Initial commit

2026-03-04 00:08:42 +00:00
commit 4d88dc0584
4449 changed files with 1556714 additions and 0 deletions
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+//! Distributed training benchmarks
+
+use crate::{
+    BenchmarkConfig, BenchmarkMeasurement, BenchmarkResults, BenchmarkStatistics,
+    time_benchmark_async,
+};
+use anyhow::Result;
+use std::collections::HashMap;
+use tracing::info;
+
+pub struct DistributedTrainingBenchmarks;
+
+impl DistributedTrainingBenchmarks {
+    pub fn new() -> Self {
+        Self
+    }
+
+    pub async fn run_all(&self, config: &BenchmarkConfig) -> Result<BenchmarkResults> {
+        info!("Starting distributed training benchmarks");
+
+        let mut results = BenchmarkResults::new("DistributedTraining".to_string(), config.clone());
+        let mut all_measurements: HashMap<String, Vec<BenchmarkMeasurement>> = HashMap::new();
+
+        // Multi-GPU scaling benchmarks
+        all_measurements.insert(
+            "multi_gpu_scaling".to_string(),
+            self.benchmark_multi_gpu_scaling(config).await?,
+        );
+
+        // Gradient synchronization
+        all_measurements.insert(
+            "gradient_sync".to_string(),
+            self.benchmark_gradient_sync(config).await?,
+        );
+
+        // Calculate statistics
+        for (name, measurements) in all_measurements {
+            match BenchmarkStatistics::from_measurements(&measurements) {
+                Ok(stats) => results.add_benchmark(name, stats),
+                Err(e) => results.add_warning(format!("Failed to calculate stats: {e}")),
+            }
+        }
+
+        results.mark_complete();
+        Ok(results)
+    }
+
+    async fn benchmark_multi_gpu_scaling(
+        &self,
+        config: &BenchmarkConfig,
+    ) -> Result<Vec<BenchmarkMeasurement>> {
+        let mut measurements = Vec::with_capacity(config.measurement_iterations);
+
+        for _ in 0..config.measurement_iterations {
+            let measurement = time_benchmark_async("multi_gpu_scaling".to_string(), || async {
+                self.multi_gpu_training_step().await?;
+                Ok(())
+            })
+            .await?;
+            measurements.push(measurement);
+        }
+
+        Ok(measurements)
+    }
+
+    async fn benchmark_gradient_sync(
+        &self,
+        config: &BenchmarkConfig,
+    ) -> Result<Vec<BenchmarkMeasurement>> {
+        let mut measurements = Vec::with_capacity(config.measurement_iterations);
+
+        for _ in 0..config.measurement_iterations {
+            let measurement = time_benchmark_async("gradient_sync".to_string(), || async {
+                self.gradient_synchronization().await?;
+                Ok(())
+            })
+            .await?;
+            measurements.push(measurement);
+        }
+
+        Ok(measurements)
+    }
+
+    async fn multi_gpu_training_step(&self) -> Result<()> {
+        tokio::time::sleep(std::time::Duration::from_millis(200)).await;
+        Ok(())
+    }
+
+    async fn gradient_synchronization(&self) -> Result<()> {
+        tokio::time::sleep(std::time::Duration::from_millis(50)).await;
+        Ok(())
+    }
+}
+
+impl Default for DistributedTrainingBenchmarks {
+    fn default() -> Self {
+        Self::new()
+    }
+}