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Merged
resserops merged 1 commit into from
Jun 29, 2026
Merged

feat(profiling/tool): add system-wide cpu usage measurement #78

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4 changes: 2 additions & 2 deletions module/common/include/oops/str.h
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Original file line number Diff line number Diff line change
Expand Up @@ -63,14 +63,14 @@ class SplitView {
}

bool operator==(const Iterator &other) const {
// 短路和迭代器的比较
// 尾迭代器参与的快速比较
if ((token_.data() == nullptr) ^ (other.token_.data() == nullptr)) {
return false; // 一个迭代器是尾迭代器，另一个不是
}
if (token_.data() == nullptr) {
return true; // 均是尾迭代器
}
// 非尾迭代器的严格匹配
// 两个正常迭代器的严格比较
return (token_.data() == other.token_.data()) && (token_.size() == other.token_.size()) &&
(s_.data() == other.s_.data()) && (s_.size() == other.s_.size()) && (delim_ == other.delim_) &&
(any_of_delims_ == other.any_of_delims_) && (skip_empty_ == other.skip_empty_);
Expand Down
41 changes: 35 additions & 6 deletions module/profiling/include/oops/cpu_timer.h
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Original file line number Diff line number Diff line change
Expand Up @@ -17,8 +17,8 @@ inline auto GetTicksPerSec() {
class CpuTimer {
struct CpuTicks {
std::uintmax_t TotalTicks() const { return user_ticks + kernel_ticks; };
std::uintmax_t user_ticks;
std::uintmax_t kernel_ticks;
std::uintmax_t user_ticks{};
std::uintmax_t kernel_ticks{};
};

using CpuTimePoint = std::variant<struct timespec, CpuTicks, std::monostate>;
Expand All @@ -34,10 +34,17 @@ class CpuTimer {
double elapsed_time{};
};

static constexpr pid_t SYSTEM{-1};
static std::string GetPath(pid_t pid) {
if (pid == SYSTEM) {
return "/proc/stat";
}
return "/proc/" + std::to_string(pid) + "/stat";
}

CpuTimer() : cpu_t0_{GetCpuTimePoint()}, elapsed_t0_{std::chrono::steady_clock::now()} {}
CpuTimer(pid_t pid)
: stat_path_{"/proc/" + std::to_string(pid) + "/stat"}, cpu_t0_{GetCpuTimePoint()},
elapsed_t0_{std::chrono::steady_clock::now()} {}
: stat_path_{GetPath(pid)}, cpu_t0_{GetCpuTimePoint()}, elapsed_t0_{std::chrono::steady_clock::now()} {}

void Reset() {
cpu_t0_ = GetCpuTimePoint();
Expand Down Expand Up @@ -76,20 +83,42 @@ class CpuTimer {
return spec;
}

// 文件快照(/proc/pid/stat)获取cpu时间，Ticks级精度(约10ms)
// 文件快照(/proc/*/stat)获取进程或system cpu时间，Ticks级精度(约10ms)
// 解析效率要求高，使用栈缓冲
char buf[512];
std::FILE *f{std::fopen(stat_path_.c_str(), "r")};
if (!f) {
return std::monostate{}; // 无法打开文件，返回空类型
}

auto res{std::fgets(buf, sizeof(buf), f)};
std::fclose(f);
if (res == nullptr) {
return std::monostate{}; // 读取失败，返回空类型
}

if (stat_path_.size() == 10) {
// 文件快照(/proc/stat)获取系统级cpu时间
char *p{buf};
while ((*p < '0') || (*p > '9')) {
++p;
}
CpuTicks cpu_ticks;
cpu_ticks.user_ticks += std::strtoull(p, &p, 10); // 匹配第1个字段user
cpu_ticks.user_ticks += std::strtoull(p + 1, &p, 10); // 匹配第2个字段nice

cpu_ticks.kernel_ticks += std::strtoull(p + 1, &p, 10); // 匹配第3个字段system

// 跳过第4个字段idle和第5个字段iowait
int rem{2};
while (rem-- > 0) {
p = std::strchr(p + 1, ' ');
assert(p != nullptr);
}

cpu_ticks.kernel_ticks += std::strtoull(p + 1, &p, 10); // 匹配第6个字段irq
cpu_ticks.kernel_ticks += std::strtoull(p + 1, &p, 10); // 匹配第7个字段softirq
return cpu_ticks;
}
// 查找第2个字段的右括号
char *p{std::strrchr(buf, ')')};
assert(p != nullptr);
Expand Down
64 changes: 31 additions & 33 deletions module/profiling/tool/monitor/monitor.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -167,7 +167,7 @@ void Measure() {
std::cout << MakeHeaderRow() << std::endl;

std::vector<double> values(oops::ToUnderlying(Metrics::COUNT));
while (!STOP.load(std::memory_order_relaxed) && ProcExist(ARGS.measure.pid)) {
while (!STOP.load(std::memory_order_relaxed) && (ProcExist(ARGS.measure.pid) || ARGS.measure.pid == -1)) {
std::this_thread::sleep_until(next_time);

// 根据选项配置完成测量
Expand Down Expand Up @@ -433,9 +433,6 @@ void AlignTimeline() {
double range_l_fidx{std::ceil(std::chrono::duration<double>{range_l - raw_l}.count()) / r_entry.interval};
double range_r_fidx{std::ceil(std::chrono::duration<double>{range_r - raw_l}.count()) / r_entry.interval};

std::cout << "lidx: " << range_l_fidx << std::endl;
std::cout << "ridx: " << range_r_fidx << std::endl;

// 计算range对应的下标，左闭右开
std::size_t range_l_idx{std::max<std::ptrdiff_t>(range_l_fidx, 0)};
std::size_t range_r_idx{std::min<std::ptrdiff_t>(range_r_fidx, size)};
Expand Down Expand Up @@ -469,78 +466,77 @@ void AlignTimeline() {
}
}

void PlotCpu() {
if (RAW_DATA_TABLE.empty()) {
return;
}
auto GetMetricEntries(Metrics m) {
struct Entries {
RawDataEntry &r_entry;
MetricDataEntry &m_entry;
};

// 识别记录了CPU利用率的raw data idx及对应CPU利用率的metric data dix
std::vector<std::pair<std::size_t, std::size_t>> valid_idxs;
for (std::size_t i{0}; i < RAW_DATA_TABLE.size(); ++i) {
const auto &r_entry{RAW_DATA_TABLE[i]};
for (std::size_t j{0}; j < r_entry.metric_data_table.size(); ++j) {
const auto &m_entry{r_entry.metric_data_table.at(j)};
if (m_entry.name == METRIC_TABLE[oops::ToUnderlying(Metrics::CPU_USAGE)].name && !m_entry.values.empty()) {
valid_idxs.emplace_back(i, j);
std::vector<Entries> res;
for (auto &r_entry : RAW_DATA_TABLE) {
for (auto &m_entry : r_entry.metric_data_table) {
if (m_entry.name == METRIC_TABLE[oops::ToUnderlying(m)].name && !m_entry.values.empty()) {
res.push_back({r_entry, m_entry});
}
}
}
if (valid_idxs.empty()) {
return res;
}

void PlotCpu() {
assert(!RAW_DATA_TABLE.empty());

auto entries{GetMetricEntries(Metrics::CPU_USAGE)};
if (entries.empty()) {
return;
}

// 根据downsample_rate，合并数据点，cpu利用率采取平均值
for (const auto &[r_idx, m_idx] : valid_idxs) {
auto &r_entry{RAW_DATA_TABLE[r_idx]};
for (const auto &[r_entry, m_entry] : entries) {
if (r_entry.downsample_rate <= 1) {
// 不需要合并
continue;
}

std::cout << r_entry.downsample_rate << std::endl;

// 计算合并后的新数据点数
auto &m_entry{r_entry.metric_data_table[m_idx]};
std::size_t new_i{0};
for (std::size_t i{0}; i + r_entry.downsample_rate - 1 < m_entry.values.size(); i += r_entry.downsample_rate) {
double sum{};
for (std::size_t j{i}; j < i + r_entry.downsample_rate; j++) {
sum += m_entry.values[j];
}
m_entry.values[new_i++] = sum / r_entry.downsample_rate;
std::cout << "avg: " << sum / r_entry.downsample_rate << std::endl;
}
m_entry.values.resize(new_i);
r_entry.interval *= r_entry.downsample_rate;
}

// 最大数值
double max_value{std::numeric_limits<double>::min()};
for (const auto &[r_idx, m_idx] : valid_idxs) {
for (double value : RAW_DATA_TABLE[r_idx].metric_data_table[m_idx].values) {
for (const auto &e : entries) {
for (double value : e.m_entry.values) {
max_value = std::max(max_value, value);
}
}
std::cout << "max_value: " << max_value << std::endl;

py::scoped_interpreter guard{}; // 必须放在try-catch块外侧，否则无法捕获py::error_already_set异常
try {
auto plt{py::module_::import("matplotlib.pyplot")};
auto subplots{plt.attr("subplots")(
valid_idxs.size(), 1, py::arg("sharex") = true,
entries.size(), 1, py::arg("sharex") = true,
py::arg("figsize") = py::make_tuple(
16, std::max<std::size_t>(std::min<std::size_t>(9, 3 * valid_idxs.size()), valid_idxs.size())))};
16, std::max<std::size_t>(std::min<std::size_t>(9, 3 * entries.size()), entries.size())))};

py::list axes; // 存储所有子图，使用vector反而会有拷贝和引用计数开销
if (valid_idxs.size() == 1) {
if (entries.size() == 1) {
axes.append(subplots[py::int_(1)]);
} else {
axes = subplots[py::int_(1)].cast<py::list>();
}

for (std::size_t i{0}; i < valid_idxs.size(); ++i) {
const auto &r_entry{RAW_DATA_TABLE[valid_idxs[i].first]};
const auto &m_entry{r_entry.metric_data_table[valid_idxs[i].second]};
for (std::size_t i{0}; i < entries.size(); ++i) {
const auto &r_entry{entries[i].r_entry};
const auto &m_entry{entries[i].m_entry};
double offset{std::chrono::duration<double>{r_entry.start_time - TOTAL_START_TIME}.count()};

// 构造时间数组，由于offset差异，每个raw data需要单独构造
Expand All @@ -557,7 +553,6 @@ void PlotCpu() {
ax.attr("margins")(py::arg("x") = 0);
ax.attr("grid")(true, py::arg("linestyle") = "--", py::arg("alpha") = 0.5);
double ylim{std::max(100., max_value)};
std::cout << "ylim " << ylim << std::endl;
ax.attr("set_ylim")(-ylim / 20, ylim + ylim / 20); // 对齐每个子图y坐标范围
// 绘制每个子图左侧描述raw data的标签
ax.attr("set_ylabel")(
Expand Down Expand Up @@ -592,6 +587,9 @@ void Report() {

// 对齐时间轴，range裁剪，分辨率缩放
AlignTimeline();
if (RAW_DATA_TABLE.empty()) {
return;
}

// 绘制CPU利用率折线图
PlotCpu();
Expand Down
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