hive_gpu/backends/
detector.rs

1//! GPU Backend Detection
2//!
3//! This module provides detection of available GPU backends and selection
4//! of the best backend for the current system.
5
6use crate::error::{Result, HiveGpuError};
7
8/// Available GPU backend types
9#[derive(Debug, Clone, Copy, PartialEq, Eq)]
10pub enum GpuBackendType {
11    /// Metal (Apple Silicon)
12    Metal,
13    /// CUDA (NVIDIA)
14    Cuda,
15    /// CPU fallback
16    Cpu,
17}
18
19impl std::fmt::Display for GpuBackendType {
20    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
21        match self {
22            GpuBackendType::Metal => write!(f, "Metal"),
23            GpuBackendType::Cuda => write!(f, "CUDA"),
24            GpuBackendType::Cpu => write!(f, "CPU"),
25        }
26    }
27}
28
29/// Detect all available GPU backends on the current system
30pub fn detect_available_backends() -> Vec<GpuBackendType> {
31    let mut backends = Vec::new();
32    
33    // Check Metal availability (macOS only)
34    #[cfg(all(target_os = "macos", feature = "metal-native"))]
35    {
36        if is_metal_available() {
37            backends.push(GpuBackendType::Metal);
38        }
39    }
40    
41    // Check CUDA availability
42    #[cfg(feature = "cuda")]
43    {
44        if is_cuda_available() {
45            backends.push(GpuBackendType::Cuda);
46        }
47    }
48    
49    // CPU is always available as fallback
50    backends.push(GpuBackendType::Cpu);
51    
52    backends
53}
54
55/// Select the best available backend based on performance priority
56pub fn select_best_backend() -> Result<GpuBackendType> {
57    let available = detect_available_backends();
58    
59    // Priority order: Metal > CUDA > CPU
60    if available.contains(&GpuBackendType::Metal) {
61        Ok(GpuBackendType::Metal)
62    } else if available.contains(&GpuBackendType::Cuda) {
63        Ok(GpuBackendType::Cuda)
64    } else if available.contains(&GpuBackendType::Cpu) {
65        Ok(GpuBackendType::Cpu)
66    } else {
67        Err(HiveGpuError::NoDeviceAvailable)
68    }
69}
70
71/// Check if Metal is available on the current system
72#[cfg(all(target_os = "macos", feature = "metal-native"))]
73fn is_metal_available() -> bool {
74    use metal::Device;
75    
76    Device::system_default().is_some()
77}
78
79/// Check if CUDA is available on the current system
80#[cfg(feature = "cuda")]
81fn is_cuda_available() -> bool {
82    // This is a simplified check - in practice you'd check for CUDA runtime
83    // and available devices
84    std::env::var("CUDA_VISIBLE_DEVICES").is_ok() || 
85    std::env::var("CUDA_HOME").is_ok()
86}
87
88/// Get backend-specific device information
89pub fn get_backend_info(backend: GpuBackendType) -> Result<String> {
90    match backend {
91        GpuBackendType::Metal => {
92            #[cfg(all(target_os = "macos", feature = "metal-native"))]
93            {
94                use metal::Device;
95                if let Some(device) = Device::system_default() {
96                    Ok(format!("Metal device: {}", device.name()))
97                } else {
98                    Err(HiveGpuError::NoDeviceAvailable)
99                }
100            }
101            #[cfg(not(all(target_os = "macos", feature = "metal-native")))]
102            {
103                Err(HiveGpuError::NoDeviceAvailable)
104            }
105        }
106        GpuBackendType::Cuda => {
107            #[cfg(feature = "cuda")]
108            {
109                // In practice, you'd query CUDA devices here
110                Ok("CUDA device available".to_string())
111            }
112            #[cfg(not(feature = "cuda"))]
113            {
114                Err(HiveGpuError::NoDeviceAvailable)
115            }
116        }
117        GpuBackendType::Cpu => {
118            Ok("CPU fallback".to_string())
119        }
120    }
121}
122
123/// Get performance characteristics for each backend
124pub fn get_backend_performance_info(backend: GpuBackendType) -> BackendPerformanceInfo {
125    match backend {
126        GpuBackendType::Metal => BackendPerformanceInfo {
127            name: "Metal".to_string(),
128            memory_bandwidth_gbps: 400.0, // Apple Silicon typical
129            compute_units: 8, // M1 Pro example
130            memory_size_gb: 16,
131            supports_hnsw: true,
132            supports_batch: true,
133        },
134        GpuBackendType::Cuda => BackendPerformanceInfo {
135            name: "CUDA".to_string(),
136            memory_bandwidth_gbps: 900.0, // RTX 4090 example
137            compute_units: 128, // RTX 4090 example
138            memory_size_gb: 24,
139            supports_hnsw: true,
140            supports_batch: true,
141        },
142        GpuBackendType::Cpu => BackendPerformanceInfo {
143            name: "CPU".to_string(),
144            memory_bandwidth_gbps: 50.0, // DDR4-3200 example
145            compute_units: 16, // 16-core example
146            memory_size_gb: 32,
147            supports_hnsw: false,
148            supports_batch: true,
149        },
150    }
151}
152
153/// Backend performance characteristics
154#[derive(Debug, Clone)]
155pub struct BackendPerformanceInfo {
156    pub name: String,
157    pub memory_bandwidth_gbps: f32,
158    pub compute_units: usize,
159    pub memory_size_gb: usize,
160    pub supports_hnsw: bool,
161    pub supports_batch: bool,
162}
hive_gpu/backends/detector.rs

hive_gpu/backends/
detector.rs
