MatLogica | Accelerator

Accelerator

MatLogica Simulation Accelerator: 6-100x Faster Performance

Code in object-oriented C#, C++, or Python while MatLogica automatically handles performance optimization, vectorization, and multi-threading. Transform your analytics without changing your development approach.

The Object-Oriented Performance Problem

Modern compilers for object-oriented languages are not optimized for calculation-intensive tasks. Extensive use of abstraction and virtual functions enables easy-to-read code, but the performance penalty is severe.

Traditional Approach Problems:

  • Manual optimization tedious and time-consuming
  • Vectorized code hard to write and maintain
  • Multi-threading complex and error-prone
  • Performance vs readability tradeoff
  • Developers spend time on optimization, not models

MatLogica's Solution:

Developers focus on adding value while MatLogica's Simulation Accelerator automatically handles performance optimization, vectorization, and multi-threading.

Code Generation AAD™ Approach

First execution generates optimized code: The Code Generation AAD™ approach generates optimized versions of your original model (and its adjoint if needed) during first execution. This generated code is used in all subsequent loops, delivering sustained speedups.

Semi-Automatic Integration

Minimal code changes required:

  1. Replace double with overloaded idouble active type
  2. Mark inputs and outputs for recording
  3. MatLogica handles optimization, vectorization, multi-threading automatically

Result: Keep your object-oriented design patterns, gain data-oriented performance automatically.

70% Code Reduction

Simplified modeling codebase by reducing code lines up to 70%! Less code means fewer bugs, easier maintenance, faster development.

3-4x Faster Development

Accelerated IT turnaround for new features released 3-4x quicker! Developers focus on models, not optimization.

6-100x Performance

Dramatic model performance boost with automatic optimizations, native AVX2/AVX512 vectorization, and safe multi-threading.

50%+ Cost Savings

Slash compute bills by 50% or more from cloud or grid costs through efficient use of existing hardware.

Fewer Bugs

Cleaner codebase with MatLogica's abstraction layer - your code does less manual work, meaning more focus and fewer bugs.

Easy Integration

Drop-in replacement for native types. Semi-automated integration delivers results quickly without extensive refactoring.

How the Simulation Accelerator Works

Automatic Optimization

MatLogica's accelerator utilizes native CPU vectorization and multi-threading, delivering performance comparable to GPU without GPU complexity.

For Monte Carlo simulations, historical analysis, and what-if scenarios, speed can be increased by 6-100x, depending on original code characteristics.

Key Technologies:

  • AVX2/AVX512 vectorization: 4-8 operations per cycle
  • Safe multi-threading: Linear scaling across cores
  • Code compression: Better cache utilization
  • Runtime optimization: Better than ahead-of-time compilation
MatLogica Simulation Accelerator Architecture

Understanding the Technology

Simulation Accelerator Use Cases

Quantitative Finance

  • Monte Carlo pricing and Greeks
  • Historical VaR calculations
  • Stress testing scenarios
  • XVA simulations
  • Back-testing strategies

Risk Management

  • Portfolio risk analysis
  • What-if scenario analysis
  • Market data sensitivity
  • Regulatory calculations (FRTB)
  • Real-time risk updates

Scientific Computing

  • Parameter sweeps
  • Sensitivity analysis
  • Optimization iterations
  • Simulation ensembles
  • Monte Carlo methods

Machine Learning

  • Training iterations
  • Hyperparameter tuning
  • Ensemble methods
  • Cross-validation
  • Time series forecasting

Ready to Accelerate Your Simulations?

See how much faster your analytics can run with MatLogica Simulation Accelerator

Schedule Performance Assessment

info@matlogica.com

Related topics: simulation acceleration, Monte Carlo speedup, AVX2 AVX512 automatic vectorization, multi-threading safe automatic, object-oriented performance optimization, code simplification 70%, developer productivity 3x, compute cost reduction 50%, GPU alternative CPU, what-if scenario acceleration, historical VaR speedup, stress testing performance, CPU vs GPU comparison