MathWorks Case Studies Cutting Algorithm Development Time with MATLAB: Q&A with FLIR

	Cutting Algorithm Development Time with MATLAB: Q&A with FLIR MathWorks

Cutting Algorithm Development Time with MATLAB: Q&A with FLIR

MathWorks

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
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. Read More
About 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. Read More
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. Read More Log in to view content
Contents

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

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.

About 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.

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.

Impact #1	Our algorithm developers produce FPGA prototypes on their own, cutting prototyping time significantly.
Impact #2	We increased MATLAB code reuse for HDL code generation for other projects from 0% to 30%.
Impact #3	We can make even major changes to our algorithms quickly: In just three hours, one of our engineers made a significant algorithmic change to a core filter that previously would have required six weeks.

Impact #1

Our algorithm developers produce FPGA prototypes on their own, cutting prototyping time significantly.

Impact #2

We increased MATLAB code reuse for HDL code generation for other projects from 0% to 30%.

Impact #3

We can make even major changes to our algorithms quickly: In just three hours, one of our engineers made a significant algorithmic change to a core filter that previously would have required six weeks.

Benefit #1	Cutting prototyping time by up to 60%.
Benefit #2	Increased MATLAB code reuse for HDL code generation from 0% to 30%.
Benefit #3	Significant algorithmic changes that previously required six weeks now take just three hours.

Benefit #1

Cutting prototyping time by up to 60%.

Benefit #2

Increased MATLAB code reuse for HDL code generation from 0% to 30%.

Benefit #3

Significant algorithmic changes that previously required six weeks now take just three hours.

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Overview

Cutting Algorithm Development Time with MATLAB: Q&A with FLIR

Operational Impact

Quantitative Benefit