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consolidate error checking in ggml_cuda_set_device

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slaren 2023-12-25 20:53:23 +01:00
parent 32304d796f
commit 692887fbe4
1 changed files with 18 additions and 19 deletions
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35
ggml-cuda.cu
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@ -530,15 +530,15 @@ struct ggml_tensor_extra_gpu {
// this is faster on Windows
// probably because the Windows CUDA libraries forget to make this check before invoking the drivers
inline cudaError_t ggml_cuda_set_device(const int device) {
inline void ggml_cuda_set_device(const int device) {
int current_device;
CUDA_CHECK(cudaGetDevice(&current_device));
if (device == current_device) {
return cudaSuccess;
return;
}
return cudaSetDevice(device);
CUDA_CHECK(cudaSetDevice(device));
}
static int g_device_count = -1;
@ -6871,7 +6871,7 @@ void ggml_init_cublas() {
}
for (int id = 0; id < g_device_count; ++id) {
CUDA_CHECK(ggml_cuda_set_device(id));
ggml_cuda_set_device(id);
// create cuda streams
for (int is = 0; is < MAX_STREAMS; ++is) {
@ -7982,12 +7982,12 @@ static void ggml_cuda_set_peer_access(const int n_tokens) {
#ifdef NDEBUG
for (int id = 0; id < g_device_count; ++id) {
CUDA_CHECK(ggml_cuda_set_device(id));
ggml_cuda_set_device(id);
CUDA_CHECK(cudaDeviceSynchronize());
}
for (int id = 0; id < g_device_count; ++id) {
CUDA_CHECK(ggml_cuda_set_device(id));
ggml_cuda_set_device(id);
for (int id_other = 0; id_other < g_device_count; ++id_other) {
if (id == id_other) {
@ -8154,7 +8154,7 @@ static void ggml_cuda_op_mul_mat(
// if multiple devices are used they need to wait for the main device
// here an event is recorded that signals that the main device has finished calculating the input data
if (split && used_devices > 1) {
CUDA_CHECK(ggml_cuda_set_device(g_main_device));
ggml_cuda_set_device(g_main_device);
CUDA_CHECK(cudaEventRecord(src0_extra->events[g_main_device][0], g_cudaStreams[g_main_device][0]));
}
@ -8294,7 +8294,7 @@ static void ggml_cuda_op_mul_mat(
int64_t is_max = (ne11 + MUL_MAT_SRC1_COL_STRIDE - 1) / MUL_MAT_SRC1_COL_STRIDE;
is_max = is_max <= MAX_STREAMS ? is_max : MAX_STREAMS;
CUDA_CHECK(ggml_cuda_set_device(g_main_device));
ggml_cuda_set_device(g_main_device);
for (int64_t id = 0; id < g_device_count; ++id) {
if (dev[id].row_low == dev[id].row_high) {
continue;
@ -8306,7 +8306,7 @@ static void ggml_cuda_op_mul_mat(
}
if (dst->backend == GGML_BACKEND_CPU) {
CUDA_CHECK(ggml_cuda_set_device(g_main_device));
ggml_cuda_set_device(g_main_device);
CUDA_CHECK(cudaDeviceSynchronize());
}
}
@ -8416,7 +8416,7 @@ static void ggml_cuda_mul_mat_vec_p021(const ggml_tensor * src0, const ggml_tens
const int64_t ne12 = src1->ne[2];
CUDA_CHECK(ggml_cuda_set_device(g_main_device));
ggml_cuda_set_device(g_main_device);
cudaStream_t main_stream = g_cudaStreams[g_main_device][0];
ggml_tensor_extra_gpu * src0_extra = (ggml_tensor_extra_gpu *) src0->extra;
@ -8448,7 +8448,7 @@ static void ggml_cuda_mul_mat_vec_nc(const ggml_tensor * src0, const ggml_tensor
const int64_t ne12 = src1->ne[2];
CUDA_CHECK(ggml_cuda_set_device(g_main_device));
ggml_cuda_set_device(g_main_device);
cudaStream_t main_stream = g_cudaStreams[g_main_device][0];
ggml_tensor_extra_gpu * src0_extra = (ggml_tensor_extra_gpu *) src0->extra;
@ -8519,7 +8519,7 @@ static void ggml_cuda_mul_mat_mat_batched_cublas(const ggml_tensor * src0, const
const int64_t ne1 = ggml_nelements(src1);
const int64_t ne = ggml_nelements(dst);
CUDA_CHECK(ggml_cuda_set_device(g_main_device));
ggml_cuda_set_device(g_main_device);
cudaStream_t main_stream = g_cudaStreams[g_main_device][0];
CUBLAS_CHECK(cublasSetStream(g_cublas_handles[g_main_device], main_stream));
@ -8803,7 +8803,7 @@ static void ggml_cuda_mul_mat_id_cublas(ggml_tensor * dst) {
const int64_t ne1 = ggml_nelements(src1);
const int64_t ne = ggml_nelements(dst);
CUDA_CHECK(ggml_cuda_set_device(g_main_device));
ggml_cuda_set_device(g_main_device);
cudaStream_t main_stream = g_cudaStreams[g_main_device][0];
CUBLAS_CHECK(cublasSetStream(g_cublas_handles[g_main_device], main_stream));
@ -9077,7 +9077,7 @@ static void ggml_cuda_cpy(const ggml_tensor * src0, const ggml_tensor * src1, gg
const int64_t nb11 = src1->nb[1];
const int64_t nb12 = src1->nb[2];
CUDA_CHECK(ggml_cuda_set_device(g_main_device));
ggml_cuda_set_device(g_main_device);
cudaStream_t main_stream = g_cudaStreams[g_main_device][0];
const ggml_tensor_extra_gpu * src0_extra = (ggml_tensor_extra_gpu *) src0->extra;
@ -9239,14 +9239,13 @@ void ggml_cuda_free_data(struct ggml_tensor * tensor) {
ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) tensor->extra;
for (int64_t id = 0; id < g_device_count; ++id) {
ggml_cuda_set_device(id);
if (extra->data_device[id] != nullptr) {
CUDA_CHECK(ggml_cuda_set_device(id));
CUDA_CHECK(cudaFree(extra->data_device[id]));
}
for (int64_t is = 0; is < MAX_STREAMS; ++is) {
if (extra->events[id][is] != nullptr) {
CUDA_CHECK(ggml_cuda_set_device(id));
CUDA_CHECK(cudaEventDestroy(extra->events[id][is]));
}
}
@ -9300,7 +9299,7 @@ static void ggml_cuda_assign_buffers_impl(struct ggml_tensor * tensor, bool scra
force_inplace;
const size_t size = ggml_nbytes(tensor);
CUDA_CHECK(ggml_cuda_set_device(g_main_device));
ggml_cuda_set_device(g_main_device);
if (inplace && (tensor->src[0]->backend == GGML_BACKEND_GPU || tensor->src[0]->backend == GGML_BACKEND_GPU_SPLIT)) {
ggml_tensor_extra_gpu * src0_extra = (ggml_tensor_extra_gpu * ) tensor->src[0]->extra;
char * src0_ddc = (char *) src0_extra->data_device[g_main_device];
@ -9377,7 +9376,7 @@ void ggml_cuda_copy_to_device(struct ggml_tensor * tensor) {
GGML_ASSERT(ggml_is_contiguous(tensor));
ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) tensor->extra;
CUDA_CHECK(ggml_cuda_set_device(g_main_device));
ggml_cuda_set_device(g_main_device);
CUDA_CHECK(cudaMemcpy(extra->data_device[g_main_device], tensor->data, ggml_nbytes(tensor), cudaMemcpyHostToDevice));
}