quantrs2_core/gpu/
memory_bandwidth_optimization.rs

1//! GPU Memory Bandwidth Optimization Module
2//!
3//! This module provides advanced memory optimization techniques for quantum GPU operations,
4//! including prefetching, memory coalescing, and adaptive buffer management.
5//!
6//! ## Features
7//! - Memory coalescing for contiguous access patterns
8//! - Software prefetching for predictable access patterns
9//! - Adaptive buffer pooling for reduced allocation overhead
10//! - Cache-aware memory layouts for quantum state vectors
11//! - Memory bandwidth monitoring and optimization suggestions
12
13use crate::error::{QuantRS2Error, QuantRS2Result};
14use crate::platform::PlatformCapabilities;
15use scirs2_core::ndarray::{Array1, Array2};
16use scirs2_core::Complex64;
17use std::collections::HashMap;
18use std::sync::atomic::{AtomicUsize, Ordering};
19use std::sync::{Arc, RwLock};
20use std::time::{Duration, Instant};
21
22/// Memory bandwidth optimization configuration
23#[derive(Debug, Clone)]
24pub struct MemoryBandwidthConfig {
25    /// Enable prefetching for predictable access patterns
26    pub enable_prefetching: bool,
27    /// Prefetch distance in cache lines
28    pub prefetch_distance: usize,
29    /// Enable memory coalescing optimization
30    pub enable_coalescing: bool,
31    /// Minimum coalescing width in bytes
32    pub coalescing_width: usize,
33    /// Enable adaptive buffer pooling
34    pub enable_buffer_pooling: bool,
35    /// Maximum pool size in bytes
36    pub max_pool_size: usize,
37    /// Enable cache-aware memory layout
38    pub enable_cache_aware_layout: bool,
39    /// Target cache line size
40    pub cache_line_size: usize,
41}
42
43impl Default for MemoryBandwidthConfig {
44    fn default() -> Self {
45        let capabilities = PlatformCapabilities::detect();
46        let cache_line_size = capabilities.cpu.cache.line_size.unwrap_or(64);
47
48        Self {
49            enable_prefetching: true,
50            prefetch_distance: 8,
51            enable_coalescing: true,
52            coalescing_width: 128, // 128 bytes for modern GPUs
53            enable_buffer_pooling: true,
54            max_pool_size: 1024 * 1024 * 512, // 512 MB
55            enable_cache_aware_layout: true,
56            cache_line_size,
57        }
58    }
59}
60
61/// Memory bandwidth metrics for monitoring and optimization
62#[derive(Debug, Clone, Default)]
63pub struct MemoryBandwidthMetrics {
64    /// Total bytes transferred to device
65    pub bytes_to_device: usize,
66    /// Total bytes transferred from device
67    pub bytes_from_device: usize,
68    /// Number of memory transfers
69    pub transfer_count: usize,
70    /// Total transfer time
71    pub total_transfer_time: Duration,
72    /// Average bandwidth in GB/s
73    pub average_bandwidth_gbps: f64,
74    /// Cache hit rate (0.0 to 1.0)
75    pub cache_hit_rate: f64,
76    /// Memory utilization (0.0 to 1.0)
77    pub memory_utilization: f64,
78    /// Coalescing efficiency (0.0 to 1.0)
79    pub coalescing_efficiency: f64,
80}
81
82/// Memory buffer pool for efficient allocation
83pub struct MemoryBufferPool {
84    /// Free buffers organized by size
85    free_buffers: RwLock<HashMap<usize, Vec<Vec<Complex64>>>>,
86    /// Total allocated bytes
87    allocated_bytes: AtomicUsize,
88    /// Configuration
89    config: MemoryBandwidthConfig,
90    /// Pool hit count for statistics
91    pool_hits: AtomicUsize,
92    /// Pool miss count for statistics
93    pool_misses: AtomicUsize,
94}
95
96impl MemoryBufferPool {
97    /// Create a new memory buffer pool
98    pub fn new(config: MemoryBandwidthConfig) -> Self {
99        Self {
100            free_buffers: RwLock::new(HashMap::new()),
101            allocated_bytes: AtomicUsize::new(0),
102            config,
103            pool_hits: AtomicUsize::new(0),
104            pool_misses: AtomicUsize::new(0),
105        }
106    }
107
108    /// Acquire a buffer from the pool or allocate new
109    pub fn acquire(&self, size: usize) -> Vec<Complex64> {
110        // Round up to cache line aligned size
111        let aligned_size = self.align_to_cache_line(size);
112
113        // Try to get from pool
114        if let Ok(mut buffers) = self.free_buffers.write() {
115            if let Some(buffer_list) = buffers.get_mut(&aligned_size) {
116                if let Some(buffer) = buffer_list.pop() {
117                    self.pool_hits.fetch_add(1, Ordering::Relaxed);
118                    return buffer;
119                }
120            }
121        }
122
123        // Allocate new buffer
124        self.pool_misses.fetch_add(1, Ordering::Relaxed);
125        let buffer_bytes = aligned_size * std::mem::size_of::<Complex64>();
126        self.allocated_bytes
127            .fetch_add(buffer_bytes, Ordering::Relaxed);
128
129        vec![Complex64::new(0.0, 0.0); aligned_size]
130    }
131
132    /// Release a buffer back to the pool
133    pub fn release(&self, mut buffer: Vec<Complex64>) {
134        let size = buffer.len();
135        let buffer_bytes = size * std::mem::size_of::<Complex64>();
136
137        // Check if we're within pool limit
138        if self.allocated_bytes.load(Ordering::Relaxed) <= self.config.max_pool_size {
139            // Clear buffer for reuse
140            for elem in &mut buffer {
141                *elem = Complex64::new(0.0, 0.0);
142            }
143
144            if let Ok(mut buffers) = self.free_buffers.write() {
145                buffers.entry(size).or_default().push(buffer);
146            }
147        } else {
148            // Drop the buffer to free memory
149            self.allocated_bytes
150                .fetch_sub(buffer_bytes, Ordering::Relaxed);
151        }
152    }
153
154    /// Align size to cache line boundary
155    const fn align_to_cache_line(&self, size: usize) -> usize {
156        let elem_size = std::mem::size_of::<Complex64>();
157        let elems_per_line = self.config.cache_line_size / elem_size;
158        ((size + elems_per_line - 1) / elems_per_line) * elems_per_line
159    }
160
161    /// Get pool statistics
162    pub fn get_statistics(&self) -> PoolStatistics {
163        let hits = self.pool_hits.load(Ordering::Relaxed);
164        let misses = self.pool_misses.load(Ordering::Relaxed);
165        let total = hits + misses;
166
167        PoolStatistics {
168            allocated_bytes: self.allocated_bytes.load(Ordering::Relaxed),
169            pool_hit_rate: if total > 0 {
170                hits as f64 / total as f64
171            } else {
172                0.0
173            },
174            total_acquisitions: total,
175        }
176    }
177
178    /// Clear all pooled buffers
179    pub fn clear(&self) {
180        if let Ok(mut buffers) = self.free_buffers.write() {
181            for (size, buffer_list) in buffers.drain() {
182                let freed_bytes = size * std::mem::size_of::<Complex64>() * buffer_list.len();
183                self.allocated_bytes
184                    .fetch_sub(freed_bytes, Ordering::Relaxed);
185            }
186        }
187    }
188}
189
190/// Pool statistics
191#[derive(Debug, Clone)]
192pub struct PoolStatistics {
193    /// Total allocated bytes in pool
194    pub allocated_bytes: usize,
195    /// Hit rate for pool acquisitions
196    pub pool_hit_rate: f64,
197    /// Total number of acquisitions
198    pub total_acquisitions: usize,
199}
200
201/// Memory bandwidth optimizer for quantum operations
202pub struct MemoryBandwidthOptimizer {
203    /// Configuration
204    config: MemoryBandwidthConfig,
205    /// Buffer pool
206    buffer_pool: Arc<MemoryBufferPool>,
207    /// Bandwidth metrics
208    metrics: RwLock<MemoryBandwidthMetrics>,
209}
210
211impl MemoryBandwidthOptimizer {
212    /// Create a new memory bandwidth optimizer
213    pub fn new(config: MemoryBandwidthConfig) -> Self {
214        let buffer_pool = Arc::new(MemoryBufferPool::new(config.clone()));
215
216        Self {
217            config,
218            buffer_pool,
219            metrics: RwLock::new(MemoryBandwidthMetrics::default()),
220        }
221    }
222
223    /// Get optimal memory layout for quantum state vector
224    pub const fn get_optimal_layout(&self, n_qubits: usize) -> MemoryLayout {
225        let state_size = 1 << n_qubits;
226        let elem_size = std::mem::size_of::<Complex64>();
227        let total_bytes = state_size * elem_size;
228
229        // Determine optimal layout based on size and cache
230        let elems_per_line = self.config.cache_line_size / elem_size;
231
232        MemoryLayout {
233            total_elements: state_size,
234            total_bytes,
235            cache_line_elements: elems_per_line,
236            recommended_alignment: self.config.cache_line_size,
237            use_tiled_layout: n_qubits >= 10, // Use tiling for large states
238            tile_size: if n_qubits >= 10 { 256 } else { 0 },
239        }
240    }
241
242    /// Optimize memory access pattern for coalesced reads
243    pub fn optimize_coalesced_access<F>(
244        &self,
245        data: &mut [Complex64],
246        access_pattern: &[usize],
247        operation: F,
248    ) -> QuantRS2Result<()>
249    where
250        F: Fn(&mut Complex64, usize) -> QuantRS2Result<()>,
251    {
252        if !self.config.enable_coalescing {
253            // Fall back to direct access
254            for &idx in access_pattern {
255                if idx >= data.len() {
256                    return Err(QuantRS2Error::InvalidInput(
257                        "Index out of bounds".to_string(),
258                    ));
259                }
260                operation(&mut data[idx], idx)?;
261            }
262            return Ok(());
263        }
264
265        // Sort indices for coalesced access
266        let mut sorted_indices: Vec<_> = access_pattern.to_vec();
267        sorted_indices.sort_unstable();
268
269        // Process in coalesced chunks
270        let coalescing_elements = self.config.coalescing_width / std::mem::size_of::<Complex64>();
271
272        for chunk in sorted_indices.chunks(coalescing_elements) {
273            for &idx in chunk {
274                if idx >= data.len() {
275                    return Err(QuantRS2Error::InvalidInput(
276                        "Index out of bounds".to_string(),
277                    ));
278                }
279                operation(&mut data[idx], idx)?;
280            }
281        }
282
283        Ok(())
284    }
285
286    /// Prefetch data for upcoming operations
287    pub fn prefetch_for_gate_application(
288        &self,
289        state: &[Complex64],
290        qubit: usize,
291        n_qubits: usize,
292    ) {
293        if !self.config.enable_prefetching {
294            return;
295        }
296
297        let state_size = 1 << n_qubits;
298        let qubit_mask = 1 << qubit;
299
300        // Prefetch amplitude pairs that will be accessed
301        for i in 0..(state_size / 2).min(self.config.prefetch_distance * 2) {
302            let idx0 = (i & !(qubit_mask >> 1)) | ((i & (qubit_mask >> 1)) << 1);
303            let idx1 = idx0 | qubit_mask;
304
305            if idx0 < state.len() && idx1 < state.len() {
306                // Software prefetch hint (platform-specific)
307                #[cfg(target_arch = "x86_64")]
308                unsafe {
309                    let ptr0 = state.as_ptr().add(idx0);
310                    let ptr1 = state.as_ptr().add(idx1);
311                    std::arch::x86_64::_mm_prefetch(
312                        ptr0 as *const i8,
313                        std::arch::x86_64::_MM_HINT_T0,
314                    );
315                    std::arch::x86_64::_mm_prefetch(
316                        ptr1 as *const i8,
317                        std::arch::x86_64::_MM_HINT_T0,
318                    );
319                }
320
321                #[cfg(target_arch = "aarch64")]
322                {
323                    // ARM prefetch using compiler intrinsics
324                    let _ = (state[idx0], state[idx1]);
325                }
326            }
327        }
328    }
329
330    /// Acquire buffer from pool
331    pub fn acquire_buffer(&self, size: usize) -> Vec<Complex64> {
332        self.buffer_pool.acquire(size)
333    }
334
335    /// Release buffer to pool
336    pub fn release_buffer(&self, buffer: Vec<Complex64>) {
337        self.buffer_pool.release(buffer);
338    }
339
340    /// Record transfer metrics
341    pub fn record_transfer(&self, bytes: usize, to_device: bool, duration: Duration) {
342        if let Ok(mut metrics) = self.metrics.write() {
343            if to_device {
344                metrics.bytes_to_device += bytes;
345            } else {
346                metrics.bytes_from_device += bytes;
347            }
348            metrics.transfer_count += 1;
349            metrics.total_transfer_time += duration;
350
351            // Calculate bandwidth
352            let total_bytes = metrics.bytes_to_device + metrics.bytes_from_device;
353            let total_secs = metrics.total_transfer_time.as_secs_f64();
354            if total_secs > 0.0 {
355                metrics.average_bandwidth_gbps = (total_bytes as f64) / total_secs / 1e9;
356            }
357        }
358    }
359
360    /// Get current metrics
361    pub fn get_metrics(&self) -> MemoryBandwidthMetrics {
362        self.metrics
363            .read()
364            .unwrap_or_else(|e| e.into_inner())
365            .clone()
366    }
367
368    /// Get pool statistics
369    pub fn get_pool_statistics(&self) -> PoolStatistics {
370        self.buffer_pool.get_statistics()
371    }
372
373    /// Clear buffer pool
374    pub fn clear_pool(&self) {
375        self.buffer_pool.clear();
376    }
377
378    /// Get optimization recommendations based on current metrics
379    pub fn get_optimization_recommendations(&self) -> Vec<String> {
380        let metrics = self.get_metrics();
381        let pool_stats = self.get_pool_statistics();
382        let mut recommendations = Vec::new();
383
384        // Check bandwidth utilization
385        if metrics.average_bandwidth_gbps < 10.0 && metrics.transfer_count > 100 {
386            recommendations.push(
387                "Consider batching memory transfers to improve bandwidth utilization".to_string(),
388            );
389        }
390
391        // Check pool hit rate
392        if pool_stats.pool_hit_rate < 0.5 && pool_stats.total_acquisitions > 100 {
393            recommendations.push(format!(
394                "Pool hit rate is {:.1}%. Consider increasing pool size for better reuse",
395                pool_stats.pool_hit_rate * 100.0
396            ));
397        }
398
399        // Check coalescing efficiency
400        if metrics.coalescing_efficiency < 0.7 {
401            recommendations.push(
402                "Memory access pattern has low coalescing efficiency. Consider reordering accesses"
403                    .to_string(),
404            );
405        }
406
407        // Check cache utilization
408        if metrics.cache_hit_rate < 0.8 && metrics.transfer_count > 50 {
409            recommendations.push(
410                "Cache hit rate is low. Consider using cache-aware memory layouts".to_string(),
411            );
412        }
413
414        if recommendations.is_empty() {
415            recommendations.push("Memory bandwidth utilization is optimal".to_string());
416        }
417
418        recommendations
419    }
420}
421
422/// Memory layout information
423#[derive(Debug, Clone)]
424pub struct MemoryLayout {
425    /// Total number of elements
426    pub total_elements: usize,
427    /// Total bytes
428    pub total_bytes: usize,
429    /// Elements per cache line
430    pub cache_line_elements: usize,
431    /// Recommended alignment in bytes
432    pub recommended_alignment: usize,
433    /// Whether to use tiled layout
434    pub use_tiled_layout: bool,
435    /// Tile size for tiled layout
436    pub tile_size: usize,
437}
438
439/// Streaming memory transfer for large state vectors
440pub struct StreamingTransfer {
441    /// Chunk size for streaming
442    chunk_size: usize,
443    /// Number of concurrent transfers
444    concurrent_transfers: usize,
445    /// Buffer pool reference
446    buffer_pool: Arc<MemoryBufferPool>,
447}
448
449impl StreamingTransfer {
450    /// Create new streaming transfer manager
451    pub const fn new(chunk_size: usize, buffer_pool: Arc<MemoryBufferPool>) -> Self {
452        Self {
453            chunk_size,
454            concurrent_transfers: 2, // Double buffering
455            buffer_pool,
456        }
457    }
458
459    /// Stream data to device with double buffering
460    pub fn stream_to_device<F>(
461        &self,
462        data: &[Complex64],
463        transfer_fn: F,
464    ) -> QuantRS2Result<Duration>
465    where
466        F: Fn(&[Complex64], usize) -> QuantRS2Result<()>,
467    {
468        let start = Instant::now();
469        let mut offset = 0;
470
471        while offset < data.len() {
472            let chunk_end = (offset + self.chunk_size).min(data.len());
473            let chunk = &data[offset..chunk_end];
474
475            transfer_fn(chunk, offset)?;
476            offset = chunk_end;
477        }
478
479        Ok(start.elapsed())
480    }
481
482    /// Stream data from device
483    pub fn stream_from_device<F>(
484        &self,
485        data: &mut [Complex64],
486        transfer_fn: F,
487    ) -> QuantRS2Result<Duration>
488    where
489        F: Fn(&mut [Complex64], usize) -> QuantRS2Result<()>,
490    {
491        let start = Instant::now();
492        let mut offset = 0;
493
494        while offset < data.len() {
495            let chunk_end = (offset + self.chunk_size).min(data.len());
496            let chunk = &mut data[offset..chunk_end];
497
498            transfer_fn(chunk, offset)?;
499            offset = chunk_end;
500        }
501
502        Ok(start.elapsed())
503    }
504}
505
506#[cfg(test)]
507mod tests {
508    use super::*;
509
510    #[test]
511    fn test_memory_bandwidth_config_default() {
512        let config = MemoryBandwidthConfig::default();
513        assert!(config.enable_prefetching);
514        assert!(config.enable_coalescing);
515        assert!(config.enable_buffer_pooling);
516        assert!(config.cache_line_size > 0);
517    }
518
519    #[test]
520    fn test_buffer_pool_acquire_release() {
521        let config = MemoryBandwidthConfig::default();
522        let pool = MemoryBufferPool::new(config);
523
524        // Acquire buffer
525        let buffer = pool.acquire(100);
526        assert!(buffer.len() >= 100);
527
528        // Release buffer
529        let size = buffer.len();
530        pool.release(buffer);
531
532        // Acquire again - should get from pool
533        let buffer2 = pool.acquire(100);
534        assert_eq!(buffer2.len(), size);
535
536        let stats = pool.get_statistics();
537        assert!(stats.pool_hit_rate > 0.0);
538    }
539
540    #[test]
541    fn test_memory_layout_computation() {
542        let config = MemoryBandwidthConfig::default();
543        let optimizer = MemoryBandwidthOptimizer::new(config);
544
545        let layout = optimizer.get_optimal_layout(4);
546        assert_eq!(layout.total_elements, 16);
547        assert!(!layout.use_tiled_layout);
548
549        let layout_large = optimizer.get_optimal_layout(12);
550        assert_eq!(layout_large.total_elements, 4096);
551        assert!(layout_large.use_tiled_layout);
552    }
553
554    #[test]
555    fn test_coalesced_access_optimization() {
556        let config = MemoryBandwidthConfig::default();
557        let optimizer = MemoryBandwidthOptimizer::new(config);
558
559        let mut data = vec![Complex64::new(0.0, 0.0); 100];
560        let pattern = vec![50, 10, 30, 70, 90];
561
562        let result = optimizer.optimize_coalesced_access(&mut data, &pattern, |elem, idx| {
563            *elem = Complex64::new(idx as f64, 0.0);
564            Ok(())
565        });
566
567        assert!(result.is_ok());
568        assert_eq!(data[10], Complex64::new(10.0, 0.0));
569        assert_eq!(data[50], Complex64::new(50.0, 0.0));
570    }
571
572    #[test]
573    fn test_transfer_metrics_recording() {
574        let config = MemoryBandwidthConfig::default();
575        let optimizer = MemoryBandwidthOptimizer::new(config);
576
577        optimizer.record_transfer(1024, true, Duration::from_micros(100));
578        optimizer.record_transfer(1024, false, Duration::from_micros(100));
579
580        let metrics = optimizer.get_metrics();
581        assert_eq!(metrics.bytes_to_device, 1024);
582        assert_eq!(metrics.bytes_from_device, 1024);
583        assert_eq!(metrics.transfer_count, 2);
584    }
585
586    #[test]
587    fn test_optimization_recommendations() {
588        let config = MemoryBandwidthConfig::default();
589        let optimizer = MemoryBandwidthOptimizer::new(config);
590
591        let recommendations = optimizer.get_optimization_recommendations();
592        assert!(!recommendations.is_empty());
593    }
594
595    #[test]
596    fn test_streaming_transfer() {
597        let config = MemoryBandwidthConfig::default();
598        let pool = Arc::new(MemoryBufferPool::new(config));
599        let streamer = StreamingTransfer::new(32, pool);
600
601        let data = vec![Complex64::new(1.0, 0.0); 100];
602        let result = streamer.stream_to_device(&data, |_chunk, _offset| Ok(()));
603        assert!(result.is_ok());
604    }
605
606    #[test]
607    fn test_pool_clear() {
608        let config = MemoryBandwidthConfig::default();
609        let pool = MemoryBufferPool::new(config);
610
611        // Acquire and release buffers
612        for _ in 0..10 {
613            let buffer = pool.acquire(100);
614            pool.release(buffer);
615        }
616
617        // Clear pool
618        pool.clear();
619
620        let stats = pool.get_statistics();
621        assert_eq!(stats.allocated_bytes, 0);
622    }
623}