// - Creates n_parallel (--parallel) contexts per model
// - Runs inference in parallel on each context
+#include <array>
#include <thread>
#include <vector>
#include <atomic>
cparams.n_seq_max = 1;
int dev_count = ggml_backend_dev_count();
- int gpu_dev_count = 0;
+ std::vector<std::array<ggml_backend_dev_t, 2>> gpus;
for (int i = 0; i < dev_count; ++i) {
auto * dev = ggml_backend_dev_get(i);
if (dev && ggml_backend_dev_type(dev) == GGML_BACKEND_DEVICE_TYPE_GPU) {
- gpu_dev_count++;
+ gpus.push_back({dev, nullptr});
}
}
+ const int gpu_dev_count = (int)gpus.size();
const int num_models = gpu_dev_count + 1 + 1; // GPUs + 1 CPU model + 1 layer split
//const int num_models = std::max(1, gpu_dev_count);
const int num_contexts = std::max(1, params.n_parallel);
if (m < gpu_dev_count) {
mparams.split_mode = LLAMA_SPLIT_MODE_NONE;
- mparams.main_gpu = m;
+ mparams.devices = gpus[m].data();
} else if (m == gpu_dev_count) {
mparams.split_mode = LLAMA_SPLIT_MODE_NONE;
mparams.main_gpu = -1; // CPU model
} else {
- mparams.split_mode = LLAMA_SPLIT_MODE_LAYER;;
+ mparams.split_mode = LLAMA_SPLIT_MODE_LAYER;
}
llama_model * model = llama_model_load_from_file(params.model.path.c_str(), mparams);