References

External resources, academic papers, and related projects that inform Trueno-DB's design and implementation.

Academic Papers

Foundational research papers cited in Trueno-DB's architecture and implementation.

Database Systems

MonetDB/X100: Vectorized Query Execution

  • Authors: Peter Boncz, Marcin Zukowski, Niels Nes
  • Conference: CIDR 2005 (Conference on Innovative Data Systems Research)
  • Summary: Introduced vectorized query execution with columnar data processing
  • Relevance: Foundation for Trueno-DB's SIMD backend and chunked processing
  • URL: cidrdb.org/cidr2005/papers/P19.pdf

Morsel-Driven Parallelism: NUMA-Aware Query Evaluation

  • Authors: Viktor Leis, Peter Boncz, Alfons Kemper, Thomas Neumann
  • Conference: SIGMOD 2014
  • Summary: Morsel-based parallelism for NUMA-aware execution (foundation for out-of-core GPU processing)
  • Relevance: Trueno-DB's 128 MB morsel size prevents VRAM exhaustion
  • DOI: 10.1145/2588555.2610507

Volcano Optimizer: Cost-Based Query Optimization

  • Authors: Goetz Graefe
  • Journal: IEEE Data Engineering Bulletin, 1993
  • Summary: Cascading query optimizer with cost-based plan selection
  • Relevance: Trueno-DB's backend dispatcher uses cost-based selection (5x rule)
  • URL: sites.computer.org/debull/93dec-cd.pdf

GPU Databases

HeavyDB (formerly MapD): GPU Database Patterns

  • Authors: Todd Mostak
  • Conference: SIGMOD 2017
  • Summary: GPU-accelerated database with kernel fusion and parallel aggregations
  • Relevance: Trueno-DB's JIT compiler and fused filter+sum kernels
  • DOI: 10.1145/3035918.3056100

Kernel Fusion for GPU Databases

  • Authors: Mark Harris (NVIDIA)
  • Year: 2007
  • Summary: Parallel reduction algorithms and kernel fusion techniques
  • Relevance: Trueno-DB's 2-stage reduction in MIN/MAX kernels
  • URL: developer.nvidia.com/gpugems/gpugems3

Columnar Storage

Apache Arrow: Columnar In-Memory Format

Analytical Databases

DuckDB

  • Description: In-process analytical database with vectorized execution
  • Language: C++
  • Relevance: Competitive benchmark baseline for OLAP queries
  • URL: duckdb.org
  • GitHub: github.com/duckdb/duckdb

Polars

  • Description: Lightning-fast DataFrame library with query optimization
  • Language: Rust
  • Relevance: Rust ecosystem leader in columnar analytics
  • URL: pola.rs
  • GitHub: github.com/pola-rs/polars

SQLite

  • Description: Self-contained SQL database engine (row-oriented)
  • Language: C
  • Relevance: OLTP baseline for performance comparisons
  • URL: sqlite.org
  • Architecture: sqlite.org/arch.html

GPU Computing

wgpu

  • Description: Safe Rust implementation of WebGPU API
  • Language: Rust
  • Relevance: Trueno-DB's GPU backend (Vulkan/Metal/DX12/WebGPU abstraction)
  • URL: wgpu.rs
  • GitHub: github.com/gfx-rs/wgpu

WebGPU Specification

  • Description: Modern cross-platform GPU API standard
  • Organization: W3C GPU for the Web Community Group
  • Relevance: Enables browser deployment (Phase 4)
  • URL: gpuweb.github.io/gpuweb

WGSL Specification

  • Description: WebGPU Shading Language (shader programming)
  • Organization: W3C
  • Relevance: Language for Trueno-DB's compute kernels and JIT compiler
  • URL: w3.org/TR/WGSL

SIMD Libraries

trueno

  • Description: SIMD-accelerated aggregations for Rust (AVX-512/AVX2/SSE2)
  • Language: Rust
  • Relevance: Trueno-DB's CPU fallback backend
  • Version: 0.6.0 (dependency in Cargo.toml)
  • GitHub: github.com/paiml/trueno

Intel Intrinsics Guide

  • Description: Complete reference for x86 SIMD instructions
  • Relevance: Understanding AVX-512/AVX2/SSE2 performance characteristics
  • Search: "Intel Intrinsics Guide" (official documentation)

Rust Ecosystem

Core Language

The Rust Programming Language (Book)

  • Authors: Steve Klabnik, Carol Nichols
  • URL: doc.rust-lang.org/book
  • Relevance: Foundation for understanding Trueno-DB's implementation

Rust Performance Book

Testing & Benchmarking

Criterion.rs

proptest

cargo-llvm-cov

Development Tools

Renacer

  • Description: Modern syscall tracer with DWARF support (Rust strace replacement)
  • Relevance: Validates zero-copy operations and GPU memory mapping
  • URL: github.com/paiml/renacer

mdBook

Toyota Way & Quality

Toyota Production System

The Toyota Way: 14 Management Principles

  • Author: Jeffrey Liker
  • ISBN: 978-0071392310
  • Relevance: Trueno-DB's development methodology (Jidoka, Kaizen, Genchi Genbutsu)

Toyota Production System: Beyond Large-Scale Production

  • Author: Taiichi Ohno
  • ISBN: 978-0915299140
  • Relevance: Foundation for EXTREME TDD and quality-first development

Software Quality

Mutation Testing: A Comprehensive Survey

  • Authors: Yue Jia, Mark Harman
  • Journal: IEEE Transactions on Software Engineering, 2011
  • Relevance: Trueno-DB's mutation testing for test suite validation
  • URL: ieeexplore.ieee.org/document/5487526

Technical Debt Grading (TDG)

  • Concept: Code quality scoring from 0-100 (F to A+)
  • Relevance: Trueno-DB maintains 96.3/100 (A+) across all modules
  • Factors: Complexity, documentation, error handling, test coverage

Community & Support

Trueno-DB Resources

Official Repository

Documentation Book

Crates.io Package

  • Status: In development (v0.2.1)
  • Planned: Publication after Phase 3 completion

Learning Resources

GPU Programming Guides

Database Internals (Book)

  • Author: Alex Petrov
  • ISBN: 978-1492040347
  • Relevance: Understanding database storage and query execution

Designing Data-Intensive Applications

  • Author: Martin Kleppmann
  • ISBN: 978-1449373320
  • Relevance: System design principles for analytics databases

Standards & Specifications

SQL:2023 Standard

IEEE 754 Floating-Point Arithmetic

Semantic Versioning 2.0.0

  • URL: semver.org
  • Relevance: Trueno-DB's versioning scheme (currently v0.2.1)

See Also

Citation

If you use Trueno-DB in academic research, please cite:

@software{trueno_db,
  title = {Trueno-DB: GPU-First Embedded Analytics Database},
  author = {{Pragmatic AI Labs}},
  year = {2025},
  url = {https://github.com/paiml/trueno-db},
  version = {0.2.1},
  license = {MIT}
}

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