File size: 8,269 Bytes
d2816aa | 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 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 | #include "bench.h"
#include <algorithm>
#include <chrono>
#include <cmath>
#include <cstdio>
#include <thread>
#include <utility>
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;
}
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