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LOCI

by Aurora Labs
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Technology Deep Dive

Execution Reasoning Grounded in Real CPU and GPU Behavior

We reason between compiled code and real CPU and GPU execution behavior, including worst case path, rare and tail paths that attackers can exploit.
Executable
Decompose
Model
Predict
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Foundation

From Source Code to Executable Reality

Most tools operate on source or runtime data. LOCI operates on compiled executables, where execution truth is already encoded.
  • Control-flow and execution paths
  • Instruction sequences
  • Memory allocation and access behavior
  • CPU and GPU kernels

Why this matters

The executable defines how software can behave during execution – without needing instrumentation or traces.
Decomposition

Binary-Level Decomposition

LOCI decomposes executables into execution-relevant components so it can reason about runtime behavior without source heuristics.
  • Functions, loops, and kernels
  • Control-flow graphs and branches
  • Instruction-level sequences
  • Memory access patterns
Models

Execution Models for CPUs and GPUs

LOCI applies execution models trained on real CPU/GPU behavior, grounded in measured hardware characteristics, not abstract rules.
  • Instruction throughput and latency
  • Branching and divergence behavior
  • Memory hierarchy effects
  • CPU/GPU scheduling and interaction
  • Performance and efficiency characteristics
Trust

Bounded Prediction, Not Generation

Unlike unconstrained text generation, LOCI predicts bounded execution outcomes: numeric, constrained, and comparable across builds.
  • Numeric and constrained outputs
  • Comparable across builds
  • Physically meaningful values (ms, watts, instructions)

Guarantee

Because predictions are bounded by executable structure and real hardware behavior, hallucinated outputs are structurally impossible.
Training

Learning from Measured Execution

Execution models are refined using measured execution data – improving accuracy while staying grounded in physical reality.
  • CPU and GPU traces
  • Performance counters
  • Execution timing and power behavior
Outputs

Execution-Aware Signal

LOCI produces execution-aware signals designed to plug directly into developer workflows and automation.
  • Execution-time estimates
  • Performance regression indicators
  • Efficiency and cost signals
  • High-risk execution path identification

Consumed by

Developers, CI systems, IDEs, and LLM coding agents.
AI Grounding

Grounding LLM Coding Agents

Instead of guessing, LLM agents operate within execution-aware boundaries informed by real CPU/GPU behavior.
  • Execution-grounded constraints for safer generation
  • Optimization guided by execution truth
  • Reduced trial-and-error cycles
Production

Designed for Production Systems

Built for performance – and reliability-critical software where correctness and predictability matter more than speculation.
  • AI inference and training systems
  • Networking and infrastructure software
  • High-performance computing
  • Data center and edge workloads

Principle

Correctness, predictability, and trust over speculative reasoning.
Next Step

Want a walkthrough on LOCI’s execution signals?

See how executable decomposition + hardware-grounded models translate into bounded, actionable signals inside CI, IDEs, and LLM coding agents.
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