Exhibition Area

Attendees who visited the exhibition area discussed challenges and ideas with MATLAB® and Simulink® experts, saw demos showing the latest features in MATLAB and Simulink, and met MathWorks partners.

Deep Learning

MATLAB makes deep learning easy and accessible even if you are not an expert. Learn how you can perform deep learning tasks with just a few lines of code. Also discover how you can design and build your own convolutional neural network models, access the latest models, or import pretrained models.

Running MATLAB Code on GPUs

Optimized CUDA® code can be generated from MATLAB code for deep learning, embedded vision, and autonomous systems. Learn and discuss how you also can use the generated CUDA code to accelerate computationally intensive MATLAB code.

Engineering Data Analytics

Engineering and IT teams use MATLAB to build advanced data analytics systems such as predictive maintenance. Discuss and understand how you can bring in and manage physical-world data and apply machine learning, neural networks, and statistics.

Integrating MATLAB into Enterprise Systems, Clusters, or Clouds

MATLAB and Simulink applications can be scaled up with clusters and clouds. Learn and understand how you can use parallel computing tools to accelerate computationally intensive MATLAB programs by running them in large-scale, high-performance computing resources such as computer clusters and cloud computing services (e.g. Amazon EC2® and Microsoft® Azure®).


Model-Based Design: Implementing MATLAB and Simulink Design on and SoC Devices

Verilog® and VHDL can be generated from designs in MATLAB and Simulink. Additionally, hardware-software co-design is enabled by providing C/C++ code generation for your software models. Discuss and learn how you can design and generate code and additionally leverage targeted support for development boards for Xilinx® Zynq®-7000 and Intel® Cyclone V SoC.

Model-Based Design: Multidomain Physical Systems

Systems are becoming more and more complex with multiple physical domains interacting. The software domain is becoming a major portion of the systems and needs to be taken into account as well. Learn and discuss how Simulink provides a complete simulation environment that lets you integrate multiple physical domains and control software to capture full system behaviors.

Model-Based Design: Rapid Prototyping and Hardware-in-the-Loop Simulations (Real-Time Testing)

Designs (models) of control software and physical systems in Simulink can be reused for the purpose of real-time testing. Learn and discuss how you can move from pure desktop simulation to real-time execution of your models on hardware specifically designed and optimized for rapid prototyping or hardware-in-the-loop (HIL) simulations.

Model-Based Design: Verification and Validation on the Model and Code Level

Early verification on the model level, and later on the code level, to ensure correctness of model and code are strategic activities within Model-Based Design. Learn and discuss capabilities such as model checking, coverage measurement, requirements management, and bug finder at code level to increase the quality of your design. Also understand how Model-Based Design with MATLAB and Simulink fulfills compliance with your safety standard, such as ISO 26262, IEC 61508 and other standards.