trustformers_debug/profiler/
gpu.rs

1//! GPU profiling and kernel analysis
2// reason: debug/profiling scaffolding — structs are constructed and their fields/methods
3// are retained for the data model, serialization completeness, and future consumers that
4// do not yet read every member. Consolidated from many item-level #[allow(dead_code)].
5#![allow(dead_code)]
6
7use anyhow::Result;
8use serde::{Deserialize, Serialize};
9use std::collections::HashMap;
10use std::time::Duration;
11
12/// Enhanced GPU kernel profiling
13#[derive(Debug, Clone, Serialize, Deserialize)]
14pub struct GpuKernelProfile {
15    pub kernel_name: String,
16    pub grid_size: (u32, u32, u32),
17    pub block_size: (u32, u32, u32),
18    pub shared_memory_bytes: usize,
19    pub registers_per_thread: u32,
20    pub occupancy: f64,
21    pub execution_time: Duration,
22    pub memory_bandwidth_gb_s: f64,
23    pub compute_utilization: f64,
24    pub stream_id: i32,
25}
26
27/// GPU profiler for kernel analysis
28#[derive(Debug)]
29pub struct GpuProfiler {
30    /// Number of GPU devices this profiler has enumerated.
31    ///
32    /// Always `0`: no GPU driver is linked, so nothing can be enumerated.
33    device_count: i32,
34    pub(crate) active_streams: HashMap<i32, Vec<GpuKernelProfile>>,
35    memory_pools: HashMap<i32, GpuMemoryPool>,
36}
37
38#[derive(Debug)]
39pub struct GpuMemoryPool {
40    device_id: i32,
41    total_memory: usize,
42    free_memory: usize,
43    fragmentation_score: f64,
44}
45
46impl GpuProfiler {
47    /// Create a GPU profiler with no enumerated devices.
48    ///
49    /// `device_count` is `0` because this crate links no GPU driver and
50    /// therefore cannot enumerate anything -- it accepts kernel profiles that
51    /// a caller records and aggregates them, but it never discovers hardware
52    /// itself. It used to report `1`, i.e. "one GPU present", on every machine
53    /// including ones with no GPU at all.
54    pub fn new() -> Result<Self> {
55        Ok(Self {
56            device_count: 0,
57            active_streams: HashMap::new(),
58            memory_pools: HashMap::new(),
59        })
60    }
61
62    pub fn profile_kernel(&mut self, kernel_profile: GpuKernelProfile) {
63        self.active_streams
64            .entry(kernel_profile.stream_id)
65            .or_default()
66            .push(kernel_profile);
67    }
68
69    pub fn get_gpu_utilization(&self, device_id: i32) -> f64 {
70        // Simplified GPU utilization calculation
71        if let Some(kernels) = self.active_streams.get(&device_id) {
72            if kernels.is_empty() {
73                0.0
74            } else {
75                kernels.iter().map(|k| k.compute_utilization).sum::<f64>() / kernels.len() as f64
76            }
77        } else {
78            0.0
79        }
80    }
81}
82
83#[derive(Debug, Serialize, Deserialize)]
84pub struct GpuKernelSummary {
85    pub total_kernels: usize,
86    pub total_execution_time: Duration,
87    pub avg_occupancy: f64,
88    pub avg_compute_utilization: f64,
89    pub slowest_kernels: Vec<String>,
90}
91
92#[cfg(test)]
93mod tests {
94    use super::*;
95
96    #[test]
97    fn test_gpu_profiler_new() {
98        let profiler = GpuProfiler::new();
99        assert!(profiler.is_ok());
100    }
101
102    #[test]
103    fn test_gpu_profiler_utilization_empty() {
104        let profiler = GpuProfiler::new().expect("should create profiler");
105        assert!((profiler.get_gpu_utilization(0) - 0.0).abs() < 1e-9);
106    }
107
108    #[test]
109    fn test_gpu_profiler_profile_kernel() {
110        let mut profiler = GpuProfiler::new().expect("should create profiler");
111        let kernel = GpuKernelProfile {
112            kernel_name: "matmul".to_string(),
113            grid_size: (128, 1, 1),
114            block_size: (256, 1, 1),
115            shared_memory_bytes: 4096,
116            registers_per_thread: 32,
117            occupancy: 0.85,
118            execution_time: Duration::from_micros(500),
119            memory_bandwidth_gb_s: 300.0,
120            compute_utilization: 0.9,
121            stream_id: 0,
122        };
123        profiler.profile_kernel(kernel);
124        let util = profiler.get_gpu_utilization(0);
125        assert!((util - 0.9).abs() < 1e-9);
126    }
127
128    #[test]
129    fn test_gpu_profiler_multiple_kernels_avg() {
130        let mut profiler = GpuProfiler::new().expect("should create profiler");
131        for util in [0.8, 0.6] {
132            profiler.profile_kernel(GpuKernelProfile {
133                kernel_name: "kern".to_string(),
134                grid_size: (1, 1, 1),
135                block_size: (1, 1, 1),
136                shared_memory_bytes: 0,
137                registers_per_thread: 0,
138                occupancy: 0.5,
139                execution_time: Duration::from_micros(100),
140                memory_bandwidth_gb_s: 0.0,
141                compute_utilization: util,
142                stream_id: 0,
143            });
144        }
145        let avg = profiler.get_gpu_utilization(0);
146        assert!((avg - 0.7).abs() < 1e-9);
147    }
148}
trustformers_debug/profiler/gpu.rs

trustformers_debug/profiler/
gpu.rs
