6 Commits

Author SHA1 Message Date
Anand Krishnamoorthi 5d8387f4d9 feat(hoist): pre-compute loop hoisting metadata at compilation time (#483)
Introduce a compiler pass that analyzes and pre-computes loop hoisting information
during policy compilation. This hoisted metadata is stored in lookup tables and made
available to downstream consumers:

- interpreter: use HoistedLoop entries during evaluation (replaces runtime scanning)
- type inference: can leverage pre-computed loop structure for type propagation
- RVM compiler: will consume hoisting metadata for optimized bytecode generation

Changes:
- populate loop hoisting tables during engine preparation and query snippet execution
- refactor eval_stmts_in_loop and eval_output_expr_in_loop to consume HoistedLoop directly
- add helper methods for accessing loop expressions, collections, and indices from HoistedLoop
- extend Lookup with get_checked and into_slots for safe query context access and merging

Signed-off-by: Anand Krishnamoorthi <anakrish@microsoft.com>
2025-10-08 11:11:30 -05:00
Anand Krishnamoorthi 2a0b4ae6b5 feat! Mimalloc as the default allocator (#434)
This change integrates mimalloc as the default memory allocator for Regorus,
delivering significant performance improvements across all evaluation modes
and language bindings.

Technical Implementation:
- Build mimalloc in vendored mode from C sources (following QSharp approach)
- Implement GlobalAlloc trait for seamless Rust integration
- Add optional 'mimalloc' feature flag for conditional compilation
- Add comprehensive ACI benchmarks to measure evaluation performance

Performance Impact:

Rust Engine Evaluation:
- Single-threaded: ~29% improvement (423 vs 328 Kelem/s)
- Multi-threaded: Better scaling with reduced thread contention
- Fresh engines: ~24% improvement (56 vs 45 Kelem/s)

Rust Compiled Policy Evaluation:
- Single-threaded: ~41% improvement (426 vs 303 Kelem/s)
- Multi-threaded: Improved allocation efficiency under contention
- Fresh compilation: ~26% improvement (53 vs 42 Kelem/s)

C# FFI Bindings:
- Engine evaluation: ~27% improvement (279 vs 219 Kelem/s)
- Compiled policies: ~29% improvement (273 vs 211 Kelem/s)
- Better threading characteristics through improved underlying allocation

Key Benefits:
- Reduced allocation-related contention in multi-threaded scenarios
- More consistent performance across different thread counts
- Improved memory allocation efficiency for both native Rust and FFI workloads
- Better scaling characteristics for production deployments

The mimalloc integration provides substantial performance gains while
maintaining full compatibility with existing code through feature flags.

Reference: QSharp allocator implementation
(https://github.com/microsoft/qsharp/tree/main/source/allocator)

Fixes #297

Signed-off-by: Anand Krishnamoorthi <anakrish@microsoft.com>
2025-08-25 15:01:38 -05:00
Anand Krishnamoorthi d561531613 feat: add multi-threaded evaluation benchmark suite with comprehensive C# implementation (#457)
This commit introduces a complete multi-threaded evaluation benchmark suite for both Rust and C# implementations of Regorus.

- Implemented engine evaluation benchmark with input and engine cloning strategies
- Implemented compiled policy evaluation benchmark with input cloning and shared compiled policy strategies.

- Created EngineEvaluationBenchmark.cs and CompiledPolicyEvaluationBenchmark.cs with time-based execution (3s warmup + 3s evaluation)
- Implemented configuration options matching Rust implementation (useClonedEngines, useSharedPolicies parameters)

- Created markdown analysis documentation with cross-platform performance analysis
- C# seems to achieve 58-89% of Rust performance on test machine.

Signed-off-by: Anand Krishnamoorthi <anakrish@microsoft.com>
2025-08-22 11:40:39 -05:00
Anand Krishnamoorthi db718654b5 feat: Add Schema Registry and Validation Framework (#456)
* feat: Add Schema Registry and Validation Framework

This commit introduces a comprehensive schema registry and validation framework, providing schema-based validation of resources and policy effects.

- Thread-safe, in-memory registry for schema storage and management
- Global registry patterns for effects and resources
- Concurrent access with proper error handling
- Unicode schema names support

- JSON Schema-compliant validation for all primitive types
- Advanced constraint validation (patterns, ranges, length limits)
- Discriminated union support with anyOf schemas
- Detailed error reporting with nested validation paths
- Discriminated subobject validation for polymorphic schemas

- **Registry Tests**: All registry operations
- **Effect Tests**: Policy effect validation
- **Resource Tests**: Resource validation
- **Validation Tests**: Core validation engine
- Thread-safety, error handling, integration scenarios, edge cases

- **Dependencies**: dashmap, once_cell, regex
- **Thread Safety**: Minimal locking with Rc<Schema> sharing
- **Error Types**: TypeMismatch, OutOfRange, PatternMismatch, etc.

- Complete schema registry and validation subsystem
- Comprehensive test coverage
- Foundation for policy validation in Regorus

Benchmarks:

- Criterion benchmarks for basic types, effects and Azure resources
- Performance range: 3.22ns (string) to 34.74µs (Azure VM resource schema validation)
- String withs patterns validation: 30.2µs. Need to explore whether regex caching helps
  bring this down.
- Azure policy effects: 188ns-1.4µs

Signed-off-by: Anand Krishnamoorthi <anakrish@microsoft.com>

* Address PR feedback

- move error to a separate file
- use meaningful var names

Signed-off-by: Anand Krishnamoorthi <anakrish@microsoft.com>

* Refactor

- Reusable Registry struct
- Split and simplify tests

Signed-off-by: Anand Krishnamoorthi <anakrish@microsoft.com>

---------

Signed-off-by: Anand Krishnamoorthi <anakrish@microsoft.com>
2025-08-14 15:59:30 -05:00
Anand Krishnamoorthi dbba57f499 perf: Optimize clone (#443)
Introduce the notion of CompiledPolicy to hold stuff that
remains immutable during evaluation - e.g. rules, function,
schedules etc

Cloning takes about 60 nano seconds for an engine loaded with
ACI policies. Earlier it used to take 40 microseconds.
Thus there is easily more than 100x speedup.

Signed-off-by: Anand Krishnamoorthi <anakrish@microsoft.com>
2025-08-06 20:50:47 -05:00
Burak Varlı 60ac4a7a7c Basic benchmarking setup with Criterion (#408)
* Basic benchmarking setup with Criterion
* Fix Clippy warnings

Signed-off-by: Burak Varlı <burakvar@amazon.co.uk>
2025-05-14 10:41:06 -05:00