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# LLVM IR Analysis Dataset: llvm-sys.rs |
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This dataset contains comprehensive LLVM IR analysis data extracted from Rust source `/home/mdupont/2024/08/24/llvm-sys.rs` using the LLVM IR extractor. |
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## Dataset Overview |
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- **Source**: /home/mdupont/2024/08/24/llvm-sys.rs |
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- **Optimization Levels**: ["O0", "O1", "O2", "O3"] |
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- **Extraction Tool**: LLVM IR extractor (part of hf-dataset-validator-rust) |
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- **Format**: Apache Parquet files optimized for machine learning |
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- **Compression**: Snappy compression for fast loading |
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## Dataset Structure |
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### Phase-Based Organization |
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The dataset captures the complete Rust β LLVM IR compilation pipeline: |
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#### 1. IR Generation (`ir_generation-*-phase/`) |
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- Initial LLVM IR generation from Rust source |
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- Type system mappings (Rust types β LLVM types) |
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- Function signature transformations |
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- Basic block and instruction analysis |
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#### 2. Optimization Passes (`optimization_passes-*-phase/`) |
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- LLVM optimization pass applications and effects |
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- Before/after IR comparisons for each optimization |
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- Performance impact measurements |
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- Optimization decision analysis |
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#### 3. Code Generation (`code_generation-*-phase/`) |
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- Final IR β machine code generation patterns |
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- Target-specific optimizations and transformations |
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- Register allocation and instruction selection |
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- Assembly code generation analysis |
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#### 4. Performance Analysis (`performance_analysis-*-phase/`) |
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- Execution cycle estimates and performance metrics |
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- Code size and complexity analysis |
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- Optimization impact correlation |
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- Performance regression detection |
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#### 5. Type System Mapping (`type_system_mapping-*-phase/`) |
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- Detailed Rust type β LLVM type conversions |
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- Generic parameter handling and monomorphization |
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- Trait object representation analysis |
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- Lifetime analysis impact on IR generation |
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#### 6. Memory Analysis (`memory_analysis-*-phase/`) |
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- Stack and heap allocation pattern analysis |
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- Memory safety guarantee preservation |
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- Reference counting and ownership in IR |
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- Memory layout optimization analysis |
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## Optimization Levels |
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Each phase is analyzed across multiple optimization levels: |
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- **O0**: No optimization (debug builds) |
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- **O1**: Basic optimizations |
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- **O2**: Standard optimizations (release builds) |
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- **O3**: Aggressive optimizations |
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## Schema |
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Each record contains: |
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- **Source Context**: Original Rust code, line/column, construct type |
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- **LLVM IR**: Generated IR code, instruction counts, basic blocks |
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- **Optimization Data**: Passes applied, before/after comparisons, impact scores |
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- **Code Generation**: Target architecture, assembly code, register usage |
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- **Performance Metrics**: Cycle estimates, code size, complexity scores |
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- **Type Mappings**: Rust β LLVM type conversions and analysis |
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- **Memory Patterns**: Allocation analysis and safety preservation |
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- **Processing Metadata**: Timestamps, tool versions, processing times |
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## Applications |
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This dataset enables research in: |
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- **Compiler Optimization**: Understanding LLVM optimization effectiveness |
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- **Performance Prediction**: Predicting performance from source patterns |
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- **Code Generation**: Learning optimal IR generation strategies |
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- **Type System Research**: Understanding type system compilation |
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- **Memory Safety**: Analyzing memory safety preservation in compilation |
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## Usage |
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### Loading with Python |
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```python |
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import pandas as pd |
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# Load IR generation data for O2 optimization |
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ir_gen_df = pd.read_parquet('ir_generation-O2-phase/data.parquet') |
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print(f"Loaded {len(ir_gen_df)} IR generation records") |
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# Load optimization pass data |
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opt_df = pd.read_parquet('optimization_passes-O2-phase/data.parquet') |
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print(f"Loaded {len(opt_df)} optimization records") |
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``` |
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### Loading with Rust |
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```rust |
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use arrow::record_batch::RecordBatch; |
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use parquet::arrow::arrow_reader::ParquetRecordBatchReaderBuilder; |
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// Load LLVM IR data |
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let file = std::fs::File::open("ir_generation-O2-phase/data.parquet")?; |
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let builder = ParquetRecordBatchReaderBuilder::try_new(file)?; |
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let reader = builder.build()?; |
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for batch_result in reader { |
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let batch = batch_result?; |
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println!("Loaded batch with {} LLVM IR records", batch.num_rows()); |
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} |
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``` |
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## Generation Details |
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- **Generated**: 2025-08-08 00:39:57 UTC |
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- **Tool Version**: LLVM IR extractor (hf-dataset-validator-rust) |
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- **Source**: /home/mdupont/2024/08/24/llvm-sys.rs |
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- **Optimization Levels**: ["O0", "O1", "O2", "O3"] |
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- **Total Phases**: 6 analysis phases Γ 4 optimization levels |
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