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8.27 kB
| perf_cell build_perf_cell(ggml_backend_t backend, | |
| const build_graph_fn & build, | |
| const init_tensors_fn & init, | |
| const op_flops_fn & flops) { | |
| perf_cell cell; | |
| const size_t graph_nodes = 1024; | |
| ggml_init_params params = { | |
| /* .mem_size = */ ggml_tensor_overhead() * 128 + ggml_graph_overhead_custom(graph_nodes, false), | |
| /* .mem_base = */ NULL, | |
| /* .no_alloc = */ true, | |
| }; | |
| cell.ctx.reset(ggml_init(params)); | |
| GGML_ASSERT(cell.ctx); | |
| ggml_tensor * out = build(cell.ctx.get()); | |
| if (!out || !ggml_backend_supports_op(backend, out)) { | |
| return cell; | |
| } | |
| cell.buf.reset(ggml_backend_alloc_ctx_tensors(cell.ctx.get(), backend)); | |
| if (!cell.buf) { | |
| return cell; | |
| } | |
| init(cell.ctx.get()); | |
| cell.gf = ggml_new_graph_custom(cell.ctx.get(), graph_nodes, false); | |
| ggml_build_forward_expand(cell.gf, out); | |
| // replicate the op to amortize overhead (target ~50 GFLOP/compute, capped to bound graph size) | |
| cell.n_runs = 1; | |
| const uint64_t n_flops = flops(out); | |
| if (n_flops > 0) { | |
| const uint64_t target_flops = 50ULL * 1000 * 1000 * 1000; | |
| const int cap = 512; | |
| const int by_flops = (int) std::min<int64_t>(cap, (int64_t) (target_flops / n_flops)); | |
| cell.n_runs = | |
| std::max(1, std::min<int>(by_flops, (int) (ggml_graph_size(cell.gf) - ggml_graph_n_nodes(cell.gf)))); | |
| } | |
| for (int i = 1; i < cell.n_runs; ++i) { | |
| ggml_graph_add_node(cell.gf, out); | |
| } | |
| return cell; | |
| } | |
| double time_cell_median(ggml_backend_t backend, const perf_cell & cell, int reps) { | |
| if (cell.gf == nullptr) { | |
| return -1.0; | |
| } | |
| ggml_backend_graph_compute(backend, cell.gf); // warmup (compiles the pipeline for this config) | |
| ggml_backend_synchronize(backend); | |
| std::vector<double> samples; | |
| samples.reserve(reps); | |
| for (int r = 0; r < reps; ++r) { | |
| const int64_t t0 = ggml_time_us(); | |
| ggml_backend_graph_compute(backend, cell.gf); | |
| ggml_backend_synchronize(backend); | |
| samples.push_back((double) (ggml_time_us() - t0)); | |
| } | |
| std::nth_element(samples.begin(), samples.begin() + samples.size() / 2, samples.end()); | |
| return samples[samples.size() / 2] / cell.n_runs; | |
| } | |
| static double measure_one(ggml_backend_t backend, | |
| const perf_cell & cell, | |
| int reps, | |
| const set_candidate_fn & set_cand, | |
| const clear_candidate_fn & clear_cand, | |
| int cand) { | |
| set_cand(cand); | |
| const double t = time_cell_median(backend, cell, reps); | |
| clear_cand(); | |
| return t; | |
| } | |
| // waits for the anchor to come back within eps of anchor_ref, with exponential backoff. | |
| // returns the converged anchor, or -1 if it never converged within max_wait. | |
| static double cool_until_steady(ggml_backend_t backend, | |
| const perf_cell & cell, | |
| int reps, | |
| const set_candidate_fn & set_cand, | |
| const clear_candidate_fn & clear_cand, | |
| int baseline_cand, | |
| double & anchor_ref, | |
| const cooldown_opts & cool, | |
| const char * cell_label) { | |
| int total_wait = 0; | |
| for (int sleep_s = 2; total_wait < cool.max_wait; sleep_s = std::min(sleep_s * 2, 32)) { | |
| const int this_wait = std::min(sleep_s, cool.max_wait - total_wait); | |
| fprintf(stderr, "# COOL sleeping %ds (%ds/%ds) %s\n", this_wait, total_wait + this_wait, cool.max_wait, | |
| cell_label); | |
| std::this_thread::sleep_for(std::chrono::seconds(this_wait)); | |
| total_wait += this_wait; | |
| const double a = measure_one(backend, cell, reps, set_cand, clear_cand, baseline_cand); | |
| if (a <= 0.0) { | |
| continue; | |
| } | |
| // a faster anchor means the machine got cooler than anything seen so far: adopt it | |
| if (a < anchor_ref) { | |
| anchor_ref = a; | |
| } | |
| if (a <= anchor_ref * (1.0 + cool.eps)) { | |
| fprintf(stderr, "# COOL steady after %ds %s\n", total_wait, cell_label); | |
| return a; | |
| } | |
| } | |
| fprintf(stderr, "# COOL gave up after %ds %s\n", total_wait, cell_label); | |
| return -1.0; | |
| } | |
| 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) { | |
| cell_result res; | |
| res.t.assign(order.size(), 0.0); | |
| double anchor_ref = 0.0; | |
| // anchors accepted as clean, as (value, position in order[]). the dirty window starts | |
| // at the position of the last anchor still within eps of anchor_ref, so a downward | |
| // drift (anchor_ref dropping) naturally widens the window to the whole cell. | |
| std::vector<std::pair<double, size_t>> anchors; | |
| auto window_start = [&]() -> size_t { | |
| for (size_t i = anchors.size(); i-- > 0;) { | |
| if (anchors[i].first <= anchor_ref * (1.0 + cool.eps)) { | |
| return anchors[i].second; | |
| } | |
| } | |
| return 0; // no clean anchor left -> the whole cell is suspect | |
| }; | |
| int retries_left = cool.max_retry; | |
| for (size_t i = 0; i < order.size(); ++i) { | |
| res.t[order[i]] = measure_one(backend, cell, reps, set_cand, clear_cand, order[i]); | |
| if (i % 4 != 0) { | |
| continue; | |
| } | |
| const double a = measure_one(backend, cell, reps, set_cand, clear_cand, baseline_cand); | |
| if (a <= 0.0) { | |
| continue; | |
| } | |
| res.anchor_min = res.anchor_min > 0.0 ? std::min(res.anchor_min, a) : a; | |
| res.anchor_max = std::max(res.anchor_max, a); | |
| if (anchor_ref == 0.0) { | |
| anchor_ref = a; | |
| anchors.push_back({ a, i }); | |
| continue; | |
| } | |
| const double drift = std::fabs(a - anchor_ref) / anchor_ref; | |
| // a cooler anchor than any so far becomes the reference: whatever was measured | |
| // before it was measured on a hotter machine | |
| if (a < anchor_ref) { | |
| anchor_ref = a; | |
| } | |
| if (drift <= cool.drift) { | |
| anchors.push_back({ a, i }); | |
| continue; | |
| } | |
| fprintf(stderr, "# WARN throttling? anchor drift %.1f%% %s\n", 100.0 * drift, cell_label); | |
| if (!cool.enabled) { | |
| anchors.push_back({ a, i }); | |
| continue; | |
| } | |
| if (retries_left <= 0) { | |
| fprintf(stderr, "# DIRTY retries exhausted %s\n", cell_label); | |
| res.trusted = false; | |
| return res; | |
| } | |
| const size_t dirty_from = window_start(); | |
| const double a_cool = | |
| cool_until_steady(backend, cell, reps, set_cand, clear_cand, baseline_cand, anchor_ref, cool, cell_label); | |
| if (a_cool <= 0.0) { | |
| res.trusted = false; | |
| return res; | |
| } | |
| // the converged anchor is the only clean one now; re-measure the dirty window from it | |
| anchors.clear(); | |
| anchors.push_back({ a_cool, dirty_from }); | |
| retries_left--; | |
| fprintf(stderr, "# REDO candidates %zu..%zu %s\n", dirty_from, i, cell_label); | |
| for (size_t j = dirty_from; j <= i; ++j) { | |
| res.t[order[j]] = measure_one(backend, cell, reps, set_cand, clear_cand, order[j]); | |
| } | |
| } | |
| return res; | |
| } | |