Enhance performance profiling and tile caching mechanisms

- Introduced a new PerformanceProfiler class for detailed timing and performance measurement across graphics operations.
- Implemented a smart tile cache with LRU eviction in the TileCache structure to optimize memory usage and improve tile rendering efficiency.
- Updated various graphics components to utilize the new caching system, reducing redundant texture updates and enhancing overall performance.
- Added dirty region tracking in Bitmap for efficient texture updates, minimizing the area that needs to be refreshed during rendering.
- Enhanced existing methods to leverage performance monitoring, providing insights into operation durations and potential bottlenecks.
This commit is contained in:
scawful
2025-09-28 23:13:12 -04:00
parent 5915391467
commit ce31906c93
15 changed files with 840 additions and 112 deletions

View File

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#include "app/gfx/performance_profiler.h"
#include <algorithm>
#include <iomanip>
#include <numeric>
#include <sstream>
namespace yaze {
namespace gfx {
PerformanceProfiler& PerformanceProfiler::Get() {
static PerformanceProfiler instance;
return instance;
}
void PerformanceProfiler::StartTimer(const std::string& operation_name) {
active_timers_[operation_name] = std::chrono::high_resolution_clock::now();
}
void PerformanceProfiler::EndTimer(const std::string& operation_name) {
auto it = active_timers_.find(operation_name);
if (it == active_timers_.end()) {
SDL_Log("Warning: EndTimer called for operation '%s' that was not started",
operation_name.c_str());
return;
}
auto end_time = std::chrono::high_resolution_clock::now();
auto duration = std::chrono::duration_cast<std::chrono::microseconds>(
end_time - it->second).count();
operation_times_[operation_name].push_back(static_cast<double>(duration));
active_timers_.erase(it);
}
PerformanceProfiler::TimingStats PerformanceProfiler::GetStats(
const std::string& operation_name) const {
TimingStats stats;
auto it = operation_times_.find(operation_name);
if (it == operation_times_.end() || it->second.empty()) {
return stats;
}
const auto& times = it->second;
stats.sample_count = times.size();
if (times.empty()) {
return stats;
}
// Calculate min, max, and average
stats.min_time_us = *std::min_element(times.begin(), times.end());
stats.max_time_us = *std::max_element(times.begin(), times.end());
stats.avg_time_us = std::accumulate(times.begin(), times.end(), 0.0) / times.size();
// Calculate median
std::vector<double> sorted_times = times;
std::sort(sorted_times.begin(), sorted_times.end());
stats.median_time_us = CalculateMedian(sorted_times);
return stats;
}
std::string PerformanceProfiler::GenerateReport(bool log_to_sdl) const {
std::ostringstream report;
report << "\n=== YAZE Graphics Performance Report ===\n";
report << "Total Operations Tracked: " << operation_times_.size() << "\n\n";
for (const auto& [operation, times] : operation_times_) {
if (times.empty()) continue;
auto stats = GetStats(operation);
report << "Operation: " << operation << "\n";
report << " Samples: " << stats.sample_count << "\n";
report << " Min: " << std::fixed << std::setprecision(2) << stats.min_time_us << " μs\n";
report << " Max: " << std::fixed << std::setprecision(2) << stats.max_time_us << " μs\n";
report << " Average: " << std::fixed << std::setprecision(2) << stats.avg_time_us << " μs\n";
report << " Median: " << std::fixed << std::setprecision(2) << stats.median_time_us << " μs\n";
// Performance analysis
if (operation.find("palette_lookup") != std::string::npos) {
if (stats.avg_time_us < 1.0) {
report << " Status: ✓ OPTIMIZED (O(1) hash map lookup)\n";
} else {
report << " Status: ⚠ NEEDS OPTIMIZATION (O(n) linear search)\n";
}
} else if (operation.find("texture_update") != std::string::npos) {
if (stats.avg_time_us < 100.0) {
report << " Status: ✓ OPTIMIZED (dirty region tracking)\n";
} else {
report << " Status: ⚠ NEEDS OPTIMIZATION (full texture updates)\n";
}
} else if (operation.find("tile_cache") != std::string::npos) {
if (stats.avg_time_us < 10.0) {
report << " Status: ✓ OPTIMIZED (LRU cache hit)\n";
} else {
report << " Status: ⚠ CACHE MISS (tile recreation needed)\n";
}
}
report << "\n";
}
// Overall performance summary
report << "=== Performance Summary ===\n";
size_t total_samples = 0;
double total_time = 0.0;
for (const auto& [operation, times] : operation_times_) {
total_samples += times.size();
total_time += std::accumulate(times.begin(), times.end(), 0.0);
}
if (total_samples > 0) {
report << "Total Samples: " << total_samples << "\n";
report << "Total Time: " << std::fixed << std::setprecision(2)
<< total_time / 1000.0 << " ms\n";
report << "Average Time per Operation: " << std::fixed << std::setprecision(2)
<< total_time / total_samples << " μs\n";
}
std::string report_str = report.str();
if (log_to_sdl) {
SDL_Log("%s", report_str.c_str());
}
return report_str;
}
void PerformanceProfiler::Clear() {
active_timers_.clear();
operation_times_.clear();
}
void PerformanceProfiler::ClearOperation(const std::string& operation_name) {
active_timers_.erase(operation_name);
operation_times_.erase(operation_name);
}
std::vector<std::string> PerformanceProfiler::GetOperationNames() const {
std::vector<std::string> names;
for (const auto& [name, times] : operation_times_) {
names.push_back(name);
}
return names;
}
bool PerformanceProfiler::IsTiming(const std::string& operation_name) const {
return active_timers_.find(operation_name) != active_timers_.end();
}
double PerformanceProfiler::CalculateMedian(std::vector<double> values) const {
if (values.empty()) return 0.0;
size_t size = values.size();
if (size % 2 == 0) {
return (values[size / 2 - 1] + values[size / 2]) / 2.0;
} else {
return values[size / 2];
}
}
// ScopedTimer implementation
ScopedTimer::ScopedTimer(const std::string& operation_name)
: operation_name_(operation_name) {
PerformanceProfiler::Get().StartTimer(operation_name_);
}
ScopedTimer::~ScopedTimer() {
PerformanceProfiler::Get().EndTimer(operation_name_);
}
} // namespace gfx
} // namespace yaze