mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-11-13 14:29:52 +00:00
cuda: add q8_0->f32 cpy operation (#9571)
llama: enable K-shift for quantized KV cache It will fail on unsupported backends or quant types.
This commit is contained in:
parent
0b3bf966f4
commit
116efee0ee
@ -2899,6 +2899,9 @@ GGML_CALL static bool ggml_backend_cuda_supports_op(ggml_backend_t backend, cons
|
||||
if (src0_type == GGML_TYPE_F32 && src1_type == GGML_TYPE_Q8_0) {
|
||||
return true;
|
||||
}
|
||||
if (src0_type == GGML_TYPE_Q8_0 && src1_type == GGML_TYPE_F32) {
|
||||
return true;
|
||||
}
|
||||
if (src0_type == GGML_TYPE_F32 && src1_type == GGML_TYPE_Q4_0) {
|
||||
return true;
|
||||
}
|
||||
|
@ -81,6 +81,17 @@ static __device__ void cpy_blck_f32_q8_0(const char * cxi, char * cdsti) {
|
||||
}
|
||||
}
|
||||
|
||||
static __device__ void cpy_blck_q8_0_f32(const char * cxi, char * cdsti) {
|
||||
const block_q8_0 * xi = (const block_q8_0 *) cxi;
|
||||
float * dsti = (float *) cdsti;
|
||||
|
||||
const float d = (float)xi->d;
|
||||
|
||||
for (int j = 0; j < QK8_0; j++) {
|
||||
dsti[j] = xi->qs[j] * d;
|
||||
}
|
||||
}
|
||||
|
||||
static __device__ void cpy_blck_f32_q4_0(const char * cxi, char * cdsti) {
|
||||
const float * xi = (const float *) cxi;
|
||||
block_q4_0 * dsti = (block_q4_0 *) cdsti;
|
||||
@ -288,6 +299,32 @@ static __global__ void cpy_f32_q(const char * cx, char * cdst, const int ne,
|
||||
cpy_blck(cx + x_offset, cdst + dst_offset);
|
||||
}
|
||||
|
||||
template <cpy_kernel_t cpy_blck, int qk>
|
||||
static __global__ void cpy_q_f32(const char * cx, char * cdst, const int ne,
|
||||
const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
|
||||
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11,
|
||||
const int nb12, const int nb13) {
|
||||
const int i = (blockDim.x*blockIdx.x + threadIdx.x)*qk;
|
||||
|
||||
if (i >= ne) {
|
||||
return;
|
||||
}
|
||||
|
||||
const int i03 = i/(ne00 * ne01 * ne02);
|
||||
const int i02 = (i - i03*ne00*ne01*ne02 )/ (ne00*ne01);
|
||||
const int i01 = (i - i03*ne00*ne01*ne02 - i02*ne01*ne00) / ne00;
|
||||
const int i00 = i - i03*ne00*ne01*ne02 - i02*ne01*ne00 - i01*ne00;
|
||||
const int x_offset = (i00/qk)*nb00 + i01*nb01 + i02*nb02 + i03 * nb03;
|
||||
|
||||
const int i13 = i/(ne10 * ne11 * ne12);
|
||||
const int i12 = (i - i13*ne10*ne11*ne12) / (ne10*ne11);
|
||||
const int i11 = (i - i13*ne10*ne11*ne12 - i12*ne10*ne11) / ne10;
|
||||
const int i10 = i - i13*ne10*ne11*ne12 - i12*ne10*ne11 - i11*ne10;
|
||||
const int dst_offset = i10*nb10 + i11*nb11 + i12*nb12 + i13*nb13;
|
||||
|
||||
cpy_blck(cx + x_offset, cdst + dst_offset);
|
||||
}
|
||||
|
||||
static void ggml_cpy_f16_f32_cuda(
|
||||
const char * cx, char * cdst, const int ne,
|
||||
const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
|
||||
@ -329,6 +366,16 @@ static void ggml_cpy_f32_q8_0_cuda(
|
||||
(cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
|
||||
}
|
||||
|
||||
static void ggml_cpy_q8_0_f32_cuda(
|
||||
const char * cx, char * cdst, const int ne,
|
||||
const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
|
||||
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {
|
||||
|
||||
const int num_blocks = ne;
|
||||
cpy_q_f32<cpy_blck_q8_0_f32, QK8_0><<<num_blocks, 1, 0, stream>>>
|
||||
(cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
|
||||
}
|
||||
|
||||
static void ggml_cpy_f32_q4_0_cuda(
|
||||
const char * cx, char * cdst, const int ne,
|
||||
const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
|
||||
@ -437,6 +484,8 @@ void ggml_cuda_cpy(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, gg
|
||||
ggml_cpy_f32_f16_cuda (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
|
||||
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q8_0) {
|
||||
ggml_cpy_f32_q8_0_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
|
||||
} else if (src0->type == GGML_TYPE_Q8_0 && src1->type == GGML_TYPE_F32) {
|
||||
ggml_cpy_q8_0_f32_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
|
||||
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q4_0) {
|
||||
ggml_cpy_f32_q4_0_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
|
||||
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q4_1) {
|
||||
@ -471,6 +520,8 @@ void* ggml_cuda_cpy_fn(const ggml_tensor * src0, ggml_tensor * src1) {
|
||||
return (void*) cpy_f32_f16<cpy_1_f32_f16>;
|
||||
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q8_0) {
|
||||
return (void*) cpy_f32_q<cpy_blck_f32_q8_0, QK8_0>;
|
||||
} else if (src0->type == GGML_TYPE_Q8_0 && src1->type == GGML_TYPE_F32) {
|
||||
return (void*) cpy_q_f32<cpy_blck_q8_0_f32, QK8_0>;
|
||||
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q4_0) {
|
||||
return (void*) cpy_f32_q<cpy_blck_f32_q4_0, QK4_0>;
|
||||
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q4_1) {
|
||||
|
@ -9930,17 +9930,36 @@ struct llm_build_context {
|
||||
const int64_t n_head_kv = hparams.n_head_kv(il);
|
||||
const int64_t n_embd_k_gqa = hparams.n_embd_k_gqa(il);
|
||||
struct ggml_tensor * rope_factors = build_rope_factors(il);
|
||||
struct ggml_tensor * tmp =
|
||||
// we rotate only the first n_rot dimensions
|
||||
ggml_rope_ext_inplace(ctx0,
|
||||
ggml_view_3d(ctx0, kv_self.k_l[il],
|
||||
n_embd_head_k, n_head_kv, n_ctx,
|
||||
ggml_row_size(kv_self.k_l[il]->type, n_embd_head_k),
|
||||
ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa),
|
||||
0),
|
||||
struct ggml_tensor * k =
|
||||
ggml_view_3d(ctx0, kv_self.k_l[il],
|
||||
n_embd_head_k, n_head_kv, n_ctx,
|
||||
ggml_row_size(kv_self.k_l[il]->type, n_embd_head_k),
|
||||
ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa),
|
||||
0);
|
||||
|
||||
struct ggml_tensor * tmp;
|
||||
if (ggml_is_quantized(k->type)) {
|
||||
// dequantize to f32 -> RoPE -> quantize back
|
||||
tmp = ggml_cast(ctx0, k, GGML_TYPE_F32);
|
||||
cb(tmp, "K_f32", il);
|
||||
for (auto * backend : lctx.backends) {
|
||||
// Figure out which backend KV cache belongs to
|
||||
if (ggml_backend_supports_buft(backend, lctx.model.buft_layer[il].buft)) {
|
||||
ggml_backend_sched_set_tensor_backend(lctx.sched, tmp, backend);
|
||||
break;
|
||||
}
|
||||
}
|
||||
tmp = ggml_rope_ext_inplace(ctx0, tmp,
|
||||
lctx.inp_K_shift, rope_factors, n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
|
||||
ext_factor, attn_factor, beta_fast, beta_slow);
|
||||
|
||||
cb(tmp, "K_shifted_f32", il);
|
||||
tmp = ggml_cpy(ctx0, tmp, k);
|
||||
} else {
|
||||
// we rotate only the first n_rot dimensions
|
||||
tmp = ggml_rope_ext_inplace(ctx0, k,
|
||||
lctx.inp_K_shift, rope_factors, n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
|
||||
ext_factor, attn_factor, beta_fast, beta_slow);
|
||||
}
|
||||
cb(tmp, "K_shifted", il);
|
||||
ggml_build_forward_expand(gf, tmp);
|
||||
}
|
||||
|
Loading…
Reference in New Issue
Block a user