root/llama.cpp
1
0
Fork 0
mirror of https://github.com/ggerganov/llama.cpp.git synced 2025-01-12 03:31:46 +00:00
Code Issues Actions 5 Packages Projects Releases Wiki Activity

[GGML][RPC] Support for models with non-512-aligned tensors over RPC. (#11047)

Browse Source 
* Added init tensor calling code

* Added get_alloc_size forwarding

* Cleaned up and improved type/error handling.

* fix: remove trailing whitespaces.

* Cleanup and use GGML error logging functions.

* Handle potentially dangerous edge cases.

* Apply suggestions from code review

Co-authored-by: Diego Devesa <slarengh@gmail.com>

---------

Co-authored-by: Diego Devesa <slarengh@gmail.com>
This commit is contained in:
matt23654 2025-01-04 16:10:30 +00:00 committed by GitHub
parent 46be942214
commit f922a9c542
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 134 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

138
ggml/src/ggml-rpc/ggml-rpc.cpp
View File

@ -93,9 +93,23 @@ enum rpc_cmd {
RPC_CMD_COPY_TENSOR,
RPC_CMD_GRAPH_COMPUTE,
RPC_CMD_GET_DEVICE_MEMORY,
RPC_CMD_INIT_TENSOR,
RPC_CMD_GET_ALLOC_SIZE,
RPC_CMD_COUNT,
};
struct rpc_msg_get_alloc_size_req {
rpc_tensor tensor;
};
struct rpc_msg_get_alloc_size_rsp {
uint64_t alloc_size;
};
struct rpc_msg_init_tensor_req {
rpc_tensor tensor;
};
struct rpc_msg_alloc_buffer_req {
uint64_t size;
};
@ -461,10 +475,18 @@ static rpc_tensor serialize_tensor(const ggml_tensor * tensor) {
}
static void ggml_backend_rpc_buffer_init_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor) {
UNUSED(buffer);
if (ggml_is_quantized(tensor->type)) {
// TODO: this check is due to MATRIX_ROW_PADDING in CUDA and should be generalized
GGML_ASSERT(tensor->ne[0] % 512 == 0 && "unsupported quantized tensor");
ggml_backend_rpc_buffer_context * ctx = (ggml_backend_rpc_buffer_context *)buffer->context;
// CUDA backend on the server pads everything to 512 due to CUDA limitations.
// Due to bandwidth constraints, we only call the server init tensor functions if necessary.
// In particular, only quantized tensors need padding
if (ggml_is_quantized(tensor->type) && (tensor->ne[0] % 512 != 0) && (tensor->view_src == nullptr)) {
rpc_msg_init_tensor_req request;
request.tensor = serialize_tensor(tensor);
bool status = send_rpc_cmd(ctx->sock, RPC_CMD_INIT_TENSOR, &request, sizeof(request), nullptr, 0);
GGML_ASSERT(status);
}
}
@ -577,9 +599,24 @@ static size_t ggml_backend_rpc_get_max_size(ggml_backend_buffer_type_t buft) {
}
static size_t ggml_backend_rpc_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) {
UNUSED(buft);
// See comments in init_tensor.
if (ggml_is_quantized(tensor->type) && (tensor->ne[0] % 512 != 0) && (tensor->view_src == nullptr)) {
ggml_backend_rpc_buffer_type_context * buft_ctx = (ggml_backend_rpc_buffer_type_context *)buft->context;
auto sock = get_socket(buft_ctx->endpoint);
rpc_msg_get_alloc_size_req request;
request.tensor = serialize_tensor(tensor);
rpc_msg_get_alloc_size_rsp response;
bool status = send_rpc_cmd(sock, RPC_CMD_GET_ALLOC_SIZE, &request, sizeof(request), &response, sizeof(response));
GGML_ASSERT(status);
return response.alloc_size;
} else {
return ggml_nbytes(tensor);
}
}
static ggml_backend_buffer_type_i ggml_backend_rpc_buffer_type_interface = {
/* .get_name = */ ggml_backend_rpc_buffer_type_name,
@ -757,6 +794,8 @@ public:
bool get_tensor(const rpc_msg_get_tensor_req & request, std::vector<uint8_t> & response);
bool copy_tensor(const rpc_msg_copy_tensor_req & request, rpc_msg_copy_tensor_rsp & response);
bool graph_compute(const std::vector<uint8_t> & input, rpc_msg_graph_compute_rsp & response);
bool init_tensor(const rpc_msg_init_tensor_req & request);
bool get_alloc_size(const rpc_msg_get_alloc_size_req & request, rpc_msg_get_alloc_size_rsp & response);
private:
ggml_tensor * deserialize_tensor(struct ggml_context * ctx, const rpc_tensor * tensor);
@ -770,6 +809,36 @@ private:
std::unordered_set<ggml_backend_buffer_t> buffers;
};
bool rpc_server::get_alloc_size(const rpc_msg_get_alloc_size_req & request, rpc_msg_get_alloc_size_rsp & response) {
ggml_backend_buffer_type_t buft;
struct ggml_init_params params {
/*.mem_size =*/ ggml_tensor_overhead(),
/*.mem_buffer =*/ NULL,
/*.no_alloc =*/ true,
};
struct ggml_context * ctx = ggml_init(params);
ggml_tensor * tensor = deserialize_tensor(ctx, &request.tensor);
if (tensor == nullptr) {
GGML_LOG_ERROR("Null tensor pointer passed to server get_alloc_size function.\n");
ggml_free(ctx);
return false;
}
if (tensor->buffer == nullptr) {
//No buffer allocated.
buft = ggml_backend_get_default_buffer_type(backend);
} else {
buft = tensor->buffer->buft;
}
response.alloc_size = ggml_backend_buft_get_alloc_size(buft,tensor);
ggml_free(ctx);
return true;
}
void rpc_server::alloc_buffer(const rpc_msg_alloc_buffer_req & request, rpc_msg_alloc_buffer_rsp & response) {
ggml_backend_buffer_type_t buft = ggml_backend_get_default_buffer_type(backend);
ggml_backend_buffer_t buffer = ggml_backend_buft_alloc_buffer(buft, request.size);
@ -905,6 +974,40 @@ bool rpc_server::set_tensor(const std::vector<uint8_t> & input) {
return true;
}
bool rpc_server::init_tensor(const rpc_msg_init_tensor_req & request) {
struct ggml_init_params params {
/*.mem_size =*/ ggml_tensor_overhead(),
/*.mem_buffer =*/ NULL,
/*.no_alloc =*/ true,
};
struct ggml_context * ctx = ggml_init(params);
ggml_tensor * tensor = deserialize_tensor(ctx, &request.tensor);
if (tensor == nullptr) {
GGML_LOG_ERROR("Null tensor pointer passed to server init_tensor function.\n");
ggml_free(ctx);
return false;
}
// Call the backend's buffer_init_tensor function
ggml_backend_buffer_t buffer = tensor->buffer;
if (buffer && buffer->iface.init_tensor) {
buffer->iface.init_tensor(buffer, tensor);
} else {
GGML_LOG_ERROR("Null buffer for tensor passed to init_tensor function\n");
}
if (tensor->extra != nullptr) {
// This pointer can either be passed around client/server, or probably better stored server-side and kept track of.
// Currently unimplemented.
GGML_LOG_ERROR("tensor->extra populated by the backend, this is currently unsupported.\n");
ggml_free(ctx);
return false;
}
ggml_free(ctx);
return true;
}
bool rpc_server::get_tensor(const rpc_msg_get_tensor_req & request, std::vector<uint8_t> & response) {
struct ggml_init_params params {
/*.mem_size =*/ ggml_tensor_overhead(),
@ -1058,6 +1161,18 @@ static void rpc_serve_client(ggml_backend_t backend, sockfd_t sockfd, size_t fre
}
break;
}
case RPC_CMD_GET_ALLOC_SIZE: {
rpc_msg_get_alloc_size_req request;
if (!recv_msg(sockfd, &request, sizeof(request))) {
return;
}
rpc_msg_get_alloc_size_rsp response;
server.get_alloc_size(request, response);
if (!send_msg(sockfd, &response, sizeof(response))) {
return;
}
break;
}
case RPC_CMD_GET_ALIGNMENT: {
if (!recv_msg(sockfd, nullptr, 0)) {
return;
@ -1133,6 +1248,19 @@ static void rpc_serve_client(ggml_backend_t backend, sockfd_t sockfd, size_t fre
}
break;
}
case RPC_CMD_INIT_TENSOR: {
rpc_msg_init_tensor_req request;
if (!recv_msg(sockfd, &request,sizeof(request))) {
return;
}
if (!server.init_tensor(request)) {
return;
}
if (!send_msg(sockfd, nullptr, 0)) {
return;
}
break;
}
case RPC_CMD_GET_TENSOR: {
rpc_msg_get_tensor_req request;
if (!recv_msg(sockfd, &request, sizeof(request))) {