Cutting Algorithm Development Time with MATLAB: Q&A with FLIR
Company Size
1,000+
Product
- MATLAB
- HDL Coder
Tech Stack
- MATLAB
- HDL Coder
- FPGA
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Digital Expertise
- Productivity Improvements
Technology Category
- Application Infrastructure & Middleware - Data Exchange & Integration
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Security & Public Safety
Applicable Functions
- Product Research & Development
- Quality Assurance
Use Cases
- Machine Condition Monitoring
- Predictive Maintenance
Services
- Software Design & Engineering Services
- System Integration
About The Customer
Founded in 1978, and with 2800 employees worldwide, FLIR Systems designs and manufactures advanced sensing technologies for applications including search and rescue, airborne and ground-based surveillance, manufacturing process control, and environmental monitoring.
The Challenge
Our hardware engineers were translating algorithms developed by algorithm engineers into HDL using written specifications, and without knowing exactly how the algorithms worked. If the FPGA implementation did not perform like our simulations, we never knew if the implementation or the algorithm was the problem. And even a small change to the algorithm meant rewriting most of the HDL.
The Solution
With MATLAB® and HDL Coder™, we can generate synthesizable HDL code directly from the algorithm. The HDL is implemented and tested on the FPGA, and the results are verified against the simulation. Our customer was ecstatic when, a few months after seeing our MATLAB simulations of a new thermal imaging filter, we showed them the first working camera with this new filter and the camera performed exactly like the simulations.
Operational Impact
Quantitative Benefit
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