cudaEvent_t events[GGML_CUDA_MAX_DEVICES]; // events for synchronizing multiple GPUs
};
-static __global__ void add_f32(const float * x, const float * y, float * dst, const int k) {
+static __global__ void add_f32(const float * x, const float * y, float * dst, const int kx, const int ky) {
const int i = blockDim.x*blockIdx.x + threadIdx.x;
- if (i >= k) {
+ if (i >= kx) {
return;
}
- dst[i] = x[i] + y[i];
+ dst[i] = x[i] + y[i%ky];
}
static __global__ void add_f16_f32_f16(const half * x, const float * y, half * dst, const int k) {
dst[i] = scale * x[i];
}
-static void add_f32_cuda(const float * x, const float * y, float * dst, const int k, cudaStream_t stream) {
- const int num_blocks = (k + CUDA_ADD_BLOCK_SIZE - 1) / CUDA_ADD_BLOCK_SIZE;
- add_f32<<<num_blocks, CUDA_ADD_BLOCK_SIZE, 0, stream>>>(x, y, dst, k);
+static void add_f32_cuda(const float * x, const float * y, float * dst, const int kx, const int ky, cudaStream_t stream) {
+ const int num_blocks = (kx + CUDA_ADD_BLOCK_SIZE - 1) / CUDA_ADD_BLOCK_SIZE;
+ add_f32<<<num_blocks, CUDA_ADD_BLOCK_SIZE, 0, stream>>>(x, y, dst, kx, ky);
}
static void add_f16_f32_f16_cuda(const half * x, const float * y, half * dst, const int k, cudaStream_t stream) {
GGML_ASSERT(src1_ddf_i != nullptr);
GGML_ASSERT(dst_ddf_i != nullptr);
- const int64_t ne0 = src0->ne[0];
+ const int64_t ne00 = src0->ne[0];
const int64_t i01_diff = i01_high - i01_low;
+ const int64_t ne10 = src1->ne[0];
+
// compute
if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) {
- add_f32_cuda(src0_ddf_i, src1_ddf_i, dst_ddf_i, ne0*i01_diff, cudaStream_main);
+ add_f32_cuda(src0_ddf_i, src1_ddf_i, dst_ddf_i, ne00*i01_diff, ne10, cudaStream_main);
} else if (src0->type == GGML_TYPE_F16 && dst->type == GGML_TYPE_F16) {
- add_f16_f32_f16_cuda((half *) src0_ddq_i, src1_ddf_i, (half *) dst_ddf_i, ne0*i01_diff, cudaStream_main);
+ add_f16_f32_f16_cuda((half *) src0_ddq_i, src1_ddf_i, (half *) dst_ddf_i, ne00*i01_diff, cudaStream_main);
} else {
GGML_ASSERT(false);
}
struct ggml_tensor * a,
struct ggml_tensor * b,
bool inplace) {
- GGML_ASSERT(ggml_are_same_shape(a, b));
+ // TODO: support less-strict constraint
+ // GGML_ASSERT(ggml_can_repeat(b, a));
+ GGML_ASSERT(ggml_can_repeat_rows(b, a));
bool is_node = false;
- if (a->grad || b->grad) {
+ if (!inplace && (a->grad || b->grad)) {
+ // TODO: support backward pass for broadcasting
+ GGML_ASSERT(ggml_are_same_shape(a, b));
is_node = true;
}
const struct ggml_tensor * src0,
const struct ggml_tensor * src1,
struct ggml_tensor * dst) {
- GGML_ASSERT(ggml_are_same_shape(src0, src1) && ggml_are_same_shape(src0, dst));
+ GGML_ASSERT(ggml_can_repeat_rows(src1, src0) && ggml_are_same_shape(src0, dst));
if (params->type == GGML_TASK_INIT || params->type == GGML_TASK_FINALIZE) {
return;
if (nb10 == sizeof(float)) {
for (int ir = ir0; ir < ir1; ++ir) {
- // src0, src1 and dst are same shape => same indices
- const int i3 = ir/(ne2*ne1);
- const int i2 = (ir - i3*ne2*ne1)/ne1;
- const int i1 = (ir - i3*ne2*ne1 - i2*ne1);
+ // src1 is broadcastable across src0 and dst in i1, i2, i3
+ const int64_t i03 = ir/(ne02*ne01);
+ const int64_t i02 = (ir - i03*ne02*ne01)/ne01;
+ const int64_t i01 = (ir - i03*ne02*ne01 - i02*ne01);
+ const int64_t i13 = i03 % ne13;
+ const int64_t i12 = i02 % ne12;
+ const int64_t i11 = i01 % ne11;
+
+ float * dst_ptr = (float *) ((char *) dst->data + i03*nb3 + i02*nb2 + i01*nb1 );
+ float * src0_ptr = (float *) ((char *) src0->data + i03*nb03 + i02*nb02 + i01*nb01);
+ float * src1_ptr = (float *) ((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11);
#ifdef GGML_USE_ACCELERATE
- vDSP_vadd(
- (float *) ((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01), 1,
- (float *) ((char *) src1->data + i3*nb13 + i2*nb12 + i1*nb11), 1,
- (float *) ((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1 ), 1,
- ne0);
+ vDSP_vadd(src0_ptr, 1, src1_ptr, 1, dst_ptr, 1, ne00);
#else
- ggml_vec_add_f32(ne0,
- (float *) ((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1 ),
- (float *) ((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01),
- (float *) ((char *) src1->data + i3*nb13 + i2*nb12 + i1*nb11));
+ ggml_vec_add_f32(ne00, dst_ptr, src0_ptr, src1_ptr);
#endif
// }
// }
} else {
// src1 is not contiguous
for (int ir = ir0; ir < ir1; ++ir) {
- // src0, src1 and dst are same shape => same indices
- const int i3 = ir/(ne2*ne1);
- const int i2 = (ir - i3*ne2*ne1)/ne1;
- const int i1 = (ir - i3*ne2*ne1 - i2*ne1);
+ // src1 is broadcastable across src0 and dst in i1, i2, i3
+ const int64_t i03 = ir/(ne02*ne01);
+ const int64_t i02 = (ir - i03*ne02*ne01)/ne01;
+ const int64_t i01 = (ir - i03*ne02*ne01 - i02*ne01);
+
+ const int64_t i13 = i03 % ne13;
+ const int64_t i12 = i02 % ne12;
+ const int64_t i11 = i01 % ne11;
+
+ float * dst_ptr = (float *) ((char *) dst->data + i03*nb3 + i02*nb2 + i01*nb1 );
+ float * src0_ptr = (float *) ((char *) src0->data + i03*nb03 + i02*nb02 + i01*nb01);
- float * dst_ptr = (float *) ((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1 );
- float * src0_ptr = (float *) ((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01);
for (int i0 = 0; i0 < ne0; i0++) {
- float * src1_ptr = (float *) ((char *) src1->data + i3*nb13 + i2*nb12 + i1*nb11 + i0*nb10);
+ float * src1_ptr = (float *) ((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11 + i0*nb10);
dst_ptr[i0] = src0_ptr[i0] + *src1_ptr;
}