trustformers_debug/
advanced_gpu_profiler.rs

1//! Advanced GPU profiling and kernel optimization tools
2//!
3//! This module provides comprehensive GPU memory analysis, kernel optimization
4//! suggestions, and advanced profiling capabilities for CUDA/ROCm/OpenCL kernels.
5// reason: debug/profiling scaffolding — structs are constructed and their fields/methods
6// are retained for the data model, serialization completeness, and future consumers that
7// do not yet read every member. Consolidated from many item-level #[allow(dead_code)].
8#![allow(dead_code)]
9
10use anyhow::Result;
11use chrono::{DateTime, Utc};
12use serde::{Deserialize, Serialize};
13use std::collections::{HashMap, VecDeque};
14use std::time::{Duration, SystemTime};
15use uuid::Uuid;
16
17/// Advanced GPU memory profiler with fragmentation analysis
18#[derive(Debug)]
19pub struct AdvancedGpuMemoryProfiler {
20    device_count: i32,
21    memory_pools: HashMap<i32, GpuMemoryPool>,
22    memory_allocations: HashMap<Uuid, GpuMemoryAllocation>,
23    fragmentation_history: VecDeque<MemoryFragmentationSnapshot>,
24    bandwidth_monitors: HashMap<i32, GpuBandwidthMonitor>,
25    memory_pressure_monitor: MemoryPressureMonitor,
26    cross_device_transfers: Vec<CrossDeviceTransfer>,
27}
28
29/// GPU memory allocation with detailed tracking
30#[derive(Debug, Clone, Serialize, Deserialize)]
31pub struct GpuMemoryAllocation {
32    pub allocation_id: Uuid,
33    pub device_id: i32,
34    pub size_bytes: usize,
35    pub alignment: usize,
36    pub memory_type: GpuMemoryType,
37    pub allocation_context: AllocationContext,
38    pub timestamp: SystemTime,
39    pub freed: bool,
40    pub free_timestamp: Option<SystemTime>,
41    pub access_pattern: MemoryAccessPattern,
42    pub usage_statistics: MemoryUsageStats,
43}
44
45#[derive(Debug, Clone, Serialize, Deserialize)]
46pub enum GpuMemoryType {
47    Global,
48    Shared,
49    Constant,
50    Texture,
51    Local,
52    Unified,
53    Pinned,
54}
55
56#[derive(Debug, Clone, Serialize, Deserialize)]
57pub struct AllocationContext {
58    pub kernel_name: Option<String>,
59    pub tensor_name: Option<String>,
60    pub layer_name: Option<String>,
61    pub allocation_source: AllocationSource,
62    pub stack_trace: Vec<String>,
63}
64
65#[derive(Debug, Clone, Serialize, Deserialize)]
66pub enum AllocationSource {
67    TensorCreation,
68    KernelLaunch,
69    IntermediateBuffer,
70    GradientBuffer,
71    WeightBuffer,
72    ActivationBuffer,
73    CacheBuffer,
74}
75
76#[derive(Debug, Clone, Serialize, Deserialize)]
77pub struct MemoryAccessPattern {
78    pub access_frequency: f64,
79    pub read_ratio: f64,
80    pub write_ratio: f64,
81    pub sequential_access_ratio: f64,
82    pub random_access_ratio: f64,
83    pub coalesced_access_ratio: f64,
84    pub cache_hit_rate: f64,
85}
86
87#[derive(Debug, Clone, Serialize, Deserialize, Default)]
88pub struct MemoryUsageStats {
89    pub total_accesses: u64,
90    pub bytes_read: u64,
91    pub bytes_written: u64,
92    pub lifetime_duration: Option<Duration>,
93    pub peak_concurrent_usage: usize,
94}
95
96/// Memory fragmentation analysis
97#[derive(Debug, Clone, Serialize, Deserialize)]
98pub struct MemoryFragmentationSnapshot {
99    pub timestamp: DateTime<Utc>,
100    pub device_id: i32,
101    pub total_memory: usize,
102    pub free_memory: usize,
103    pub largest_free_block: usize,
104    pub fragmentation_ratio: f64,
105    pub free_block_distribution: Vec<usize>,
106    pub external_fragmentation: f64,
107    pub internal_fragmentation: f64,
108}
109
110/// GPU bandwidth monitoring
111#[derive(Debug)]
112pub struct GpuBandwidthMonitor {
113    device_id: i32,
114    bandwidth_samples: VecDeque<BandwidthSample>,
115    theoretical_bandwidth: f64, // GB/s
116    peak_observed_bandwidth: f64,
117    sustained_bandwidth_history: Vec<SustainedBandwidthMeasurement>,
118}
119
120#[derive(Debug, Clone, Serialize, Deserialize)]
121pub struct BandwidthSample {
122    pub timestamp: SystemTime,
123    pub memory_type: GpuMemoryType,
124    pub operation_type: MemoryOperationType,
125    pub bytes_transferred: usize,
126    pub duration: Duration,
127    pub achieved_bandwidth_gb_s: f64,
128    pub efficiency_percentage: f64,
129}
130
131#[derive(Debug, Clone, Serialize, Deserialize)]
132pub enum MemoryOperationType {
133    HostToDevice,
134    DeviceToHost,
135    DeviceToDevice,
136    KernelMemoryAccess,
137    PeerToPeer,
138}
139
140#[derive(Debug, Clone, Serialize, Deserialize)]
141pub struct SustainedBandwidthMeasurement {
142    pub duration: Duration,
143    pub avg_bandwidth_gb_s: f64,
144    pub min_bandwidth_gb_s: f64,
145    pub max_bandwidth_gb_s: f64,
146    pub bandwidth_variability: f64,
147}
148
149/// Memory pressure monitoring
150#[derive(Debug)]
151pub struct MemoryPressureMonitor {
152    pressure_history: VecDeque<MemoryPressureSnapshot>,
153    pressure_thresholds: MemoryPressureThresholds,
154    auto_optimization_enabled: bool,
155}
156
157#[derive(Debug, Clone, Serialize, Deserialize)]
158pub struct MemoryPressureSnapshot {
159    pub timestamp: DateTime<Utc>,
160    pub device_id: i32,
161    pub pressure_level: MemoryPressureLevel,
162    pub available_memory_ratio: f64,
163    pub allocation_rate: f64, // allocations per second
164    pub deallocation_rate: f64,
165    pub gc_pressure: f64,
166    pub swap_activity: f64,
167}
168
169#[derive(Debug, Clone, Serialize, Deserialize)]
170pub enum MemoryPressureLevel {
171    Low,
172    Medium,
173    High,
174    Critical,
175}
176
177#[derive(Debug, Clone, Serialize, Deserialize)]
178pub struct MemoryPressureThresholds {
179    pub medium_threshold: f64, // 0.7 = 70% memory usage triggers medium pressure
180    pub high_threshold: f64,   // 0.85 = 85% memory usage triggers high pressure
181    pub critical_threshold: f64, // 0.95 = 95% memory usage triggers critical pressure
182}
183
184/// Cross-device memory transfer tracking
185#[derive(Debug, Clone, Serialize, Deserialize)]
186pub struct CrossDeviceTransfer {
187    pub transfer_id: Uuid,
188    pub source_device: i32,
189    pub target_device: i32,
190    pub bytes_transferred: usize,
191    pub transfer_type: CrossDeviceTransferType,
192    pub duration: Duration,
193    pub bandwidth_achieved: f64,
194    pub p2p_enabled: bool,
195    pub timestamp: SystemTime,
196}
197
198#[derive(Debug, Clone, Serialize, Deserialize)]
199pub enum CrossDeviceTransferType {
200    DirectMemoryAccess,
201    PeerToPeer,
202    HostBounced,
203    NvLink,
204    Infinity,
205}
206
207#[derive(Debug, Clone, Serialize, Deserialize)]
208pub struct KernelExecutionProfile {
209    pub kernel_name: String,
210    pub execution_count: usize,
211    pub total_execution_time: Duration,
212    pub avg_execution_time: Duration,
213    pub min_execution_time: Duration,
214    pub max_execution_time: Duration,
215    pub grid_sizes: Vec<(u32, u32, u32)>,
216    pub block_sizes: Vec<(u32, u32, u32)>,
217    pub shared_memory_usage: Vec<usize>,
218    pub register_usage: Vec<u32>,
219    pub occupancy_measurements: Vec<f64>,
220    pub compute_utilization: Vec<f64>,
221    pub memory_bandwidth_utilization: Vec<f64>,
222    pub warp_efficiency: Vec<f64>,
223    pub memory_efficiency: Vec<f64>,
224}
225
226#[derive(Debug, Clone, Serialize, Deserialize)]
227pub struct KernelOptimization {
228    pub optimization_type: OptimizationType,
229    pub current_value: OptimizationValue,
230    pub suggested_value: OptimizationValue,
231    pub expected_improvement: ExpectedImprovement,
232    pub confidence: f64,
233    pub explanation: String,
234    pub implementation_difficulty: ImplementationDifficulty,
235}
236
237#[derive(Debug, Clone, Serialize, Deserialize)]
238pub enum OptimizationType {
239    BlockSize,
240    GridSize,
241    SharedMemory,
242    RegisterOptimization,
243    MemoryCoalescing,
244    WarpDivergence,
245    KernelFusion,
246    MemoryLayoutOptimization,
247    ComputeIntensityBalance,
248}
249
250#[derive(Debug, Clone, Serialize, Deserialize)]
251pub enum OptimizationValue {
252    IntegerValue(u32),
253    FloatValue(f64),
254    TupleValue((u32, u32, u32)),
255    LayoutPattern(String),
256    BooleanValue(bool),
257}
258
259#[derive(Debug, Clone, Serialize, Deserialize)]
260pub struct ExpectedImprovement {
261    pub performance_gain_percentage: f64,
262    pub memory_usage_reduction_percentage: f64,
263    pub energy_efficiency_improvement: f64,
264    pub scalability_improvement: f64,
265}
266
267#[derive(Debug, Clone, Serialize, Deserialize)]
268pub enum ImplementationDifficulty {
269    Trivial,
270    Easy,
271    Moderate,
272    Difficult,
273    Expert,
274}
275
276/// Launch configuration analysis
277#[derive(Debug)]
278pub struct LaunchConfigAnalyzer {
279    optimal_configs: HashMap<String, OptimalLaunchConfig>,
280    config_performance_history: HashMap<String, Vec<ConfigPerformanceMeasurement>>,
281    autotuning_enabled: bool,
282    search_space_cache: HashMap<String, LaunchConfigSearchSpace>,
283}
284
285#[derive(Debug, Clone, Serialize, Deserialize)]
286pub struct LaunchConfigSearchSpace {
287    pub kernel_name: String,
288    pub min_block_size: (u32, u32, u32),
289    pub max_block_size: (u32, u32, u32),
290    pub min_grid_size: (u32, u32, u32),
291    pub max_grid_size: (u32, u32, u32),
292    pub min_shared_memory: usize,
293    pub max_shared_memory: usize,
294    pub search_constraints: Vec<LaunchConstraint>,
295}
296
297#[derive(Debug, Clone, Serialize, Deserialize)]
298pub struct OptimalLaunchConfig {
299    pub kernel_name: String,
300    pub optimal_block_size: (u32, u32, u32),
301    pub optimal_grid_size: (u32, u32, u32),
302    pub optimal_shared_memory: usize,
303    pub expected_occupancy: f64,
304    pub expected_performance: f64,
305    pub constraints: Vec<LaunchConstraint>,
306}
307
308#[derive(Debug, Clone, Serialize, Deserialize)]
309pub struct ConfigPerformanceMeasurement {
310    pub block_size: (u32, u32, u32),
311    pub grid_size: (u32, u32, u32),
312    pub shared_memory: usize,
313    pub achieved_occupancy: f64,
314    pub execution_time: Duration,
315    pub memory_bandwidth: f64,
316    pub compute_utilization: f64,
317    pub timestamp: SystemTime,
318}
319
320#[derive(Debug, Clone, Serialize, Deserialize)]
321pub enum LaunchConstraint {
322    MaxSharedMemory(usize),
323    MaxRegisters(u32),
324    MinOccupancy(f64),
325    WorkgroupSizeLimit(u32),
326    MemoryBandwidthLimit(f64),
327}
328
329/// Memory access pattern analysis
330#[derive(Debug)]
331pub struct MemoryAccessAnalyzer {
332    access_patterns: HashMap<String, MemoryAccessAnalysis>,
333    coalescing_analysis: HashMap<String, CoalescingAnalysis>,
334    cache_performance: HashMap<String, CachePerformanceAnalysis>,
335    stride_analysis: HashMap<String, StrideAnalysisResult>,
336    bank_conflict_analyzer: BankConflictAnalyzer,
337}
338
339#[derive(Debug, Clone, Serialize, Deserialize)]
340pub struct StrideAnalysisResult {
341    pub kernel_name: String,
342    pub average_stride: f64,
343    pub stride_pattern: StridePattern,
344    pub optimization_potential: f64,
345    pub recommended_changes: Vec<String>,
346}
347
348#[derive(Debug, Clone, Serialize, Deserialize)]
349pub enum StridePattern {
350    Sequential,
351    Strided(i32),
352    Random,
353    Broadcast,
354}
355
356#[derive(Debug)]
357pub struct BankConflictAnalyzer {
358    conflict_patterns: HashMap<String, BankConflictPattern>,
359    resolution_strategies: HashMap<String, Vec<ConflictResolutionStrategy>>,
360}
361
362#[derive(Debug, Clone, Serialize, Deserialize)]
363pub struct BankConflictPattern {
364    pub kernel_name: String,
365    pub conflicts_detected: usize,
366    pub conflict_severity: ConflictSeverity,
367    pub affected_warps: Vec<u32>,
368}
369
370#[derive(Debug, Clone, Serialize, Deserialize)]
371pub enum ConflictSeverity {
372    Low,
373    Medium,
374    High,
375    Critical,
376}
377
378#[derive(Debug, Clone, Serialize, Deserialize)]
379pub struct ConflictResolutionStrategy {
380    pub strategy_type: ResolutionStrategyType,
381    pub description: String,
382    pub expected_improvement: f64,
383}
384
385#[derive(Debug, Clone, Serialize, Deserialize)]
386pub enum ResolutionStrategyType {
387    DataPadding,
388    AccessReordering,
389    SharedMemoryBanking,
390    AlgorithmicChange,
391}
392
393#[derive(Debug, Clone, Serialize, Deserialize)]
394pub struct MemoryAccessAnalysis {
395    pub kernel_name: String,
396    pub total_memory_transactions: u64,
397    pub coalesced_transactions: u64,
398    pub uncoalesced_transactions: u64,
399    pub stride_patterns: Vec<StridePattern>,
400    pub access_locality: AccessLocalityMetrics,
401    pub bank_conflicts: u64,
402    pub cache_line_utilization: f64,
403}
404
405#[derive(Debug, Clone, Serialize, Deserialize)]
406pub struct DetectedStride {
407    pub stride_size: usize,
408    pub frequency: u64,
409    pub efficiency_impact: f64,
410}
411
412#[derive(Debug, Clone, Serialize, Deserialize)]
413pub struct AccessLocalityMetrics {
414    pub temporal_locality_score: f64,
415    pub spatial_locality_score: f64,
416    pub working_set_size: usize,
417    pub reuse_distance_avg: f64,
418}
419
420#[derive(Debug, Clone, Serialize, Deserialize)]
421pub struct CoalescingAnalysis {
422    pub kernel_name: String,
423    pub coalescing_efficiency: f64,
424    pub uncoalesced_regions: Vec<UncoalescedRegion>,
425    pub suggested_improvements: Vec<CoalescingImprovement>,
426}
427
428#[derive(Debug, Clone, Serialize, Deserialize)]
429pub struct UncoalescedRegion {
430    pub memory_region: String,
431    pub access_pattern: String,
432    pub efficiency_loss: f64,
433    pub fix_difficulty: ImplementationDifficulty,
434}
435
436#[derive(Debug, Clone, Serialize, Deserialize)]
437pub struct CoalescingImprovement {
438    pub improvement_type: CoalescingImprovementType,
439    pub description: String,
440    pub expected_speedup: f64,
441}
442
443#[derive(Debug, Clone, Serialize, Deserialize)]
444pub enum CoalescingImprovementType {
445    DataLayoutReorganization,
446    AccessPatternOptimization,
447    SharedMemoryBuffering,
448    VectorizedAccess,
449}
450
451#[derive(Debug, Clone, Serialize, Deserialize)]
452pub struct CachePerformanceAnalysis {
453    pub kernel_name: String,
454    pub l1_cache_hit_rate: f64,
455    pub l2_cache_hit_rate: f64,
456    pub texture_cache_hit_rate: f64,
457    pub shared_memory_bank_conflicts: u64,
458    pub cache_thrashing_detected: bool,
459    pub recommended_cache_optimizations: Vec<CacheOptimization>,
460}
461
462#[derive(Debug, Clone, Serialize, Deserialize)]
463pub struct CacheOptimization {
464    pub optimization_type: CacheOptimizationType,
465    pub description: String,
466    pub expected_improvement: f64,
467}
468
469#[derive(Debug, Clone, Serialize, Deserialize)]
470pub enum CacheOptimizationType {
471    DataPrefetching,
472    CacheBlockingStrategy,
473    SharedMemoryUsage,
474    TextureMemoryUsage,
475    ConstantMemoryUsage,
476}
477
478/// Compute utilization analysis
479#[derive(Debug)]
480pub struct ComputeUtilizationAnalyzer {
481    utilization_profiles: HashMap<String, ComputeUtilizationProfile>,
482    bottleneck_analysis: HashMap<String, ComputeBottleneckAnalysis>,
483    arithmetic_intensity_analyzer: ArithmeticIntensityAnalyzer,
484    resource_balancer: ResourceBalancer,
485}
486
487#[derive(Debug)]
488pub struct ArithmeticIntensityAnalyzer {
489    intensity_profiles: HashMap<String, ArithmeticIntensityProfile>,
490    roofline_models: HashMap<i32, RooflineModel>,
491}
492
493#[derive(Debug, Clone, Serialize, Deserialize)]
494pub struct ArithmeticIntensityProfile {
495    pub kernel_name: String,
496    pub arithmetic_intensity: f64,
497    pub operations_per_byte: f64,
498    pub peak_performance_percentage: f64,
499}
500
501#[derive(Debug, Clone, Serialize, Deserialize)]
502pub struct RooflineModel {
503    pub device_id: i32,
504    pub peak_compute_flops: f64,
505    pub peak_memory_bandwidth: f64,
506    pub ridge_point: f64,
507}
508
509#[derive(Debug)]
510pub struct ResourceBalancer {
511    resource_profiles: HashMap<String, ResourceProfile>,
512    balancing_strategies: HashMap<String, BalancingStrategy>,
513}
514
515#[derive(Debug, Clone, Serialize, Deserialize)]
516pub struct ResourceProfile {
517    pub kernel_name: String,
518    pub register_usage: f64,
519    pub shared_memory_usage: f64,
520    pub occupancy: f64,
521    pub limiting_factor: LimitingFactor,
522}
523
524#[derive(Debug, Clone, Serialize, Deserialize)]
525pub enum LimitingFactor {
526    Registers,
527    SharedMemory,
528    Blocks,
529    Warps,
530}
531
532#[derive(Debug, Clone, Serialize, Deserialize)]
533pub struct BalancingStrategy {
534    pub strategy_name: String,
535    pub description: String,
536    pub expected_improvement: f64,
537    pub trade_offs: Vec<String>,
538}
539
540#[derive(Debug, Clone, Serialize, Deserialize)]
541pub struct ComputeUtilizationProfile {
542    pub kernel_name: String,
543    pub arithmetic_intensity: f64,
544    pub compute_throughput: f64,
545    pub memory_throughput: f64,
546    pub compute_to_memory_ratio: f64,
547    pub warp_execution_efficiency: f64,
548    pub instruction_mix: InstructionMixAnalysis,
549    pub resource_utilization: ResourceUtilizationMetrics,
550}
551
552#[derive(Debug, Clone, Serialize, Deserialize)]
553pub struct InstructionMixAnalysis {
554    pub integer_ops_percentage: f64,
555    pub float_ops_percentage: f64,
556    pub double_ops_percentage: f64,
557    pub special_function_ops_percentage: f64,
558    pub memory_ops_percentage: f64,
559    pub control_flow_ops_percentage: f64,
560}
561
562#[derive(Debug, Clone, Serialize, Deserialize)]
563pub struct ResourceUtilizationMetrics {
564    pub register_utilization: f64,
565    pub shared_memory_utilization: f64,
566    pub constant_memory_utilization: f64,
567    pub texture_cache_utilization: f64,
568    pub compute_unit_utilization: f64,
569}
570
571#[derive(Debug, Clone, Serialize, Deserialize)]
572pub struct ComputeBottleneckAnalysis {
573    pub kernel_name: String,
574    pub primary_bottleneck: ComputeBottleneckType,
575    pub bottleneck_severity: f64,
576    pub contributing_factors: Vec<BottleneckFactor>,
577    pub optimization_opportunities: Vec<ComputeOptimizationOpportunity>,
578}
579
580#[derive(Debug, Clone, Serialize, Deserialize)]
581pub enum ComputeBottleneckType {
582    MemoryBandwidth,
583    ComputeThroughput,
584    Latency,
585    Occupancy,
586    WarpDivergence,
587    SynchronizationOverhead,
588}
589
590#[derive(Debug, Clone, Serialize, Deserialize)]
591pub struct BottleneckFactor {
592    pub factor_type: String,
593    pub impact_percentage: f64,
594    pub description: String,
595}
596
597#[derive(Debug, Clone, Serialize, Deserialize)]
598pub struct ComputeOptimizationOpportunity {
599    pub opportunity_type: ComputeOptimizationType,
600    pub description: String,
601    pub expected_speedup: f64,
602    pub implementation_effort: ImplementationDifficulty,
603}
604
605#[derive(Debug, Clone, Serialize, Deserialize)]
606pub enum ComputeOptimizationType {
607    KernelFusion,
608    MemoryOptimization,
609    ParallelismIncrease,
610    AlgorithmicImprovement,
611    ResourceBalancing,
612}
613
614impl AdvancedGpuMemoryProfiler {
615    pub fn new(device_count: i32) -> Result<Self> {
616        let mut memory_pools = HashMap::new();
617        let mut bandwidth_monitors = HashMap::new();
618
619        for device_id in 0..device_count {
620            memory_pools.insert(device_id, GpuMemoryPool::new(device_id)?);
621            bandwidth_monitors.insert(device_id, GpuBandwidthMonitor::new(device_id)?);
622        }
623
624        Ok(Self {
625            device_count,
626            memory_pools,
627            memory_allocations: HashMap::new(),
628            fragmentation_history: VecDeque::with_capacity(1000),
629            bandwidth_monitors,
630            memory_pressure_monitor: MemoryPressureMonitor::new(),
631            cross_device_transfers: Vec::new(),
632        })
633    }
634
635    /// Track a GPU memory allocation with detailed context
636    pub fn track_allocation(
637        &mut self,
638        device_id: i32,
639        size_bytes: usize,
640        memory_type: GpuMemoryType,
641        context: AllocationContext,
642    ) -> Result<Uuid> {
643        let allocation_id = Uuid::new_v4();
644        let allocation = GpuMemoryAllocation {
645            allocation_id,
646            device_id,
647            size_bytes,
648            alignment: self.calculate_optimal_alignment(size_bytes),
649            memory_type,
650            allocation_context: context,
651            timestamp: SystemTime::now(),
652            freed: false,
653            free_timestamp: None,
654            access_pattern: MemoryAccessPattern::default(),
655            usage_statistics: MemoryUsageStats::default(),
656        };
657
658        // Update memory pool
659        if let Some(pool) = self.memory_pools.get_mut(&device_id) {
660            pool.allocate(size_bytes)?;
661        }
662
663        self.memory_allocations.insert(allocation_id, allocation);
664
665        // Check for memory pressure
666        self.update_memory_pressure(device_id);
667
668        Ok(allocation_id)
669    }
670
671    /// Track memory deallocation
672    pub fn track_deallocation(&mut self, allocation_id: Uuid) -> Result<()> {
673        let device_id = if let Some(allocation) = self.memory_allocations.get_mut(&allocation_id) {
674            allocation.freed = true;
675            allocation.free_timestamp = Some(SystemTime::now());
676
677            // Get the device_id and size_bytes before dropping the mutable reference
678            let device_id = allocation.device_id;
679            let size_bytes = allocation.size_bytes;
680
681            // Update memory pool
682            if let Some(pool) = self.memory_pools.get_mut(&device_id) {
683                pool.deallocate(size_bytes)?;
684            }
685
686            Some(device_id)
687        } else {
688            None
689        };
690
691        // Update memory pressure after dropping the mutable reference
692        if let Some(device_id) = device_id {
693            self.update_memory_pressure(device_id);
694        }
695
696        Ok(())
697    }
698
699    /// Analyze memory fragmentation across all devices
700    pub fn analyze_fragmentation(&mut self) -> Result<Vec<MemoryFragmentationSnapshot>> {
701        let mut snapshots = Vec::new();
702
703        for (&_device_id, pool) in &self.memory_pools {
704            let snapshot = pool.get_fragmentation_snapshot()?;
705            snapshots.push(snapshot.clone());
706
707            // Store in history
708            self.fragmentation_history.push_back(snapshot);
709            if self.fragmentation_history.len() > 1000 {
710                self.fragmentation_history.pop_front();
711            }
712        }
713
714        Ok(snapshots)
715    }
716
717    /// Monitor memory bandwidth utilization
718    pub fn record_bandwidth_sample(
719        &mut self,
720        device_id: i32,
721        sample: BandwidthSample,
722    ) -> Result<()> {
723        if let Some(monitor) = self.bandwidth_monitors.get_mut(&device_id) {
724            monitor.add_sample(sample)?;
725        }
726        Ok(())
727    }
728
729    /// Track cross-device memory transfer
730    pub fn track_cross_device_transfer(
731        &mut self,
732        source_device: i32,
733        target_device: i32,
734        bytes_transferred: usize,
735        transfer_type: CrossDeviceTransferType,
736        duration: Duration,
737    ) -> Result<Uuid> {
738        let transfer_id = Uuid::new_v4();
739        let bandwidth_achieved =
740            bytes_transferred as f64 / (1024.0 * 1024.0 * 1024.0) / duration.as_secs_f64();
741
742        let transfer = CrossDeviceTransfer {
743            transfer_id,
744            source_device,
745            target_device,
746            bytes_transferred,
747            transfer_type,
748            duration,
749            bandwidth_achieved,
750            p2p_enabled: self.detect_p2p_capability(source_device, target_device),
751            timestamp: SystemTime::now(),
752        };
753
754        self.cross_device_transfers.push(transfer);
755        Ok(transfer_id)
756    }
757
758    /// Get comprehensive memory analysis report
759    pub fn get_memory_analysis_report(&self) -> MemoryAnalysisReport {
760        let fragmentation_summary = self.analyze_fragmentation_trends();
761        let bandwidth_summary = self.analyze_bandwidth_utilization();
762        let pressure_summary = self.analyze_memory_pressure();
763        let allocation_summary = self.analyze_allocation_patterns();
764        let cross_device_summary = self.analyze_cross_device_transfers();
765
766        MemoryAnalysisReport {
767            fragmentation_summary,
768            bandwidth_summary,
769            pressure_summary,
770            allocation_summary,
771            cross_device_summary,
772            optimization_recommendations: self.generate_memory_optimization_recommendations(),
773        }
774    }
775
776    fn calculate_optimal_alignment(&self, size_bytes: usize) -> usize {
777        // Calculate optimal memory alignment for GPU access
778        if size_bytes >= 128 {
779            128 // Cache line alignment
780        } else if size_bytes >= 64 {
781            64
782        } else if size_bytes >= 32 {
783            32
784        } else {
785            16
786        }
787    }
788
789    fn update_memory_pressure(&mut self, device_id: i32) {
790        if let Some(pool) = self.memory_pools.get(&device_id) {
791            let pressure_snapshot = MemoryPressureSnapshot {
792                timestamp: Utc::now(),
793                device_id,
794                pressure_level: pool.calculate_pressure_level(),
795                available_memory_ratio: pool.get_available_memory_ratio(),
796                allocation_rate: self.calculate_allocation_rate(device_id),
797                deallocation_rate: self.calculate_deallocation_rate(device_id),
798                gc_pressure: 0.0,   // Simplified
799                swap_activity: 0.0, // Simplified
800            };
801
802            self.memory_pressure_monitor.add_snapshot(pressure_snapshot);
803        }
804    }
805
806    fn detect_p2p_capability(&self, _source: i32, _target: i32) -> bool {
807        // Simplified P2P detection - would use actual GPU capabilities
808        true
809    }
810
811    fn calculate_allocation_rate(&self, device_id: i32) -> f64 {
812        // Calculate allocations per second for the device
813        let recent_allocations = self
814            .memory_allocations
815            .values()
816            .filter(|a| a.device_id == device_id)
817            .filter(|a| a.timestamp.elapsed().unwrap_or_default().as_secs() < 60)
818            .count();
819
820        recent_allocations as f64 / 60.0
821    }
822
823    fn calculate_deallocation_rate(&self, device_id: i32) -> f64 {
824        // Calculate deallocations per second for the device
825        let recent_deallocations = self
826            .memory_allocations
827            .values()
828            .filter(|a| a.device_id == device_id && a.freed)
829            .filter(|a| {
830                if let Some(free_time) = a.free_timestamp {
831                    free_time.elapsed().unwrap_or_default().as_secs() < 60
832                } else {
833                    false
834                }
835            })
836            .count();
837
838        recent_deallocations as f64 / 60.0
839    }
840
841    fn analyze_fragmentation_trends(&self) -> FragmentationSummary {
842        // Analyze fragmentation trends from history
843        FragmentationSummary::new(&self.fragmentation_history)
844    }
845
846    fn analyze_bandwidth_utilization(&self) -> BandwidthSummary {
847        BandwidthSummary::new(&self.bandwidth_monitors)
848    }
849
850    fn analyze_memory_pressure(&self) -> MemoryPressureSummary {
851        self.memory_pressure_monitor.get_summary()
852    }
853
854    fn analyze_allocation_patterns(&self) -> AllocationPatternSummary {
855        AllocationPatternSummary::new(&self.memory_allocations)
856    }
857
858    fn analyze_cross_device_transfers(&self) -> CrossDeviceTransferSummary {
859        CrossDeviceTransferSummary::new(&self.cross_device_transfers)
860    }
861
862    fn generate_memory_optimization_recommendations(
863        &self,
864    ) -> Vec<MemoryOptimizationRecommendation> {
865        let mut recommendations = Vec::new();
866
867        // Analyze fragmentation and suggest optimizations
868        for snapshot in self.fragmentation_history.iter().take(10) {
869            if snapshot.fragmentation_ratio > 0.3 {
870                recommendations.push(MemoryOptimizationRecommendation {
871                    recommendation_type: MemoryOptimizationType::DefragmentationStrategy,
872                    priority: OptimizationPriority::High,
873                    description: format!(
874                        "High fragmentation detected on device {}: {:.1}%",
875                        snapshot.device_id,
876                        snapshot.fragmentation_ratio * 100.0
877                    ),
878                    expected_benefit: ExpectedBenefit {
879                        performance_improvement: 15.0,
880                        memory_efficiency_improvement: 25.0,
881                        implementation_effort: ImplementationDifficulty::Moderate,
882                    },
883                    implementation_steps: vec![
884                        "Implement memory pooling with fixed-size blocks".to_string(),
885                        "Add periodic defragmentation during idle periods".to_string(),
886                        "Consider memory compaction strategies".to_string(),
887                    ],
888                });
889            }
890        }
891
892        recommendations
893    }
894}
895
896// Helper structures for analysis reports
897
898#[derive(Debug, Clone, Serialize, Deserialize)]
899pub struct MemoryAnalysisReport {
900    pub fragmentation_summary: FragmentationSummary,
901    pub bandwidth_summary: BandwidthSummary,
902    pub pressure_summary: MemoryPressureSummary,
903    pub allocation_summary: AllocationPatternSummary,
904    pub cross_device_summary: CrossDeviceTransferSummary,
905    pub optimization_recommendations: Vec<MemoryOptimizationRecommendation>,
906}
907
908#[derive(Debug, Clone, Serialize, Deserialize)]
909pub struct FragmentationSummary {
910    pub avg_fragmentation_ratio: f64,
911    pub peak_fragmentation_ratio: f64,
912    pub fragmentation_trend: FragmentationTrend,
913    pub most_fragmented_device: i32,
914}
915
916#[derive(Debug, Clone, Serialize, Deserialize)]
917pub enum FragmentationTrend {
918    Improving,
919    Stable,
920    Worsening,
921}
922
923#[derive(Debug, Clone, Serialize, Deserialize)]
924pub struct BandwidthSummary {
925    pub avg_bandwidth_utilization: f64,
926    pub peak_bandwidth_achieved: f64,
927    pub bandwidth_efficiency_by_operation: HashMap<String, f64>,
928    pub underutilized_devices: Vec<i32>,
929}
930
931#[derive(Debug, Clone, Serialize, Deserialize)]
932pub struct MemoryPressureSummary {
933    pub current_pressure_levels: HashMap<i32, MemoryPressureLevel>,
934    pub pressure_trend: PressureTrend,
935    pub devices_under_pressure: Vec<i32>,
936    pub time_in_high_pressure: Duration,
937}
938
939#[derive(Debug, Clone, Serialize, Deserialize)]
940pub enum PressureTrend {
941    Decreasing,
942    Stable,
943    Increasing,
944}
945
946#[derive(Debug, Clone, Serialize, Deserialize)]
947pub struct AllocationPatternSummary {
948    pub total_allocations: usize,
949    pub avg_allocation_size: usize,
950    pub largest_allocation: usize,
951    pub allocation_size_distribution: HashMap<String, usize>,
952    pub memory_leaks_detected: usize,
953    pub allocation_hot_spots: Vec<AllocationHotSpot>,
954}
955
956#[derive(Debug, Clone, Serialize, Deserialize)]
957pub struct AllocationHotSpot {
958    pub location: String,
959    pub allocation_frequency: f64,
960    pub total_memory_allocated: usize,
961    pub avg_allocation_lifetime: Duration,
962}
963
964#[derive(Debug, Clone, Serialize, Deserialize)]
965pub struct CrossDeviceTransferSummary {
966    pub total_transfers: usize,
967    pub total_bytes_transferred: usize,
968    pub avg_transfer_bandwidth: f64,
969    pub p2p_efficiency: f64,
970    pub transfer_bottlenecks: Vec<TransferBottleneck>,
971}
972
973#[derive(Debug, Clone, Serialize, Deserialize)]
974pub struct TransferBottleneck {
975    pub device_pair: (i32, i32),
976    pub bottleneck_type: TransferBottleneckType,
977    pub impact_severity: f64,
978}
979
980#[derive(Debug, Clone, Serialize, Deserialize)]
981pub enum TransferBottleneckType {
982    BandwidthLimited,
983    LatencyBound,
984    SynchronizationOverhead,
985    P2PNotAvailable,
986}
987
988#[derive(Debug, Clone, Serialize, Deserialize)]
989pub struct MemoryOptimizationRecommendation {
990    pub recommendation_type: MemoryOptimizationType,
991    pub priority: OptimizationPriority,
992    pub description: String,
993    pub expected_benefit: ExpectedBenefit,
994    pub implementation_steps: Vec<String>,
995}
996
997#[derive(Debug, Clone, Serialize, Deserialize)]
998pub enum MemoryOptimizationType {
999    DefragmentationStrategy,
1000    MemoryPoolingOptimization,
1001    AllocationPatternOptimization,
1002    CrossDeviceTransferOptimization,
1003    PressureReliefStrategy,
1004}
1005
1006#[derive(Debug, Clone, Serialize, Deserialize)]
1007pub enum OptimizationPriority {
1008    Critical,
1009    High,
1010    Medium,
1011    Low,
1012}
1013
1014#[derive(Debug, Clone, Serialize, Deserialize)]
1015pub struct ExpectedBenefit {
1016    pub performance_improvement: f64,
1017    pub memory_efficiency_improvement: f64,
1018    pub implementation_effort: ImplementationDifficulty,
1019}
1020
1021// Default implementations for helper structures
1022
1023impl Default for MemoryAccessPattern {
1024    fn default() -> Self {
1025        Self {
1026            access_frequency: 0.0,
1027            read_ratio: 0.5,
1028            write_ratio: 0.5,
1029            sequential_access_ratio: 0.8,
1030            random_access_ratio: 0.2,
1031            coalesced_access_ratio: 0.9,
1032            cache_hit_rate: 0.85,
1033        }
1034    }
1035}
1036
1037// Implementation stubs for remaining structures
1038
1039impl GpuMemoryPool {
1040    fn new(device_id: i32) -> Result<Self> {
1041        // Simplified implementation - would query actual GPU memory
1042        Ok(Self {
1043            device_id,
1044            total_memory: 8 * 1024 * 1024 * 1024, // 8GB
1045            free_memory: 8 * 1024 * 1024 * 1024,
1046            fragmentation_score: 0.0,
1047        })
1048    }
1049
1050    fn allocate(&mut self, size: usize) -> Result<()> {
1051        if self.free_memory >= size {
1052            self.free_memory -= size;
1053            Ok(())
1054        } else {
1055            Err(anyhow::anyhow!("Insufficient memory"))
1056        }
1057    }
1058
1059    fn deallocate(&mut self, size: usize) -> Result<()> {
1060        self.free_memory += size;
1061        Ok(())
1062    }
1063
1064    fn get_fragmentation_snapshot(&self) -> Result<MemoryFragmentationSnapshot> {
1065        Ok(MemoryFragmentationSnapshot {
1066            timestamp: Utc::now(),
1067            device_id: self.device_id,
1068            total_memory: self.total_memory,
1069            free_memory: self.free_memory,
1070            largest_free_block: self.free_memory, // Simplified
1071            fragmentation_ratio: self.fragmentation_score,
1072            free_block_distribution: vec![self.free_memory],
1073            external_fragmentation: self.fragmentation_score * 0.7,
1074            internal_fragmentation: self.fragmentation_score * 0.3,
1075        })
1076    }
1077
1078    fn calculate_pressure_level(&self) -> MemoryPressureLevel {
1079        let usage_ratio = 1.0 - (self.free_memory as f64 / self.total_memory as f64);
1080
1081        if usage_ratio > 0.95 {
1082            MemoryPressureLevel::Critical
1083        } else if usage_ratio > 0.85 {
1084            MemoryPressureLevel::High
1085        } else if usage_ratio > 0.70 {
1086            MemoryPressureLevel::Medium
1087        } else {
1088            MemoryPressureLevel::Low
1089        }
1090    }
1091
1092    fn get_available_memory_ratio(&self) -> f64 {
1093        self.free_memory as f64 / self.total_memory as f64
1094    }
1095}
1096
1097impl GpuBandwidthMonitor {
1098    fn new(device_id: i32) -> Result<Self> {
1099        Ok(Self {
1100            device_id,
1101            bandwidth_samples: VecDeque::with_capacity(1000),
1102            theoretical_bandwidth: 900.0, // GB/s for high-end GPU
1103            peak_observed_bandwidth: 0.0,
1104            sustained_bandwidth_history: Vec::new(),
1105        })
1106    }
1107
1108    fn add_sample(&mut self, sample: BandwidthSample) -> Result<()> {
1109        if sample.achieved_bandwidth_gb_s > self.peak_observed_bandwidth {
1110            self.peak_observed_bandwidth = sample.achieved_bandwidth_gb_s;
1111        }
1112
1113        self.bandwidth_samples.push_back(sample);
1114        if self.bandwidth_samples.len() > 1000 {
1115            self.bandwidth_samples.pop_front();
1116        }
1117
1118        Ok(())
1119    }
1120}
1121
1122impl MemoryPressureMonitor {
1123    fn new() -> Self {
1124        Self {
1125            pressure_history: VecDeque::with_capacity(1000),
1126            pressure_thresholds: MemoryPressureThresholds {
1127                medium_threshold: 0.7,
1128                high_threshold: 0.85,
1129                critical_threshold: 0.95,
1130            },
1131            auto_optimization_enabled: true,
1132        }
1133    }
1134
1135    fn add_snapshot(&mut self, snapshot: MemoryPressureSnapshot) {
1136        self.pressure_history.push_back(snapshot);
1137        if self.pressure_history.len() > 1000 {
1138            self.pressure_history.pop_front();
1139        }
1140    }
1141
1142    fn get_summary(&self) -> MemoryPressureSummary {
1143        // Simplified implementation
1144        MemoryPressureSummary {
1145            current_pressure_levels: HashMap::new(),
1146            pressure_trend: PressureTrend::Stable,
1147            devices_under_pressure: Vec::new(),
1148            time_in_high_pressure: Duration::from_secs(0),
1149        }
1150    }
1151}
1152
1153// Additional implementation stubs for summary structures
1154
1155impl FragmentationSummary {
1156    fn new(_history: &VecDeque<MemoryFragmentationSnapshot>) -> Self {
1157        Self {
1158            avg_fragmentation_ratio: 0.1,
1159            peak_fragmentation_ratio: 0.2,
1160            fragmentation_trend: FragmentationTrend::Stable,
1161            most_fragmented_device: 0,
1162        }
1163    }
1164}
1165
1166impl BandwidthSummary {
1167    fn new(_monitors: &HashMap<i32, GpuBandwidthMonitor>) -> Self {
1168        Self {
1169            avg_bandwidth_utilization: 0.75,
1170            peak_bandwidth_achieved: 800.0,
1171            bandwidth_efficiency_by_operation: HashMap::new(),
1172            underutilized_devices: Vec::new(),
1173        }
1174    }
1175}
1176
1177impl AllocationPatternSummary {
1178    fn new(_allocations: &HashMap<Uuid, GpuMemoryAllocation>) -> Self {
1179        Self {
1180            total_allocations: 0,
1181            avg_allocation_size: 0,
1182            largest_allocation: 0,
1183            allocation_size_distribution: HashMap::new(),
1184            memory_leaks_detected: 0,
1185            allocation_hot_spots: Vec::new(),
1186        }
1187    }
1188}
1189
1190impl CrossDeviceTransferSummary {
1191    fn new(_transfers: &[CrossDeviceTransfer]) -> Self {
1192        Self {
1193            total_transfers: 0,
1194            total_bytes_transferred: 0,
1195            avg_transfer_bandwidth: 0.0,
1196            p2p_efficiency: 0.9,
1197            transfer_bottlenecks: Vec::new(),
1198        }
1199    }
1200}
1201
1202#[derive(Debug)]
1203struct GpuMemoryPool {
1204    device_id: i32,
1205    total_memory: usize,
1206    free_memory: usize,
1207    fragmentation_score: f64,
1208}
1209
1210/// Configuration for advanced GPU profiling
1211#[derive(Debug, Clone, Serialize, Deserialize)]
1212pub struct AdvancedGpuProfilingConfig {
1213    /// Enable GPU profiling
1214    pub enable_gpu_profiling: bool,
1215    /// Number of GPU devices to profile
1216    pub device_count: i32,
1217    /// Enable memory profiling
1218    pub enable_memory_profiling: bool,
1219    /// Enable kernel profiling
1220    pub enable_kernel_profiling: bool,
1221    /// Enable bandwidth monitoring
1222    pub enable_bandwidth_monitoring: bool,
1223    /// Maximum number of allocations to track
1224    pub max_tracked_allocations: usize,
1225    /// Sampling rate for profiling (0.0 to 1.0)
1226    pub profiling_sampling_rate: f32,
1227    /// Enable fragmentation analysis
1228    pub enable_fragmentation_analysis: bool,
1229}
1230
1231impl Default for AdvancedGpuProfilingConfig {
1232    fn default() -> Self {
1233        Self {
1234            enable_gpu_profiling: true,
1235            device_count: 1,
1236            enable_memory_profiling: true,
1237            enable_kernel_profiling: true,
1238            enable_bandwidth_monitoring: true,
1239            max_tracked_allocations: 10000,
1240            profiling_sampling_rate: 1.0,
1241            enable_fragmentation_analysis: true,
1242        }
1243    }
1244}
1245
1246/// Summary report for kernel optimization
1247#[derive(Debug, Clone, Serialize, Deserialize)]
1248pub struct KernelOptimizationSummaryReport {
1249    pub total_kernels_analyzed: usize,
1250    pub optimization_opportunities_found: usize,
1251    pub high_impact_optimizations: Vec<HighImpactOptimization>,
1252    pub fusion_opportunities: usize,
1253    pub regression_alerts: usize,
1254    pub overall_optimization_score: f64,
1255    pub top_recommendations: Vec<String>,
1256}
1257
1258#[derive(Debug, Clone, Serialize, Deserialize)]
1259pub struct HighImpactOptimization {
1260    pub kernel_name: String,
1261    pub optimization_type: String,
1262    pub expected_speedup: f64,
1263    pub implementation_difficulty: String,
1264    pub description: String,
1265}
trustformers_debug/advanced_gpu_profiler.rs

trustformers_debug/
advanced_gpu_profiler.rs
