File size: 2,183 Bytes
c59fd93 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 | #pragma once
#include "ggml-backend.h"
#include "ggml-cpp.h"
#include "ggml.h"
#include <cstdint>
#include <functional>
#include <vector>
// A prebuilt graph replicated to amortize dispatch and synchronization overhead.
struct perf_cell {
ggml_context_ptr ctx;
ggml_backend_buffer_ptr buf;
ggml_cgraph * gf = nullptr;
int n_runs = 0;
};
using build_graph_fn = std::function<ggml_tensor *(ggml_context *)>;
using init_tensors_fn = std::function<void(ggml_context *)>;
using op_flops_fn = std::function<uint64_t(ggml_tensor *)>;
perf_cell build_perf_cell(ggml_backend_t backend,
const build_graph_fn & build,
const init_tensors_fn & init,
const op_flops_fn & flops);
double time_cell_median(ggml_backend_t backend, const perf_cell & cell, int reps);
struct cooldown_opts {
bool enabled = true;
double drift = 0.10; // anchor drift that triggers a cooldown
double eps = 0.03; // anchor tolerance to call the GPU cool again
int max_wait = 120; // seconds of cooling per cell before giving up
int max_retry = 2; // re-measure rounds per cell before giving up
};
using set_candidate_fn = std::function<void(int)>;
using clear_candidate_fn = std::function<void()>;
struct cell_result {
std::vector<double> t;
bool trusted = true;
double anchor_min = 0.0;
double anchor_max = 0.0;
};
// Times candidates in order while using baseline_cand as a thermal-drift anchor.
cell_result measure_cell(ggml_backend_t backend,
const perf_cell & cell,
int reps,
const std::vector<int> & order,
const set_candidate_fn & set_cand,
const clear_candidate_fn & clear_cand,
int baseline_cand,
const cooldown_opts & cool,
const char * cell_label);
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