Automation Tools
for Better Code

Automated Software Parallelization for Embedded Multicore, GPUs, DSPs and Vector Processors

With more than 10 years of research and tool development, emmtrix Technologies is your solution provider for efficient software development targeting high-performance embedded multicore systems: Multicore and vector processors, accelerators (e.g. GPUs, DSPs), or any heterogeneous combination of these are fully supported.

Your benefits:

  • Parallelize your applications onto the various processing elements (software parallelization)
  • Maintain your functional safety (ISO 26262 / DO 178C)
  • Convert your code (C++, MATLAB®, Simulink™, GNU Octave and Scilab) efficiently and transparenly to C 
  • Estimate the performance of your code even at an early development stage
  • Understand data dependencies and event chains of your code (static code analysis)

Our Solutions

Performance Estimation

  • Early in workflow
  • Master your timing budgets
  • Continuous integration support
  • Estimation methods:
    • Static source code
    • Simulation
    • Profiling on hardware
  • Intuitive visualization
  • Continuous performance monitoring during the development


Automated Vectorization

Data Dependency Analysis

Code Conversion

Tools & Services

emmtrix Parallel Studio icon

emmtrix Parallel Studio (ePS)

User-configurable automated development of parallel C code for embedded multicore systems, GPUs and FPGAs.

emmtrix Code Generator icon

emmtrix Code Generator (eCG)

Embedded C code generation from MATLAB® or Simulink®, Scilab or Xcos or GNU Octave optimized for parallelization.

emmtrix Model Code Generator icon

emmtrix Model Code Generator (eMCG)

Translate graphical Simulink® models (*.slx) into MATLAB® or GNU Octave language files (.m) with emmtrix Model Code Generator.

emmtrix C++ to C Compiler icon

emmtrix C++ to C Compiler (eCPP2C)

Automatical translation of C++ source code into analyzable C code enables software parallelization of C++ applications with ePS.

ePS Qualification Kit icon

ePS Qualification Kit (ePS-QKIT)

Verification tool for emmtrix Parallel Studio according to DO-178C/330, ISO 26262 and comparable functinal safefty standards.

Service icon

Customization, Consulting and Trainings

Wide range of custom services to address your specific multicore requirements, get going fast and take the right decisions.

Free Webinars on Software Optimization

Modern multi-core systems, DSPs and GPUs are ubiquitous, with vector processing units like the PPU of AURIX TC4x™ adding another type of accelerator. In order to use these platforms efficiently and effectively, companies and software developers have to deal with and understand parallelization/vectorization. Distributing software onto the available processing units increases performance but also complexity. In our webinars you will learn how to successfully parallelize/vectorize code, as well as more about our tools and their benefits.

Latest News & Next Event(s)

Dependency Chain Analysis

C-Vise/C-Reduce open-source tools

Company | Sep 20, 2022
emmtrix is supporting C-Vise/C-Reduce open-source tools!

Dependency Chain Analysis

EIC GHG Programme – 1st badge

Company | Sep 13, 2022
It’s official: emmtrix is on the way to reducing its CO2 footprint!

Dependency Chain Analysis

ePS Release 2022.07

Tools | Aug 04, 2022
Besides the usual improvements and bug fixes, we have some new features.

SAEC Days logo

Nov 15 – 16, 2022 | Baden-Baden Germany

ELIV MarketPlace 2022

Visit our booth at ELIV MarketPlace 2022. The event (long known as “Baden-Baden Special”) has been held every year since 2004. More than 400 experts meet here to learn abut trends and developments in electronics for mobile applications.

People Who Trust Us

Together with our clients and partners we create solutions for leveraging embedded multicore programming.
AbsInt logo
DLR logo
Infineon logo
ViGEM logo
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 879405

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 879405

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