---
name: Trueno Integration Investigation
about: Investigate using Trueno for SIMD-accelerated operations
title: "[RESEARCH] Investigate Trueno integration for performance-critical operations"
labels: performance, research, kaizen
assignees: ''
---

## Context

**Trueno** (v0.1.0) is a multi-target high-performance compute library developed by PAIML with exceptional SIMD performance:
- **340% faster** dot products (SSE2 vs scalar)
- **315% faster** sum reductions
- **348% faster** max finding
- Supports CPU SIMD (x86/ARM/WASM), GPU (Vulkan/Metal/DX12), WebAssembly

**Repository**: `/home/noah/src/trueno` (local), https://github.com/paiml/trueno (remote)

## Investigation Scope

Explore potential Trueno integration for performance-critical operations in PMAT:

### 1. Rust Project Score
- **File caching aggregations** (sum file sizes, count files)
- **Complexity score calculations** (aggregating metrics across files)
- **Parallel reduction operations** (combining category scores)

### 2. Churn Analysis
- **Time series aggregations** (summing commits over time windows)
- **Statistical calculations** (mean, max, percentiles)
- **Vector operations** (comparing churn patterns)

### 3. Code Quality Metrics
- **Cyclomatic complexity aggregation** across functions
- **SATD annotation counting and scoring**
- **Dead code detection scoring**

## Expected Benefits

If applicable:
- **5-340% speedup** for compute-intensive aggregations
- **Write once, optimize everywhere** (x86/ARM/WASM/GPU)
- **Zero unsafe** in public API (safety via type system)
- **Production ready** (PMAT quality gates, Toyota Way principles)

## Constraints

- **v0.1.0**: Early release, API may evolve
- **Dependency cost**: Adding new dependency (currently minimal footprint)
- **Complexity trade-off**: SIMD may be overkill for small datasets

## Action Items

- [ ] Profile PMAT hotspots to identify compute-intensive operations
- [ ] Benchmark candidate operations with and without Trueno
- [ ] Evaluate API ergonomics for PMAT use cases
- [ ] Assess dependency impact (compile time, binary size)
- [ ] Decision: Integrate, defer, or skip based on evidence

## Success Criteria

**Integrate if**:
- ≥10% measurable performance improvement
- API fits naturally with existing code
- No significant dependency bloat
- Trueno reaches v0.2+ (stable API)

**Defer if**:
- Performance gains <10%
- API requires significant refactoring
- Trueno API still evolving rapidly

**Skip if**:
- No meaningful performance benefit
- Complexity outweighs gains

## Production Example: Renacer v0.2.0

**Renacer** (syscall tracer) successfully uses Trueno SIMD for statistics mode:
- **Published**: https://crates.io/crates/renacer v0.2.0
- **Use Case**: SIMD-accelerated syscall statistics aggregation
- **Quality**: 91.21% coverage, 94.2/100 TDG score
- **Performance**: Trueno provides 5-340% speedup for aggregate operations
- **Architecture**: Demonstrates Trueno production readiness

**Key Insight**: Renacer proves Trueno is production-ready for high-performance data aggregation.

## Related

- Kaizen optimization philosophy (continuous improvement)
- Toyota Way principles (evidence-based decisions)
- Trueno README: `/home/noah/src/trueno/README.md`
- Renacer (reference implementation): https://github.com/paiml/renacer
