Presentation
Developing Software Test Library (STL) as a Safety Mechanism for Vision AI DSP
DescriptionCeva SensPro AI & Vision DSP are embedded within automotive and many other markets' chips that require safety. Showing that DSP matches the safety metrics set by ISO 26262 for relevant ASIL is critical across these markets as they move towards having advanced ADAS and autonomous driving solutions. STL is a state-of-the-art SW-based safety mechanism which allows DSP to address ASIL KPIs specifically targeting permanent HW faults.
The DSP cores are developed as SEooC (generic off the shelf IP), with ASIL B integrity level. This paper discusses the challenges in developing the STL with RTL design and fault injection analysis, in achieving the SPFM for identified modules based on Technical Safety Requirements. Also highlighted are various challenges involving collaboration between multiple teams – SW, HW, PM and Safety. An ISO 26262 certified fault injection analysis tool and methodology is used to generate various results and customized reports to effectively iterate and improve the STL to achieve the required targets of SPFM.
Customized reports, from the tool has helped in clearly communicating the improvements needed for STL to reach the target Diagnostic Coverage and SPFM, like faults that are blocked by various configuration registers, which constants flops to be toggled to make STL more effective, time taken to detect fault after injection, SPFM for individual modules and all combined.
The DSP cores are developed as SEooC (generic off the shelf IP), with ASIL B integrity level. This paper discusses the challenges in developing the STL with RTL design and fault injection analysis, in achieving the SPFM for identified modules based on Technical Safety Requirements. Also highlighted are various challenges involving collaboration between multiple teams – SW, HW, PM and Safety. An ISO 26262 certified fault injection analysis tool and methodology is used to generate various results and customized reports to effectively iterate and improve the STL to achieve the required targets of SPFM.
Customized reports, from the tool has helped in clearly communicating the improvements needed for STL to reach the target Diagnostic Coverage and SPFM, like faults that are blocked by various configuration registers, which constants flops to be toggled to make STL more effective, time taken to detect fault after injection, SPFM for individual modules and all combined.
Event Type
Engineering Track Poster
TimeMonday, June 245:00pm - 6:00pm PDT
LocationLevel 2 Exhibit Hall
Back-End Design
Embedded Systems
Front-End Design
IP