scirs2_sparse/gpu/
vulkan.rs

1//! Vulkan GPU backend for sparse matrix operations
2//!
3//! This module provides Vulkan-accelerated sparse matrix operations with
4//! cross-platform support for various GPU vendors (NVIDIA, AMD, Intel, etc.)
5
6use crate::csr_array::CsrArray;
7use crate::error::{SparseError, SparseResult};
8use crate::sparray::SparseArray;
9use scirs2_core::ndarray::{Array1, ArrayView1};
10use scirs2_core::numeric::{Float, SparseElement};
11use std::collections::HashMap;
12use std::fmt::Debug;
13use std::sync::Arc;
14
15#[cfg(feature = "gpu")]
16use scirs2_core::gpu::{GpuDevice, GpuError};
17
18/// Optimization levels for Vulkan backend
19#[derive(Debug, Clone, Copy, PartialEq, Eq)]
20pub enum VulkanOptimizationLevel {
21    /// Basic implementation without advanced optimizations
22    Basic,
23    /// Use compute shader optimizations
24    ComputeShader,
25    /// Use subgroup operations (requires subgroup support)
26    Subgroup,
27    /// Maximum performance with all optimizations
28    Maximum,
29}
30
31/// Vulkan device information
32#[derive(Debug, Clone)]
33pub struct VulkanDeviceInfo {
34    pub device_name: String,
35    pub vendor_id: u32,
36    pub device_type: VulkanDeviceType,
37    pub max_compute_shared_memory_size: usize,
38    pub max_compute_work_group_count: [u32; 3],
39    pub max_compute_work_group_invocations: u32,
40    pub max_compute_work_group_size: [u32; 3],
41    pub subgroup_size: u32,
42    pub supports_subgroups: bool,
43    pub supports_int8: bool,
44    pub supports_int16: bool,
45    pub supports_float64: bool,
46}
47
48#[derive(Debug, Clone, Copy, PartialEq, Eq)]
49pub enum VulkanDeviceType {
50    Other,
51    IntegratedGpu,
52    DiscreteGpu,
53    VirtualGpu,
54    Cpu,
55}
56
57impl VulkanDeviceInfo {
58    /// Detect Vulkan device information
59    pub fn detect() -> Self {
60        // In a real implementation, this would query Vulkan API
61        // For now, return reasonable defaults
62        Self {
63            device_name: "Default Vulkan Device".to_string(),
64            vendor_id: 0,
65            device_type: VulkanDeviceType::DiscreteGpu,
66            max_compute_shared_memory_size: 32768, // 32KB typical
67            max_compute_work_group_count: [65535, 65535, 65535],
68            max_compute_work_group_invocations: 1024,
69            max_compute_work_group_size: [1024, 1024, 64],
70            subgroup_size: 32,
71            supports_subgroups: true,
72            supports_int8: true,
73            supports_int16: true,
74            supports_float64: true,
75        }
76    }
77
78    /// Check if device is NVIDIA
79    pub fn is_nvidia(&self) -> bool {
80        self.vendor_id == 0x10DE
81    }
82
83    /// Check if device is AMD
84    pub fn is_amd(&self) -> bool {
85        self.vendor_id == 0x1002
86    }
87
88    /// Check if device is Intel
89    pub fn is_intel(&self) -> bool {
90        self.vendor_id == 0x8086
91    }
92
93    /// Get optimal work group size for SpMV
94    pub fn optimal_workgroup_size(&self) -> usize {
95        if self.supports_subgroups {
96            self.subgroup_size as usize
97        } else {
98            64 // Conservative default
99        }
100    }
101}
102
103/// Memory manager for Vulkan buffers
104#[derive(Debug)]
105pub struct VulkanMemoryManager {
106    allocated_buffers: HashMap<String, usize>,
107    total_allocated: usize,
108    peak_usage: usize,
109}
110
111impl VulkanMemoryManager {
112    pub fn new() -> Self {
113        Self {
114            allocated_buffers: HashMap::new(),
115            total_allocated: 0,
116            peak_usage: 0,
117        }
118    }
119
120    pub fn allocate(&mut self, id: String, size: usize) -> SparseResult<()> {
121        self.allocated_buffers.insert(id, size);
122        self.total_allocated += size;
123        if self.total_allocated > self.peak_usage {
124            self.peak_usage = self.total_allocated;
125        }
126        Ok(())
127    }
128
129    pub fn deallocate(&mut self, id: &str) -> SparseResult<()> {
130        if let Some(size) = self.allocated_buffers.remove(id) {
131            self.total_allocated = self.total_allocated.saturating_sub(size);
132        }
133        Ok(())
134    }
135
136    pub fn current_usage(&self) -> usize {
137        self.total_allocated
138    }
139
140    pub fn peak_usage(&self) -> usize {
141        self.peak_usage
142    }
143
144    pub fn reset(&mut self) {
145        self.allocated_buffers.clear();
146        self.total_allocated = 0;
147        self.peak_usage = 0;
148    }
149}
150
151impl Default for VulkanMemoryManager {
152    fn default() -> Self {
153        Self::new()
154    }
155}
156
157/// Vulkan sparse matrix-vector multiplication handler
158pub struct VulkanSpMatVec {
159    device_info: VulkanDeviceInfo,
160    memory_manager: VulkanMemoryManager,
161    shader_cache: HashMap<String, Arc<Vec<u8>>>,
162}
163
164impl VulkanSpMatVec {
165    /// Create a new Vulkan SpMV handler
166    pub fn new() -> SparseResult<Self> {
167        let device_info = VulkanDeviceInfo::detect();
168
169        Ok(Self {
170            device_info,
171            memory_manager: VulkanMemoryManager::new(),
172            shader_cache: HashMap::new(),
173        })
174    }
175
176    /// Get device information
177    pub fn device_info(&self) -> &VulkanDeviceInfo {
178        &self.device_info
179    }
180
181    /// Get memory manager
182    pub fn memory_manager(&self) -> &VulkanMemoryManager {
183        &self.memory_manager
184    }
185
186    /// Get mutable memory manager
187    pub fn memory_manager_mut(&mut self) -> &mut VulkanMemoryManager {
188        &mut self.memory_manager
189    }
190
191    /// Execute sparse matrix-vector multiplication using Vulkan
192    #[cfg(feature = "gpu")]
193    pub fn execute_spmv<T>(
194        &self,
195        matrix: &CsrArray<T>,
196        vector: &ArrayView1<T>,
197        device: &GpuDevice,
198    ) -> SparseResult<Array1<T>>
199    where
200        T: Float + SparseElement + Debug + Copy + std::iter::Sum,
201    {
202        self.execute_optimized_spmv(
203            matrix,
204            vector,
205            device,
206            VulkanOptimizationLevel::ComputeShader,
207        )
208    }
209
210    /// Execute optimized sparse matrix-vector multiplication using Vulkan
211    #[cfg(feature = "gpu")]
212    pub fn execute_optimized_spmv<T>(
213        &self,
214        matrix: &CsrArray<T>,
215        vector: &ArrayView1<T>,
216        device: &GpuDevice,
217        optimization_level: VulkanOptimizationLevel,
218    ) -> SparseResult<Array1<T>>
219    where
220        T: Float + SparseElement + Debug + Copy + std::iter::Sum,
221    {
222        // Validate inputs
223        let (nrows, ncols) = matrix.shape();
224        if vector.len() != ncols {
225            return Err(SparseError::DimensionMismatch {
226                expected: ncols,
227                found: vector.len(),
228            });
229        }
230
231        // In a real implementation, we would:
232        // 1. Create Vulkan command buffer
233        // 2. Allocate GPU buffers for matrix data (indptr, indices, data)
234        // 3. Allocate GPU buffer for input vector
235        // 4. Allocate GPU buffer for output vector
236        // 5. Load appropriate compute shader based on optimization level
237        // 6. Dispatch compute shader with appropriate workgroup size
238        // 7. Read back results
239
240        // For now, fall back to CPU implementation
241        matrix.dot_vector(vector)
242    }
243
244    /// CPU fallback implementation
245    pub fn execute_spmv_cpu<T>(
246        &self,
247        matrix: &CsrArray<T>,
248        vector: &ArrayView1<T>,
249    ) -> SparseResult<Array1<T>>
250    where
251        T: Float + SparseElement + Debug + Copy + std::iter::Sum,
252    {
253        matrix.dot_vector(vector)
254    }
255
256    /// Get shader source code for CSR SpMV
257    fn get_spmv_shader_source(&self, optimization_level: VulkanOptimizationLevel) -> &str {
258        match optimization_level {
259            VulkanOptimizationLevel::Basic => {
260                // Basic compute shader
261                r#"
262#version 450
263
264layout (local_size_x = 64, local_size_y = 1, local_size_z = 1) in;
265
266layout(set = 0, binding = 0) readonly buffer IndptrBuffer {
267    uint indptr[];
268};
269
270layout(set = 0, binding = 1) readonly buffer IndicesBuffer {
271    uint indices[];
272};
273
274layout(set = 0, binding = 2) readonly buffer DataBuffer {
275    float data[];
276};
277
278layout(set = 0, binding = 3) readonly buffer VectorBuffer {
279    float vector[];
280};
281
282layout(set = 0, binding = 4) writeonly buffer ResultBuffer {
283    float result[];
284};
285
286layout(push_constant) uniform PushConstants {
287    uint nrows;
288} pc;
289
290void main() {
291    uint row = gl_GlobalInvocationID.x;
292
293    if (row >= pc.nrows) {
294        return;
295    }
296
297    uint row_start = indptr[row];
298    uint row_end = indptr[row + 1];
299
300    float sum = 0.0;
301    for (uint i = row_start; i < row_end; i++) {
302        uint col = indices[i];
303        sum += data[i] * vector[col];
304    }
305
306    result[row] = sum;
307}
308"#
309            }
310            VulkanOptimizationLevel::ComputeShader => {
311                // Optimized with shared memory
312                r#"
313#version 450
314
315layout (local_size_x = 64, local_size_y = 1, local_size_z = 1) in;
316
317layout(set = 0, binding = 0) readonly buffer IndptrBuffer {
318    uint indptr[];
319};
320
321layout(set = 0, binding = 1) readonly buffer IndicesBuffer {
322    uint indices[];
323};
324
325layout(set = 0, binding = 2) readonly buffer DataBuffer {
326    float data[];
327};
328
329layout(set = 0, binding = 3) readonly buffer VectorBuffer {
330    float vector[];
331};
332
333layout(set = 0, binding = 4) writeonly buffer ResultBuffer {
334    float result[];
335};
336
337layout(push_constant) uniform PushConstants {
338    uint nrows;
339} pc;
340
341shared float shared_vector[256];
342
343void main() {
344    uint row = gl_GlobalInvocationID.x;
345    uint local_id = gl_LocalInvocationID.x;
346
347    if (row >= pc.nrows) {
348        return;
349    }
350
351    uint row_start = indptr[row];
352    uint row_end = indptr[row + 1];
353
354    float sum = 0.0;
355    for (uint i = row_start; i < row_end; i++) {
356        uint col = indices[i];
357
358        // Cooperative loading to shared memory for better cache utilization
359        if (col < 256) {
360            shared_vector[col] = vector[col];
361            memoryBarrierShared();
362            barrier();
363            sum += data[i] * shared_vector[col];
364        } else {
365            sum += data[i] * vector[col];
366        }
367    }
368
369    result[row] = sum;
370}
371"#
372            }
373            VulkanOptimizationLevel::Subgroup => {
374                // Using subgroup operations
375                r#"
376#version 450
377#extension GL_KHR_shader_subgroup_arithmetic : enable
378
379layout (local_size_x = 64, local_size_y = 1, local_size_z = 1) in;
380
381layout(set = 0, binding = 0) readonly buffer IndptrBuffer {
382    uint indptr[];
383};
384
385layout(set = 0, binding = 1) readonly buffer IndicesBuffer {
386    uint indices[];
387};
388
389layout(set = 0, binding = 2) readonly buffer DataBuffer {
390    float data[];
391};
392
393layout(set = 0, binding = 3) readonly buffer VectorBuffer {
394    float vector[];
395};
396
397layout(set = 0, binding = 4) writeonly buffer ResultBuffer {
398    float result[];
399};
400
401layout(push_constant) uniform PushConstants {
402    uint nrows;
403} pc;
404
405void main() {
406    uint row = gl_GlobalInvocationID.x;
407
408    if (row >= pc.nrows) {
409        return;
410    }
411
412    uint row_start = indptr[row];
413    uint row_end = indptr[row + 1];
414
415    float sum = 0.0;
416    for (uint i = row_start; i < row_end; i++) {
417        uint col = indices[i];
418        sum += data[i] * vector[col];
419    }
420
421    // Use subgroup reduction for better performance
422    sum = subgroupAdd(sum);
423
424    if (subgroupElect()) {
425        result[row] = sum;
426    }
427}
428"#
429            }
430            VulkanOptimizationLevel::Maximum => {
431                // Maximum optimization with all features
432                self.get_spmv_shader_source(VulkanOptimizationLevel::Subgroup)
433            }
434        }
435    }
436
437    /// Compile shader (placeholder - would use shaderc in real implementation)
438    fn compile_shader(&mut self, source: &str, name: &str) -> SparseResult<Arc<Vec<u8>>> {
439        // In real implementation, would compile GLSL to SPIR-V
440        // For now, just cache a dummy bytecode
441        let bytecode = Arc::new(source.as_bytes().to_vec());
442        self.shader_cache.insert(name.to_string(), bytecode.clone());
443        Ok(bytecode)
444    }
445}
446
447#[cfg(test)]
448mod tests {
449    use super::*;
450
451    #[test]
452    fn test_vulkan_device_info() {
453        let info = VulkanDeviceInfo::detect();
454        assert!(!info.device_name.is_empty());
455        assert!(info.optimal_workgroup_size() > 0);
456    }
457
458    #[test]
459    fn test_vulkan_memory_manager() {
460        let mut manager = VulkanMemoryManager::new();
461
462        manager
463            .allocate("buffer1".to_string(), 1024)
464            .expect("Failed to allocate");
465        assert_eq!(manager.current_usage(), 1024);
466
467        manager
468            .allocate("buffer2".to_string(), 2048)
469            .expect("Failed to allocate");
470        assert_eq!(manager.current_usage(), 3072);
471        assert_eq!(manager.peak_usage(), 3072);
472
473        manager.deallocate("buffer1").expect("Failed to deallocate");
474        assert_eq!(manager.current_usage(), 2048);
475        assert_eq!(manager.peak_usage(), 3072);
476
477        manager.reset();
478        assert_eq!(manager.current_usage(), 0);
479    }
480
481    #[test]
482    fn test_vulkan_spmv_creation() {
483        let result = VulkanSpMatVec::new();
484        assert!(result.is_ok());
485
486        let spmv = result.expect("Failed to create");
487        assert!(spmv.device_info().optimal_workgroup_size() > 0);
488    }
489
490    #[test]
491    fn test_vulkan_cpu_fallback() {
492        let spmv = VulkanSpMatVec::new().expect("Failed to create");
493
494        // Create a simple test matrix
495        let rows = vec![0, 0, 1, 2];
496        let cols = vec![0, 1, 1, 2];
497        let data = vec![1.0, 2.0, 3.0, 4.0];
498        let matrix = CsrArray::from_triplets(&rows, &cols, &data, (3, 3), false)
499            .expect("Failed to create matrix");
500
501        let vector = Array1::from_vec(vec![1.0, 2.0, 3.0]);
502        let result = spmv
503            .execute_spmv_cpu(&matrix, &vector.view())
504            .expect("Failed to execute");
505
506        assert_eq!(result.len(), 3);
507    }
508
509    #[test]
510    fn test_shader_source_generation() {
511        let spmv = VulkanSpMatVec::new().expect("Failed to create");
512
513        let basic_shader = spmv.get_spmv_shader_source(VulkanOptimizationLevel::Basic);
514        assert!(basic_shader.contains("#version 450"));
515        assert!(basic_shader.contains("layout"));
516
517        let optimized_shader = spmv.get_spmv_shader_source(VulkanOptimizationLevel::ComputeShader);
518        assert!(optimized_shader.contains("shared"));
519
520        let subgroup_shader = spmv.get_spmv_shader_source(VulkanOptimizationLevel::Subgroup);
521        assert!(subgroup_shader.contains("subgroup"));
522    }
523}
scirs2_sparse/gpu/vulkan.rs

scirs2_sparse/gpu/
vulkan.rs
