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ggml : introduce GGML_CALL function annotation (#4850)

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This change makes it possible to build ggml-cuda.cu and ggml-metal.m as
independent dynamic shared objects, that may be conditionally linked at
runtime in a multiplatform binary. It introduces a GGML_CALL annotation
that documents which functions have a cyclic call relationship, between
the application code and GPU modules.

This change does nothing, unless the build defines -DGGML_MULTIPLATFORM
which causes back-references and function pointers to conform to MS ABI
which is supported by NVCC, ROCm, XCode, GCC and Clang across platforms
This commit is contained in:
Justine Tunney 2024-01-16 03:16:33 -08:00 • committed by GitHub
parent d75c232e1d
commit a0b3ac8c48
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GPG key ID: 4AEE18F83AFDEB23
9 changed files with 244 additions and 235 deletions
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121
ggml-cuda.cu
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@ -7615,11 +7615,11 @@ struct cuda_pool_alloc {
static bool g_cublas_loaded = false;
bool ggml_cublas_loaded(void) {
GGML_CALL bool ggml_cublas_loaded(void) {
return g_cublas_loaded;
}
void ggml_init_cublas() {
GGML_CALL void ggml_init_cublas() {
static bool initialized = false;
if (!initialized) {
@ -7707,7 +7707,7 @@ void ggml_init_cublas() {
}
}
void * ggml_cuda_host_malloc(size_t size) {
GGML_CALL void * ggml_cuda_host_malloc(size_t size) {
if (getenv("GGML_CUDA_NO_PINNED") != nullptr) {
return nullptr;
}
@ -7725,7 +7725,7 @@ void * ggml_cuda_host_malloc(size_t size) {
return ptr;
}
void ggml_cuda_host_free(void * ptr) {
GGML_CALL void ggml_cuda_host_free(void * ptr) {
CUDA_CHECK(cudaFreeHost(ptr));
}
@ -9242,7 +9242,7 @@ static void ggml_cuda_rms_norm(const ggml_tensor * src0, const ggml_tensor * src
ggml_cuda_op_flatten(src0, src1, dst, ggml_cuda_op_rms_norm);
}
bool ggml_cuda_can_mul_mat(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst) {
GGML_CALL bool ggml_cuda_can_mul_mat(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst) {
if (!g_cublas_loaded) return false;
const int64_t ne10 = src1->ne[0];
@ -10013,7 +10013,7 @@ static size_t ggml_nbytes_split(const struct ggml_tensor * tensor, int nrows_spl
return nrows_split*ggml_row_size(tensor->type, tensor->ne[0]);
}
static void ggml_cuda_set_main_device(const int main_device) {
GGML_CALL static void ggml_cuda_set_main_device(const int main_device) {
if (main_device >= g_device_count) {
fprintf(stderr, "warning: cannot set main_device=%d because there are only %d devices. Using device %d instead.\n",
main_device, g_device_count, g_main_device);
@ -10028,7 +10028,7 @@ static void ggml_cuda_set_main_device(const int main_device) {
}
}
bool ggml_cuda_compute_forward(struct ggml_compute_params * params, struct ggml_tensor * tensor) {
GGML_CALL bool ggml_cuda_compute_forward(struct ggml_compute_params * params, struct ggml_tensor * tensor) {
if (!g_cublas_loaded) return false;
ggml_cuda_func_t func;
@ -10186,7 +10186,7 @@ bool ggml_cuda_compute_forward(struct ggml_compute_params * params, struct ggml_
return true;
}
int ggml_cuda_get_device_count() {
GGML_CALL int ggml_cuda_get_device_count() {
int device_count;
if (cudaGetDeviceCount(&device_count) != cudaSuccess) {
return 0;
@ -10194,7 +10194,7 @@ int ggml_cuda_get_device_count() {
return device_count;
}
void ggml_cuda_get_device_description(int device, char * description, size_t description_size) {
GGML_CALL void ggml_cuda_get_device_description(int device, char * description, size_t description_size) {
cudaDeviceProp prop;
CUDA_CHECK(cudaGetDeviceProperties(&prop, device));
snprintf(description, description_size, "%s", prop.name);
@ -10244,27 +10244,27 @@ struct ggml_backend_cuda_buffer_context {
}
};
static const char * ggml_backend_cuda_buffer_get_name(ggml_backend_buffer_t buffer) {
GGML_CALL static const char * ggml_backend_cuda_buffer_get_name(ggml_backend_buffer_t buffer) {
ggml_backend_cuda_buffer_context * ctx = (ggml_backend_cuda_buffer_context *)buffer->context;
return ctx->name.c_str();
}
static bool ggml_backend_buffer_is_cuda(ggml_backend_buffer_t buffer) {
GGML_CALL static bool ggml_backend_buffer_is_cuda(ggml_backend_buffer_t buffer) {
return buffer->iface.get_name == ggml_backend_cuda_buffer_get_name;
}
static void ggml_backend_cuda_buffer_free_buffer(ggml_backend_buffer_t buffer) {
GGML_CALL static void ggml_backend_cuda_buffer_free_buffer(ggml_backend_buffer_t buffer) {
ggml_backend_cuda_buffer_context * ctx = (ggml_backend_cuda_buffer_context *)buffer->context;
CUDA_CHECK(cudaFree(ctx->dev_ptr));
delete ctx;
}
static void * ggml_backend_cuda_buffer_get_base(ggml_backend_buffer_t buffer) {
GGML_CALL static void * ggml_backend_cuda_buffer_get_base(ggml_backend_buffer_t buffer) {
ggml_backend_cuda_buffer_context * ctx = (ggml_backend_cuda_buffer_context *)buffer->context;
return ctx->dev_ptr;
}
static void ggml_backend_cuda_buffer_init_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor) {
GGML_CALL static void ggml_backend_cuda_buffer_init_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor) {
ggml_backend_cuda_buffer_context * ctx = (ggml_backend_cuda_buffer_context *)buffer->context;
if (tensor->view_src != NULL && tensor->view_offs == 0) {
@ -10296,7 +10296,7 @@ static void ggml_backend_cuda_buffer_init_tensor(ggml_backend_buffer_t buffer, g
}
}
static void ggml_backend_cuda_buffer_set_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
GGML_CALL static void ggml_backend_cuda_buffer_set_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
GGML_ASSERT(tensor->backend == GGML_BACKEND_GPU);
ggml_backend_cuda_buffer_context * ctx = (ggml_backend_cuda_buffer_context *)buffer->context;
@ -10307,7 +10307,7 @@ static void ggml_backend_cuda_buffer_set_tensor(ggml_backend_buffer_t buffer, gg
CUDA_CHECK(cudaDeviceSynchronize());
}
static void ggml_backend_cuda_buffer_get_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * tensor, void * data, size_t offset, size_t size) {
GGML_CALL static void ggml_backend_cuda_buffer_get_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * tensor, void * data, size_t offset, size_t size) {
GGML_ASSERT(tensor->backend == GGML_BACKEND_GPU);
ggml_backend_cuda_buffer_context * ctx = (ggml_backend_cuda_buffer_context *)buffer->context;
@ -10318,7 +10318,7 @@ static void ggml_backend_cuda_buffer_get_tensor(ggml_backend_buffer_t buffer, co
CUDA_CHECK(cudaDeviceSynchronize());
}
static bool ggml_backend_cuda_buffer_cpy_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * src, ggml_tensor * dst) {
GGML_CALL static bool ggml_backend_cuda_buffer_cpy_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * src, ggml_tensor * dst) {
if (ggml_backend_buffer_is_cuda(src->buffer)) {
ggml_backend_cuda_buffer_context * src_ctx = (ggml_backend_cuda_buffer_context *)src->buffer->context;
ggml_backend_cuda_buffer_context * dst_ctx = (ggml_backend_cuda_buffer_context *)buffer->context;
@ -10335,7 +10335,7 @@ static bool ggml_backend_cuda_buffer_cpy_tensor(ggml_backend_buffer_t buffer, co
return false;
}
static void ggml_backend_cuda_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
GGML_CALL static void ggml_backend_cuda_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
ggml_backend_cuda_buffer_context * ctx = (ggml_backend_cuda_buffer_context *)buffer->context;
ggml_cuda_set_device(ctx->device);
@ -10357,19 +10357,18 @@ static ggml_backend_buffer_i ggml_backend_cuda_buffer_interface = {
};
// cuda buffer type
struct ggml_backend_cuda_buffer_type_context {
int device;
std::string name;
};
static const char * ggml_backend_cuda_buffer_type_name(ggml_backend_buffer_type_t buft) {
GGML_CALL static const char * ggml_backend_cuda_buffer_type_name(ggml_backend_buffer_type_t buft) {
ggml_backend_cuda_buffer_type_context * ctx = (ggml_backend_cuda_buffer_type_context *)buft->context;
return ctx->name.c_str();
}
static ggml_backend_buffer_t ggml_backend_cuda_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
GGML_CALL static ggml_backend_buffer_t ggml_backend_cuda_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
ggml_backend_cuda_buffer_type_context * buft_ctx = (ggml_backend_cuda_buffer_type_context *)buft->context;
ggml_cuda_set_device(buft_ctx->device);
@ -10388,13 +10387,13 @@ static ggml_backend_buffer_t ggml_backend_cuda_buffer_type_alloc_buffer(ggml_bac
return ggml_backend_buffer_init(buft, ggml_backend_cuda_buffer_interface, ctx, size);
}
static size_t ggml_backend_cuda_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
GGML_CALL static size_t ggml_backend_cuda_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
return 128;
UNUSED(buft);
}
static size_t ggml_backend_cuda_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) {
GGML_CALL static size_t ggml_backend_cuda_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) {
int64_t row_low = 0;
int64_t row_high = ggml_nrows(tensor);
int64_t nrows_split = row_high - row_low;
@ -10414,7 +10413,7 @@ static size_t ggml_backend_cuda_buffer_type_get_alloc_size(ggml_backend_buffer_t
UNUSED(buft);
}
static bool ggml_backend_cuda_buffer_type_supports_backend(ggml_backend_buffer_type_t buft, ggml_backend_t backend) {
GGML_CALL static bool ggml_backend_cuda_buffer_type_supports_backend(ggml_backend_buffer_type_t buft, ggml_backend_t backend) {
if (!ggml_backend_is_cuda(backend)) {
return false;
}
@ -10434,7 +10433,7 @@ static ggml_backend_buffer_type_i ggml_backend_cuda_buffer_type_interface = {
/* .is_host = */ NULL,
};
ggml_backend_buffer_type_t ggml_backend_cuda_buffer_type(int device) {
GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_buffer_type(int device) {
// FIXME: this is not thread safe
if (device >= ggml_backend_cuda_get_device_count()) {
return nullptr;
@ -10479,7 +10478,7 @@ struct ggml_backend_cuda_split_buffer_context {
std::vector<ggml_tensor_extra_gpu *> tensor_extras;
};
static const char * ggml_backend_cuda_split_buffer_get_name(ggml_backend_buffer_t buffer) {
GGML_CALL static const char * ggml_backend_cuda_split_buffer_get_name(ggml_backend_buffer_t buffer) {
return GGML_CUDA_NAME "_Split";
UNUSED(buffer);
@ -10490,19 +10489,19 @@ static const char * ggml_backend_cuda_split_buffer_get_name(ggml_backend_buffer_
// return buffer->iface.get_name == ggml_backend_cuda_split_buffer_get_name;
//}
static void ggml_backend_cuda_split_buffer_free_buffer(ggml_backend_buffer_t buffer) {
GGML_CALL static void ggml_backend_cuda_split_buffer_free_buffer(ggml_backend_buffer_t buffer) {
ggml_backend_cuda_split_buffer_context * ctx = (ggml_backend_cuda_split_buffer_context *)buffer->context;
delete ctx;
}
static void * ggml_backend_cuda_split_buffer_get_base(ggml_backend_buffer_t buffer) {
GGML_CALL static void * ggml_backend_cuda_split_buffer_get_base(ggml_backend_buffer_t buffer) {
// the pointers are stored in the tensor extras, this is just a dummy address and never dereferenced
return (void *)0x1000;
UNUSED(buffer);
}
static void ggml_backend_cuda_split_buffer_init_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor) {
GGML_CALL static void ggml_backend_cuda_split_buffer_init_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor) {
GGML_ASSERT(tensor->view_src == nullptr); // views of split tensors are not supported
ggml_backend_cuda_split_buffer_context * ctx = (ggml_backend_cuda_split_buffer_context *)buffer->context;
@ -10552,7 +10551,7 @@ static void ggml_backend_cuda_split_buffer_init_tensor(ggml_backend_buffer_t buf
tensor->extra = extra;
}
static void ggml_backend_cuda_split_buffer_set_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
GGML_CALL static void ggml_backend_cuda_split_buffer_set_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
// split tensors must always be set in their entirety at once
GGML_ASSERT(offset == 0);
GGML_ASSERT(size == ggml_nbytes(tensor));
@ -10586,7 +10585,7 @@ static void ggml_backend_cuda_split_buffer_set_tensor(ggml_backend_buffer_t buff
}
}
static void ggml_backend_cuda_split_buffer_get_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * tensor, void * data, size_t offset, size_t size) {
GGML_CALL static void ggml_backend_cuda_split_buffer_get_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * tensor, void * data, size_t offset, size_t size) {
// split tensors must always be set in their entirety at once
GGML_ASSERT(offset == 0);
GGML_ASSERT(size == ggml_nbytes(tensor));
@ -10620,7 +10619,7 @@ static void ggml_backend_cuda_split_buffer_get_tensor(ggml_backend_buffer_t buff
}
}
static void ggml_backend_cuda_split_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
GGML_CALL static void ggml_backend_cuda_split_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
UNUSED(buffer);
UNUSED(value);
}
@ -10639,13 +10638,13 @@ static struct ggml_backend_buffer_i ggml_backend_cuda_split_buffer_interface = {
// cuda split buffer type
static const char * ggml_backend_cuda_split_buffer_type_name(ggml_backend_buffer_type_t buft) {
GGML_CALL static const char * ggml_backend_cuda_split_buffer_type_name(ggml_backend_buffer_type_t buft) {
return GGML_CUDA_NAME "_Split";
UNUSED(buft);
}
static ggml_backend_buffer_t ggml_backend_cuda_split_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
GGML_CALL static ggml_backend_buffer_t ggml_backend_cuda_split_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
// since we don't know the exact split after rounding, we cannot allocate the device buffers at this point
// instead, we allocate them for each tensor separately in init_tensor
// however, the size still represents the maximum cumulative size of all the device buffers after the tensors are allocated,
@ -10655,13 +10654,13 @@ static ggml_backend_buffer_t ggml_backend_cuda_split_buffer_type_alloc_buffer(gg
return ggml_backend_buffer_init(buft, ggml_backend_cuda_split_buffer_interface, ctx, size);
}
static size_t ggml_backend_cuda_split_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
GGML_CALL static size_t ggml_backend_cuda_split_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
return 128;
UNUSED(buft);
}
static size_t ggml_backend_cuda_split_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) {
GGML_CALL static size_t ggml_backend_cuda_split_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) {
ggml_backend_cuda_split_buffer_type_context * ctx = (ggml_backend_cuda_split_buffer_type_context *)buft->context;
size_t total_size = 0;
@ -10688,13 +10687,13 @@ static size_t ggml_backend_cuda_split_buffer_type_get_alloc_size(ggml_backend_bu
return total_size;
}
static bool ggml_backend_cuda_split_buffer_type_supports_backend(ggml_backend_buffer_type_t buft, ggml_backend_t backend) {
GGML_CALL static bool ggml_backend_cuda_split_buffer_type_supports_backend(ggml_backend_buffer_type_t buft, ggml_backend_t backend) {
return ggml_backend_is_cuda(backend);
UNUSED(buft);
}
static bool ggml_backend_cuda_split_buffer_type_is_host(ggml_backend_buffer_type_t buft) {
GGML_CALL static bool ggml_backend_cuda_split_buffer_type_is_host(ggml_backend_buffer_type_t buft) {
return false;
UNUSED(buft);
@ -10709,7 +10708,7 @@ static ggml_backend_buffer_type_i ggml_backend_cuda_split_buffer_type_interface
/* .is_host = */ ggml_backend_cuda_split_buffer_type_is_host,
};
ggml_backend_buffer_type_t ggml_backend_cuda_split_buffer_type(const float * tensor_split) {
GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_split_buffer_type(const float * tensor_split) {
// FIXME: this is not thread safe
static std::map<std::array<float, GGML_CUDA_MAX_DEVICES>, struct ggml_backend_buffer_type> buft_map;
@ -10745,23 +10744,23 @@ ggml_backend_buffer_type_t ggml_backend_cuda_split_buffer_type(const float * ten
// host buffer type
static const char * ggml_backend_cuda_host_buffer_type_name(ggml_backend_buffer_type_t buft) {
GGML_CALL static const char * ggml_backend_cuda_host_buffer_type_name(ggml_backend_buffer_type_t buft) {
return GGML_CUDA_NAME "_Host";
UNUSED(buft);
}
static const char * ggml_backend_cuda_host_buffer_name(ggml_backend_buffer_t buffer) {
GGML_CALL static const char * ggml_backend_cuda_host_buffer_name(ggml_backend_buffer_t buffer) {
return GGML_CUDA_NAME "_Host";
UNUSED(buffer);
}
static void ggml_backend_cuda_host_buffer_free_buffer(ggml_backend_buffer_t buffer) {
GGML_CALL static void ggml_backend_cuda_host_buffer_free_buffer(ggml_backend_buffer_t buffer) {
ggml_cuda_host_free(buffer->context);
}
static ggml_backend_buffer_t ggml_backend_cuda_host_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
GGML_CALL static ggml_backend_buffer_t ggml_backend_cuda_host_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
void * ptr = ggml_cuda_host_malloc(size);
if (ptr == nullptr) {
@ -10777,7 +10776,7 @@ static ggml_backend_buffer_t ggml_backend_cuda_host_buffer_type_alloc_buffer(ggm
return buffer;
}
ggml_backend_buffer_type_t ggml_backend_cuda_host_buffer_type() {
GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_host_buffer_type() {
static struct ggml_backend_buffer_type ggml_backend_cuda_buffer_type_host = {
/* .iface = */ {
/* .get_name = */ ggml_backend_cuda_host_buffer_type_name,
@ -10795,26 +10794,26 @@ ggml_backend_buffer_type_t ggml_backend_cuda_host_buffer_type() {
// backend
static const char * ggml_backend_cuda_name(ggml_backend_t backend) {
GGML_CALL static const char * ggml_backend_cuda_name(ggml_backend_t backend) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
return cuda_ctx->name.c_str();
}
static void ggml_backend_cuda_free(ggml_backend_t backend) {
GGML_CALL static void ggml_backend_cuda_free(ggml_backend_t backend) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
delete cuda_ctx;
delete backend;
}
static ggml_backend_buffer_type_t ggml_backend_cuda_get_default_buffer_type(ggml_backend_t backend) {
GGML_CALL static ggml_backend_buffer_type_t ggml_backend_cuda_get_default_buffer_type(ggml_backend_t backend) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
return ggml_backend_cuda_buffer_type(cuda_ctx->device);
}
static void ggml_backend_cuda_set_tensor_async(ggml_backend_t backend, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
GGML_CALL static void ggml_backend_cuda_set_tensor_async(ggml_backend_t backend, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
GGML_ASSERT(tensor->buffer->buft == ggml_backend_cuda_buffer_type(cuda_ctx->device) && "unsupported buffer type");
@ -10823,7 +10822,7 @@ static void ggml_backend_cuda_set_tensor_async(ggml_backend_t backend, ggml_tens
CUDA_CHECK(cudaMemcpyAsync((char *)tensor->data + offset, data, size, cudaMemcpyHostToDevice, g_cudaStreams[cuda_ctx->device][0]));
}
static void ggml_backend_cuda_get_tensor_async(ggml_backend_t backend, const ggml_tensor * tensor, void * data, size_t offset, size_t size) {
GGML_CALL static void ggml_backend_cuda_get_tensor_async(ggml_backend_t backend, const ggml_tensor * tensor, void * data, size_t offset, size_t size) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
GGML_ASSERT(tensor->buffer->buft == ggml_backend_cuda_buffer_type(cuda_ctx->device) && "unsupported buffer type");
@ -10832,7 +10831,7 @@ static void ggml_backend_cuda_get_tensor_async(ggml_backend_t backend, const ggm
CUDA_CHECK(cudaMemcpyAsync(data, (const char *)tensor->data + offset, size, cudaMemcpyDeviceToHost, g_cudaStreams[cuda_ctx->device][0]));
}
static bool ggml_backend_cuda_cpy_tensor_async(ggml_backend_t backend, const ggml_tensor * src, ggml_tensor * dst) {
GGML_CALL static bool ggml_backend_cuda_cpy_tensor_async(ggml_backend_t backend, const ggml_tensor * src, ggml_tensor * dst) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
if (dst->buffer->buft == ggml_backend_cuda_buffer_type(cuda_ctx->device) && ggml_backend_buffer_is_cuda(src->buffer)) {
@ -10843,7 +10842,7 @@ static bool ggml_backend_cuda_cpy_tensor_async(ggml_backend_t backend, const ggm
return false;
}
static void ggml_backend_cuda_synchronize(ggml_backend_t backend) {
GGML_CALL static void ggml_backend_cuda_synchronize(ggml_backend_t backend) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
CUDA_CHECK(cudaStreamSynchronize(g_cudaStreams[cuda_ctx->device][0]));
@ -10851,7 +10850,7 @@ static void ggml_backend_cuda_synchronize(ggml_backend_t backend) {
UNUSED(backend);
}
static bool ggml_backend_cuda_graph_compute(ggml_backend_t backend, ggml_cgraph * cgraph) {
GGML_CALL static bool ggml_backend_cuda_graph_compute(ggml_backend_t backend, ggml_cgraph * cgraph) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
ggml_cuda_set_main_device(cuda_ctx->device);
@ -10890,7 +10889,7 @@ static bool ggml_backend_cuda_graph_compute(ggml_backend_t backend, ggml_cgraph
return true;
}
static bool ggml_backend_cuda_supports_op(ggml_backend_t backend, const ggml_tensor * op) {
GGML_CALL static bool ggml_backend_cuda_supports_op(ggml_backend_t backend, const ggml_tensor * op) {
switch (op->op) {
case GGML_OP_UNARY:
switch (ggml_get_unary_op(op)) {
@ -11016,7 +11015,7 @@ static ggml_backend_i ggml_backend_cuda_interface = {
/* .supports_op = */ ggml_backend_cuda_supports_op,
};
ggml_backend_t ggml_backend_cuda_init(int device) {
GGML_CALL ggml_backend_t ggml_backend_cuda_init(int device) {
ggml_init_cublas(); // TODO: remove from ggml.c
if (device < 0 || device >= ggml_cuda_get_device_count()) {
@ -11040,35 +11039,35 @@ ggml_backend_t ggml_backend_cuda_init(int device) {
return cuda_backend;
}
bool ggml_backend_is_cuda(ggml_backend_t backend) {
GGML_CALL bool ggml_backend_is_cuda(ggml_backend_t backend) {
return backend && backend->iface.get_name == ggml_backend_cuda_name;
}
int ggml_backend_cuda_get_device_count() {
GGML_CALL int ggml_backend_cuda_get_device_count() {
return ggml_cuda_get_device_count();
}
void ggml_backend_cuda_get_device_description(int device, char * description, size_t description_size) {
GGML_CALL void ggml_backend_cuda_get_device_description(int device, char * description, size_t description_size) {
ggml_cuda_get_device_description(device, description, description_size);
}
void ggml_backend_cuda_get_device_memory(int device, size_t * free, size_t * total) {
GGML_CALL void ggml_backend_cuda_get_device_memory(int device, size_t * free, size_t * total) {
ggml_cuda_set_device(device);
CUDA_CHECK(cudaMemGetInfo(free, total));
}
// backend registry
static ggml_backend_t ggml_backend_reg_cuda_init(const char * params, void * user_data) {
GGML_CALL static ggml_backend_t ggml_backend_reg_cuda_init(const char * params, void * user_data) {
ggml_backend_t cuda_backend = ggml_backend_cuda_init((int) (intptr_t) user_data);
return cuda_backend;
UNUSED(params);
}
extern "C" int ggml_backend_cuda_reg_devices();
extern "C" GGML_CALL int ggml_backend_cuda_reg_devices();
int ggml_backend_cuda_reg_devices() {
GGML_CALL int ggml_backend_cuda_reg_devices() {
int device_count = ggml_cuda_get_device_count();
//int device_count = 1; // DEBUG: some tools require delaying CUDA initialization
for (int i = 0; i < device_count; i++) {