trueno 0.17.2

High-performance SIMD compute library with GPU support for matrix operations
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339

use super::*;

#[test]
fn test_simd_detection() {
    let simd = detect_simd();
    // Should detect at least scalar
    assert!(simd.lanes() >= 1);
}

#[test]
fn test_simd_lanes() {
    assert_eq!(SimdWidth::Scalar.lanes(), 1);
    assert_eq!(SimdWidth::Avx2.lanes(), 8);
    assert_eq!(SimdWidth::Avx512.lanes(), 16);
}

#[test]
fn test_hardware_detection() {
    let cap = HardwareCapability::detect();
    assert!(cap.cpu.cores > 0);
    assert!(cap.cpu.peak_gflops > 0.0);
}

#[test]
fn test_bottleneck_classification() {
    let cap = HardwareCapability::detect();

    // Low arithmetic intensity = memory bound
    assert_eq!(cap.bottleneck(0.1, false), Bottleneck::Memory);

    // High arithmetic intensity = compute bound
    assert_eq!(cap.bottleneck(1000.0, false), Bottleneck::Compute);
}

#[test]
fn test_roofline_throughput() {
    let cap = HardwareCapability::detect();

    // Memory-bound workload
    let low_ai = cap.expected_throughput_gflops(0.1, false);
    // Compute-bound workload
    let high_ai = cap.expected_throughput_gflops(1000.0, false);

    // Low AI should give lower throughput (memory limited)
    assert!(low_ai < high_ai);
}

#[test]
fn test_toml_roundtrip() {
    let cap = HardwareCapability::detect();
    let toml_str = toml::to_string_pretty(&cap).unwrap();
    let parsed: HardwareCapability = toml::from_str(&toml_str).unwrap();
    assert_eq!(cap.cpu.cores, parsed.cpu.cores);
}

#[test]
fn test_byte_budget_in_hardware_toml() {
    let cap = HardwareCapability::detect();

    // Should have byte_budget populated
    assert!(cap.byte_budget.is_some());
    let budget = cap.byte_budget.unwrap();
    assert!(budget.gb_per_sec > 0.0);
    assert!(budget.gb_per_sec <= 25.0); // Capped at zstd max

    // Test TOML roundtrip preserves byte_budget
    let toml_str = toml::to_string_pretty(&cap).unwrap();
    assert!(toml_str.contains("[byte_budget]"));
    assert!(toml_str.contains("gb_per_sec"));

    let parsed: HardwareCapability = toml::from_str(&toml_str).unwrap();
    assert!(parsed.byte_budget.is_some());
    let parsed_budget = parsed.byte_budget.unwrap();
    assert!((parsed_budget.gb_per_sec - budget.gb_per_sec).abs() < 0.001);
}

#[test]
fn test_byte_budget_backward_compat() {
    // Test that hardware.toml without byte_budget still parses
    let toml_without_budget = r#"
timestamp = "2026-01-13T18:00:00Z"
hostname = "test"

[cpu]
vendor = "Intel"
model = "Test CPU"
cores = 4
threads = 8
simd = "Avx2"
base_freq_ghz = 3.5
peak_gflops = 112.0
memory_bw_gbps = 80.0

[roofline]
cpu_arithmetic_intensity = 1.4
"#;
    let parsed: HardwareCapability = toml::from_str(toml_without_budget).unwrap();
    // byte_budget should be None when not in TOML (backward compat)
    assert!(parsed.byte_budget.is_none());
}

// Additional coverage tests

#[test]
fn test_simd_width_bits() {
    assert_eq!(SimdWidth::Scalar.bits(), 32);
    assert_eq!(SimdWidth::Sse2.bits(), 128);
    assert_eq!(SimdWidth::Neon128.bits(), 128);
    assert_eq!(SimdWidth::WasmSimd128.bits(), 128);
    assert_eq!(SimdWidth::Avx2.bits(), 256);
    assert_eq!(SimdWidth::Avx512.bits(), 512);
}

#[test]
fn test_simd_width_compute_speedup() {
    assert!((SimdWidth::Scalar.compute_speedup() - 1.0).abs() < 0.01);
    assert!((SimdWidth::Sse2.compute_speedup() - 4.0).abs() < 0.01);
    assert!((SimdWidth::Neon128.compute_speedup() - 4.0).abs() < 0.01);
    assert!((SimdWidth::WasmSimd128.compute_speedup() - 4.0).abs() < 0.01);
    assert!((SimdWidth::Avx2.compute_speedup() - 10.0).abs() < 0.01);
    assert!((SimdWidth::Avx512.compute_speedup() - 12.0).abs() < 0.01);
}

#[test]
fn test_best_backend() {
    let cap = HardwareCapability::detect();
    let backend = cap.best_backend();
    // Should be a valid backend (even if None)
    assert!(matches!(
        backend,
        GpuBackend::None
            | GpuBackend::Cuda
            | GpuBackend::Metal
            | GpuBackend::Vulkan
            | GpuBackend::Wgpu
    ));
}

#[test]
fn test_load_or_detect_creates_new() {
    use std::path::PathBuf;
    let tmp_path = PathBuf::from("/tmp/trueno_test_nonexistent_12345.toml");
    // Ensure it doesn't exist
    let _ = std::fs::remove_file(&tmp_path);

    let cap = HardwareCapability::load_or_detect(&tmp_path);
    assert!(cap.cpu.cores > 0);

    // Cleanup
    let _ = std::fs::remove_file(&tmp_path);
}

#[test]
fn test_save_and_load() {
    use std::path::PathBuf;
    let tmp_path = PathBuf::from("/tmp/trueno_test_save_load.toml");

    let original = HardwareCapability::detect();
    original.save(&tmp_path).expect("Failed to save");

    let loaded = HardwareCapability::load_or_detect(&tmp_path);
    assert_eq!(original.cpu.cores, loaded.cpu.cores);
    assert_eq!(original.hostname, loaded.hostname);

    // Cleanup
    let _ = std::fs::remove_file(&tmp_path);
}

#[test]
fn test_expected_throughput_with_gpu() {
    // Create a capability with GPU
    let cap = HardwareCapability::detect();

    // Test GPU branch if available
    if cap.gpu.is_some() {
        let throughput_gpu = cap.expected_throughput_gflops(10.0, true);
        let throughput_cpu = cap.expected_throughput_gflops(10.0, false);
        // Both should be positive
        assert!(throughput_gpu > 0.0);
        assert!(throughput_cpu > 0.0);
    }

    // CPU path should always work
    let cpu_throughput = cap.expected_throughput_gflops(10.0, false);
    assert!(cpu_throughput > 0.0);
}

#[test]
fn test_expected_throughput_with_fake_gpu() {
    // Create a capability with a fake GPU to test GPU branch
    let mut cap = HardwareCapability::detect();
    cap.gpu = Some(GpuCapability {
        vendor: "Test".to_string(),
        model: "Fake GPU".to_string(),
        backend: GpuBackend::Cuda,
        compute_capability: Some("8.9".to_string()),
        peak_tflops_fp32: 100.0,
        peak_tflops_tensor: Some(400.0),
        memory_bw_gbps: 1000.0,
        vram_gb: 24.0,
    });

    // This should exercise the GPU branch
    let throughput_gpu = cap.expected_throughput_gflops(10.0, true);
    let throughput_cpu = cap.expected_throughput_gflops(10.0, false);

    // GPU with 1000 GB/s and AI=10: memory_bound = 10000 GFLOPS
    // GPU compute = 100 TFLOPS = 100000 GFLOPS
    // Result should be min(10000, 100000) = 10000
    assert!((throughput_gpu - 10000.0).abs() < 1.0);
    assert!(throughput_cpu > 0.0);
}

#[test]
fn test_load_invalid_toml() {
    let tmp_path = std::env::temp_dir().join("trueno_test_invalid.toml");

    // Write invalid TOML
    std::fs::write(&tmp_path, "this is not valid toml [[[").expect("Failed to write");

    // Should fall back to detect
    let cap = HardwareCapability::load_or_detect(&tmp_path);
    assert!(cap.cpu.cores > 0);

    // Cleanup
    let _ = std::fs::remove_file(&tmp_path);
}

#[test]
fn test_expected_throughput_no_gpu_fallback() {
    // Create a capability without GPU
    let mut cap = HardwareCapability::detect();
    cap.gpu = None;

    // Request GPU but none available - should fallback to CPU
    let throughput_gpu_request = cap.expected_throughput_gflops(10.0, true);
    let throughput_cpu = cap.expected_throughput_gflops(10.0, false);

    // Both should give the same result since there's no GPU
    assert!((throughput_gpu_request - throughput_cpu).abs() < 0.001);
    assert!(throughput_cpu > 0.0);
}

#[test]
fn test_bottleneck_with_gpu() {
    // Create capability with fake GPU to test GPU bottleneck path
    let mut cap = HardwareCapability::detect();
    cap.gpu = Some(GpuCapability {
        vendor: "Test".to_string(),
        model: "Fake GPU".to_string(),
        backend: GpuBackend::Cuda,
        compute_capability: Some("8.9".to_string()),
        peak_tflops_fp32: 100.0,
        peak_tflops_tensor: Some(400.0),
        memory_bw_gbps: 1000.0,
        vram_gb: 24.0,
    });
    cap.roofline.gpu_arithmetic_intensity = Some(50.0);

    // Low AI should be memory bound
    assert_eq!(cap.bottleneck(10.0, true), Bottleneck::Memory);

    // High AI should be compute bound
    assert_eq!(cap.bottleneck(100.0, true), Bottleneck::Compute);

    // Test edge case at threshold
    assert_eq!(cap.bottleneck(50.0, true), Bottleneck::Compute);
}

#[test]
fn test_bottleneck_gpu_without_ai() {
    // Create capability with GPU but no gpu_arithmetic_intensity
    let mut cap = HardwareCapability::detect();
    cap.gpu = Some(GpuCapability {
        vendor: "Test".to_string(),
        model: "Fake GPU".to_string(),
        backend: GpuBackend::Cuda,
        compute_capability: None,
        peak_tflops_fp32: 50.0,
        peak_tflops_tensor: None,
        memory_bw_gbps: 500.0,
        vram_gb: 8.0,
    });
    cap.roofline.gpu_arithmetic_intensity = None; // No GPU AI set

    // When gpu_arithmetic_intensity is None, uses f64::MAX as threshold
    // So any finite AI should be memory bound
    assert_eq!(cap.bottleneck(1000.0, true), Bottleneck::Memory);
}

#[test]
fn test_simd_width_neon() {
    // Test NEON SIMD width (4 lanes)
    assert_eq!(SimdWidth::Neon128.lanes(), 4);
}

#[test]
fn test_simd_width_sse2() {
    // Test SSE2 SIMD width (4 lanes)
    assert_eq!(SimdWidth::Sse2.lanes(), 4);
}

#[test]
fn test_best_backend_without_gpu() {
    let mut cap = HardwareCapability::detect();
    cap.gpu = None;

    // Should return None backend when no GPU
    assert_eq!(cap.best_backend(), GpuBackend::None);
}

#[test]
fn test_best_backend_with_gpu() {
    let mut cap = HardwareCapability::detect();
    cap.gpu = Some(GpuCapability {
        vendor: "NVIDIA".to_string(),
        model: "RTX 4090".to_string(),
        backend: GpuBackend::Cuda,
        compute_capability: Some("8.9".to_string()),
        peak_tflops_fp32: 82.58,
        peak_tflops_tensor: Some(330.3),
        memory_bw_gbps: 1008.0,
        vram_gb: 24.0,
    });

    assert_eq!(cap.best_backend(), GpuBackend::Cuda);
}

#[test]
fn test_gpu_backend_variants() {
    // Test all GPU backend variants
    assert_ne!(GpuBackend::None, GpuBackend::Cuda);
    assert_ne!(GpuBackend::Cuda, GpuBackend::Vulkan);
    assert_ne!(GpuBackend::Vulkan, GpuBackend::Metal);

    // Test debug formatting
    let debug_str = format!("{:?}", GpuBackend::Cuda);
    assert!(debug_str.contains("Cuda"));
}