is contained in:
Johannes Gäßler
GitHub
parent
b24c3049d9
commit
16b9cd1939
5 changed files with 158 additions and 68 deletions
202
ggml-cuda.cu
202
ggml-cuda.cu
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@ -50,7 +50,15 @@ static_assert(sizeof(half) == sizeof(ggml_fp16_t), "wrong fp16 size");
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} while (0)
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#endif // CUDART_VERSION >= 11
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typedef void (*dequantize_kernel_t)(const void * vx, const int ib, const int iqs, float & v0, float & v1);
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#ifdef GGML_CUDA_DMMV_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_DMMV_F16
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typedef void (*dequantize_kernel_t)(const void * vx, const int ib, const int iqs, dfloat2 & v);
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typedef void (*to_fp32_cuda_t)(const void * x, float * y, int k, cudaStream_t stream);
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typedef void (*dot_kernel_k_t)(const void * vx, const int ib, const int iqs, const float * y, float & v);
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typedef void (*cpy_kernel_t)(const char * cx, char * cdst);
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@ -234,82 +242,106 @@ static __global__ void rms_norm_f32(const float * x, float * dst, const int ncol
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}
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}
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static __device__ void dequantize_q4_0(const void * vx, const int ib, const int iqs, float & v0, float & v1){
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static __device__ __forceinline__ void dequantize_q4_0(const void * vx, const int ib, const int iqs, dfloat2 & v){
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const block_q4_0 * x = (const block_q4_0 *) vx;
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const float d = x[ib].d;
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const dfloat d = x[ib].d;
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const uint8_t vui = x[ib].qs[iqs];
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const int vui = x[ib].qs[iqs];
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const int8_t vi0 = vui & 0xF;
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const int8_t vi1 = vui >> 4;
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v.x = vui & 0xF;
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v.y = vui >> 4;
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v0 = (vi0 - 8)*d;
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v1 = (vi1 - 8)*d;
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#ifdef GGML_CUDA_DMMV_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_DMMV_F16
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}
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static __device__ void dequantize_q4_1(const void * vx, const int ib, const int iqs, float & v0, float & v1){
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static __device__ __forceinline__ void dequantize_q4_1(const void * vx, const int ib, const int iqs, dfloat2 & v){
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const block_q4_1 * x = (const block_q4_1 *) vx;
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const float d = x[ib].d;
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const float m = x[ib].m;
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const dfloat d = x[ib].d;
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const dfloat m = x[ib].m;
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const uint8_t vui = x[ib].qs[iqs];
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const int vui = x[ib].qs[iqs];
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const int8_t vi0 = vui & 0xF;
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const int8_t vi1 = vui >> 4;
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v.x = vui & 0xF;
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v.y = vui >> 4;
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v0 = vi0*d + m;
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v1 = vi1*d + m;
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#ifdef GGML_CUDA_DMMV_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_DMMV_F16
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}
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static __device__ void dequantize_q5_0(const void * vx, const int ib, const int iqs, float & v0, float & v1){
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static __device__ __forceinline__ void dequantize_q5_0(const void * vx, const int ib, const int iqs, dfloat2 & v){
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const block_q5_0 * x = (const block_q5_0 *) vx;
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const float d = x[ib].d;
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const dfloat 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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const uint8_t xh_0 = ((qh >> (iqs + 0)) << 4) & 0x10;
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const uint8_t xh_1 = ((qh >> (iqs + 12)) ) & 0x10;
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const int xh_0 = ((qh >> (iqs + 0)) << 4) & 0x10;
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const int xh_1 = ((qh >> (iqs + 12)) ) & 0x10;
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const int32_t x0 = ((x[ib].qs[iqs] & 0xf) | xh_0) - 16;
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const int32_t x1 = ((x[ib].qs[iqs] >> 4) | xh_1) - 16;
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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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v0 = x0*d;
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v1 = x1*d;
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#ifdef GGML_CUDA_DMMV_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_DMMV_F16
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}
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static __device__ void dequantize_q5_1(const void * vx, const int ib, const int iqs, float & v0, float & v1){
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static __device__ __forceinline__ void dequantize_q5_1(const void * vx, const int ib, const int iqs, dfloat2 & v){
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const block_q5_1 * x = (const block_q5_1 *) vx;
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const float d = x[ib].d;
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const float m = x[ib].m;
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const dfloat d = x[ib].d;
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const dfloat m = x[ib].m;
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uint32_t qh;
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memcpy(&qh, x[ib].qh, sizeof(qh));
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const uint8_t xh_0 = ((qh >> (iqs + 0)) << 4) & 0x10;
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const uint8_t xh_1 = ((qh >> (iqs + 12)) ) & 0x10;
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const int xh_0 = ((qh >> (iqs + 0)) << 4) & 0x10;
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const int xh_1 = ((qh >> (iqs + 12)) ) & 0x10;
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const int32_t x0 = ((x[ib].qs[iqs] & 0xf) | xh_0);
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const int32_t x1 = ((x[ib].qs[iqs] >> 4) | xh_1);
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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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v0 = x0*d + m;
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v1 = x1*d + m;
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#ifdef GGML_CUDA_DMMV_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_DMMV_F16
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}
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static __device__ void dequantize_q8_0(const void * vx, const int ib, const int iqs, float & v0, float & v1){
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static __device__ __forceinline__ void dequantize_q8_0(const void * vx, const int ib, const int iqs, dfloat2 & v){
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const block_q8_0 * x = (const block_q8_0 *) vx;
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const float d = x[ib].d;
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const dfloat d = x[ib].d;
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const int8_t vi0 = x[ib].qs[iqs + 0];
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const int8_t vi1 = x[ib].qs[iqs + 1];
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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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v0 = vi0*d;
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v1 = vi1*d;
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#ifdef GGML_CUDA_DMMV_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_DMMV_F16
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}
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//================================== k-quants
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@ -843,11 +875,12 @@ static __global__ void dequantize_mul_mat_vec_q6_k(const void * vx, const float
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}
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}
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static __device__ void convert_f16(const void * vx, const int ib, const int iqs, float & v0, float & v1){
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static __device__ void convert_f16(const void * vx, const int ib, const int iqs, dfloat2 & v){
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const half * x = (const half *) vx;
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v0 = __half2float(x[ib + iqs + 0]);
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v1 = __half2float(x[ib + iqs + 1]);
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// automatic half -> float type cast if dfloat == float
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v.x = x[ib + iqs + 0];
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v.y = x[ib + iqs + 1];
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}
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template <int qk, int qr, dequantize_kernel_t dequantize_kernel>
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@ -864,13 +897,15 @@ static __global__ void dequantize_block(const void * vx, float * y, const int k)
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const int y_offset = qr == 1 ? 1 : qk/2;
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// dequantize
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float & v0 = y[iybs + iqs + 0];
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float & v1 = y[iybs + iqs + y_offset];
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dequantize_kernel(vx, ib, iqs, v0, v1);
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dfloat2 v;
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dequantize_kernel(vx, ib, iqs, v);
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y[iybs + iqs + 0] = v.x;
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y[iybs + iqs + y_offset] = v.y;
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}
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template <int qk, int qr, dequantize_kernel_t dequantize_kernel>
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static __global__ void dequantize_mul_mat_vec(const void * vx, const float * y, float * dst, const int ncols, const int nrows) {
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static __global__ void dequantize_mul_mat_vec(const void * vx, const dfloat * y, float * dst, const int ncols, const int nrows) {
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// qk = quantized weights per x block
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// qr = number of quantized weights per data value in x block
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const int row = blockIdx.y*blockDim.y + threadIdx.y;
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@ -885,7 +920,12 @@ static __global__ void dequantize_mul_mat_vec(const void * vx, const float * y,
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const int vals_per_iter = iter_stride / WARP_SIZE; // num quantized vals per thread and i iter
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const int y_offset = qr == 1 ? 1 : qk/2;
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float tmp = 0.0f; // partial sum for thread in warp
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// partial sum for each thread
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#ifdef GGML_CUDA_DMMV_F16
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half2 tmp = {0.0f, 0.0f}; // two sums for f16 to take advantage of half2 intrinsics
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#else
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float tmp = 0.0f;
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#endif // GGML_CUDA_DMMV_F16
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for (int i = 0; i < ncols; i += iter_stride) {
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const int col = i + vals_per_iter*tid;
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@ -899,14 +939,21 @@ static __global__ void dequantize_mul_mat_vec(const void * vx, const float * y,
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// process 2 vals per j iter
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// dequantize
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float v0, v1;
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dequantize_kernel(vx, ib, iqs + j/qr, v0, v1);
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// for qr = 2 the iqs needs to increase by 1 per j iter because 2 weights per data val
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dfloat2 v;
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dequantize_kernel(vx, ib, iqs + j/qr, v);
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// matrix multiplication
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tmp += v0 * y[iybs + iqs + j/qr + 0];
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tmp += v1 * y[iybs + iqs + j/qr + y_offset];
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// for qr = 2 the y index needs to increase by 1 per j iter because of y_offset = qk/2
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#ifdef GGML_CUDA_DMMV_F16
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tmp += __hmul2(v, {
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y[iybs + iqs + j/qr + 0],
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y[iybs + iqs + j/qr + y_offset]
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});
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#else
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tmp += v.x * y[iybs + iqs + j/qr + 0];
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tmp += v.y * y[iybs + iqs + j/qr + y_offset];
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#endif // GGML_CUDA_DMMV_F16
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}
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}
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@ -918,7 +965,11 @@ static __global__ void dequantize_mul_mat_vec(const void * vx, const float * y,
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}
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if (tid == 0) {
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#ifdef GGML_CUDA_DMMV_F16
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dst[row] = tmp.x + tmp.y;
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#else
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dst[row] = tmp;
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#endif // GGML_CUDA_DMMV_F16
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}
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}
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@ -1213,7 +1264,7 @@ static void dequantize_row_q6_K_cuda(const void * vx, float * y, const int k, cu
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dequantize_block_q6_K<<<nb, 64, 0, stream>>>(vx, y);
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}
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static void dequantize_mul_mat_vec_q4_0_cuda(const void * vx, const float * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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static void dequantize_mul_mat_vec_q4_0_cuda(const void * vx, const dfloat * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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GGML_ASSERT(ncols % GGML_CUDA_DMMV_X == 0);
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const int block_num_y = (nrows + GGML_CUDA_DMMV_Y - 1) / GGML_CUDA_DMMV_Y;
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const dim3 block_nums(1, block_num_y, 1);
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@ -1222,7 +1273,7 @@ static void dequantize_mul_mat_vec_q4_0_cuda(const void * vx, const float * y, f
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<<<block_nums, block_dims, 0, stream>>>(vx, y, dst, ncols, nrows);
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}
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static void dequantize_mul_mat_vec_q4_1_cuda(const void * vx, const float * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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static void dequantize_mul_mat_vec_q4_1_cuda(const void * vx, const dfloat * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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GGML_ASSERT(ncols % GGML_CUDA_DMMV_X == 0);
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const int block_num_y = (nrows + GGML_CUDA_DMMV_Y - 1) / GGML_CUDA_DMMV_Y;
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const dim3 block_nums(1, block_num_y, 1);
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@ -1231,7 +1282,7 @@ static void dequantize_mul_mat_vec_q4_1_cuda(const void * vx, const float * y, f
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<<<block_nums, block_dims, 0, stream>>>(vx, y, dst, ncols, nrows);
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}
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static void dequantize_mul_mat_vec_q5_0_cuda(const void * vx, const float * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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static void dequantize_mul_mat_vec_q5_0_cuda(const void * vx, const dfloat * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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GGML_ASSERT(ncols % GGML_CUDA_DMMV_X == 0);
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const int block_num_y = (nrows + GGML_CUDA_DMMV_Y - 1) / GGML_CUDA_DMMV_Y;
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const dim3 block_nums(1, block_num_y, 1);
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@ -1240,7 +1291,7 @@ static void dequantize_mul_mat_vec_q5_0_cuda(const void * vx, const float * y, f
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<<<block_nums, block_dims, 0, stream>>>(vx, y, dst, ncols, nrows);
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}
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static void dequantize_mul_mat_vec_q5_1_cuda(const void * vx, const float * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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static void dequantize_mul_mat_vec_q5_1_cuda(const void * vx, const dfloat * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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GGML_ASSERT(ncols % GGML_CUDA_DMMV_X == 0);
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const int block_num_y = (nrows + GGML_CUDA_DMMV_Y - 1) / GGML_CUDA_DMMV_Y;
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const dim3 block_nums(1, block_num_y, 1);
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@ -1249,7 +1300,7 @@ static void dequantize_mul_mat_vec_q5_1_cuda(const void * vx, const float * y, f
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<<<block_nums, block_dims, 0, stream>>>(vx, y, dst, ncols, nrows);
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}
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static void dequantize_mul_mat_vec_q8_0_cuda(const void * vx, const float * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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static void dequantize_mul_mat_vec_q8_0_cuda(const void * vx, const dfloat * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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GGML_ASSERT(ncols % GGML_CUDA_DMMV_X == 0);
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const int block_num_y = (nrows + GGML_CUDA_DMMV_Y - 1) / GGML_CUDA_DMMV_Y;
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const dim3 block_nums(1, block_num_y, 1);
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@ -1299,7 +1350,7 @@ static void convert_fp16_to_fp32_cuda(const void * vx, float * y, const int k, c
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dequantize_block<1, 1, convert_f16><<<num_blocks, CUDA_DEQUANTIZE_BLOCK_SIZE, 0, stream>>>(vx, y, k);
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}
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static void convert_mul_mat_vec_f16_cuda(const void * vx, const float * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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static void convert_mul_mat_vec_f16_cuda(const void * vx, const dfloat * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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GGML_ASSERT(ncols % GGML_CUDA_DMMV_X == 0);
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const int block_num_y = (nrows + GGML_CUDA_DMMV_Y - 1) / GGML_CUDA_DMMV_Y;
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const dim3 block_nums(1, block_num_y, 1);
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@ -1714,21 +1765,40 @@ inline void ggml_cuda_op_dequantize_mul_mat_vec(
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const int64_t ne00 = src0->ne[0];
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const int64_t nrows = i01_high - i01_low;
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// on some GPUs it is faster to convert src1 to half and to use half precision intrinsics
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#ifdef GGML_CUDA_DMMV_F16
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size_t ash;
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dfloat * src1_dfloat = nullptr; // dfloat == half
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bool src1_convert_f16 = src0->type == GGML_TYPE_Q4_0 || src0->type == GGML_TYPE_Q4_1 ||
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src0->type == GGML_TYPE_Q5_0 || src0->type == GGML_TYPE_Q5_1 ||
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src0->type == GGML_TYPE_Q8_0 || src0->type == GGML_TYPE_F16;
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if (src1_convert_f16) {
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src1_dfloat = (half *) ggml_cuda_pool_malloc(ne00*sizeof(half), &ash);
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ggml_cpy_f32_f16_cuda((char *) src1_ddf_i, (char *) src1_dfloat, ne00,
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ne00, 1, sizeof(float), 0, 0,
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||||
ne00, 1, sizeof(half), 0, 0, cudaStream_main);
|
||||
}
|
||||
#else
|
||||
dfloat * src1_dfloat = src1_ddf_i; // dfloat == float, no conversion
|
||||
#endif // GGML_CUDA_DMMV_F16
|
||||
|
||||
switch (src0->type) {
|
||||
case GGML_TYPE_Q4_0:
|
||||
dequantize_mul_mat_vec_q4_0_cuda(src0_ddq_i, src1_ddf_i, dst_ddf_i, ne00, nrows, cudaStream_main);
|
||||
dequantize_mul_mat_vec_q4_0_cuda(src0_ddq_i, src1_dfloat, dst_ddf_i, ne00, nrows, cudaStream_main);
|
||||
break;
|
||||
case GGML_TYPE_Q4_1:
|
||||
dequantize_mul_mat_vec_q4_1_cuda(src0_ddq_i, src1_ddf_i, dst_ddf_i, ne00, nrows, cudaStream_main);
|
||||
dequantize_mul_mat_vec_q4_1_cuda(src0_ddq_i, src1_dfloat, dst_ddf_i, ne00, nrows, cudaStream_main);
|
||||
break;
|
||||
case GGML_TYPE_Q5_0:
|
||||
dequantize_mul_mat_vec_q5_0_cuda(src0_ddq_i, src1_ddf_i, dst_ddf_i, ne00, nrows, cudaStream_main);
|
||||
dequantize_mul_mat_vec_q5_0_cuda(src0_ddq_i, src1_dfloat, dst_ddf_i, ne00, nrows, cudaStream_main);
|
||||
break;
|
||||
case GGML_TYPE_Q5_1:
|
||||
dequantize_mul_mat_vec_q5_1_cuda(src0_ddq_i, src1_ddf_i, dst_ddf_i, ne00, nrows, cudaStream_main);
|
||||
dequantize_mul_mat_vec_q5_1_cuda(src0_ddq_i, src1_dfloat, dst_ddf_i, ne00, nrows, cudaStream_main);
|
||||
break;
|
||||
case GGML_TYPE_Q8_0:
|
||||
dequantize_mul_mat_vec_q8_0_cuda(src0_ddq_i, src1_ddf_i, dst_ddf_i, ne00, nrows, cudaStream_main);
|
||||
dequantize_mul_mat_vec_q8_0_cuda(src0_ddq_i, src1_dfloat, dst_ddf_i, ne00, nrows, cudaStream_main);
|
||||
break;
|
||||
case GGML_TYPE_Q2_K:
|
||||
dequantize_mul_mat_vec_q2_K_cuda(src0_ddq_i, src1_ddf_i, dst_ddf_i, ne00, nrows, cudaStream_main);
|
||||
|
|
@ -1746,7 +1816,7 @@ inline void ggml_cuda_op_dequantize_mul_mat_vec(
|
|||
dequantize_mul_mat_vec_q6_K_cuda(src0_ddq_i, src1_ddf_i, dst_ddf_i, ne00, nrows, cudaStream_main);
|
||||
break;
|
||||
case GGML_TYPE_F16:
|
||||
convert_mul_mat_vec_f16_cuda(src0_ddq_i, src1_ddf_i, dst_ddf_i, ne00, nrows, cudaStream_main);
|
||||
convert_mul_mat_vec_f16_cuda(src0_ddq_i, src1_dfloat, dst_ddf_i, ne00, nrows, cudaStream_main);
|
||||
break;
|
||||
default:
|
||||
GGML_ASSERT(false);
|
||||
|
|
@ -1754,6 +1824,12 @@ inline void ggml_cuda_op_dequantize_mul_mat_vec(
|
|||
}
|
||||
CUDA_CHECK(cudaGetLastError());
|
||||
|
||||
#ifdef GGML_CUDA_DMMV_F16
|
||||
if (src1_convert_f16) {
|
||||
ggml_cuda_pool_free(src1_dfloat, ash);
|
||||
}
|
||||
#endif // GGML_CUDA_DMMV_F16
|
||||
|
||||
(void) src1;
|
||||
(void) dst;
|
||||
(void) src0_ddf_i;
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue