Arteris Articles

Semiconductor Engineering: Time For FMEDA Reuse?

Stefano Lorenzini, Fellow & Functional Safety Manager at Arteris IP authored this Semiconductor Engineering article:

Time for FMEDA Reuse?

 July 7th, 2022 - By Stefano Lorenzini

Making it easier to integrate configurable IP into safety-critical systems.

How do designers quantify safety in electronic systems? Through one or more tables called Failure Modes, Effects and Diagnostic Analysis – FMEDA. In fact, an FMEDA does not have to be a table; it could be manifested in scripts or some other form, but a table is the easiest way to think of this information. Think of an FMEDA for an IP, as the concept extends easily to a system-on-chip (SoC). The table has a row for each failure mode that the IP experts can imagine might lead to a critical safety problem. Following identifying information for that failure mode is a description of the effect – the safety problem it might cause. Through fault simulation, the safety engineer determines the likelihood of the root cause problem leading to that effect. If the likelihood is significant, the designer will propose a mitigation technique, such as a parity check to detect the problem or an error-correcting code (ECC) check to correct it. A completed FMEDA then represents a comprehensive safety quality document for that IP, a characterization that an SoC integrator can use when determining the FMEDA for the whole design.

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Topics: IP System-on-Chip functional safety network-on-chip semiconductor engineering SoCs FMEDA scalability traceability Stefano Lorenzini NoCs Arteris IP (AIP)

Semiconductor Engineering: Automotive AI Hardware: A New Breed

Kurt Shuler, Vice President of Marketing at Arteris IP authored this new article in Semiconductor Engineering:

Automotive AI Hardware: A New Breed

June 3rd, 2021 - By Kurt Shuler

What sets automotive apart from the conventional wisdom on AI hardware markets.

Arteris IP functional safety manager Stefano Lorenzini recently presented “Automotive Systems-on-Chip (SoCs) with AI/ML and Functional Safety” at the Linley Processor Conference. A main point of the presentation was that conventional wisdom on AI hardware markets is binary. There’s AI in the cloud: Big, power-hungry, general-purpose. And there’s AI at the edge: Small, low power, limited application-specific features. Automotive AI doesn’t really fit into either category. To power ADAS and autonomous driving functions, these chips are extremely application-specific and require more performance than typical edge AI, are low power but not as low as IoT chips at the edge, and must be as low cost as possible. They also add a new angle – low latency because safety demands fast and deterministic response times. Add to all that the functional safety requirements demanded by ISO 26262 – inside the AI structure as much as everywhere else. Bottom line: Automotive AI SoC architectures are unique beasts.

Topics: SoC NoC functional safety network-on-chip automotive ECC The Linley Group ISO 26262 compliance semiconductor engineering arteris ip interconnects kurt shuler AI SoCs AI/ML Stefano Lorenzini heterogeneous socs ASIL

SemiWiki: Architecture Wrinkles in Automotive AI: Unique Needs

Bernard Murphy (SemiWiki) learns from Stefano Lorenzini, Functional Safety Manager at Arteris IP, the difference between AI in automotive and other contexts. 

Architecture Wrinkles in Automotive AI: Unique Needs

May 20th, 2021 - Bernard Murphy

Arteris IP recently spoke at the Spring Linley Processor Conference on April 21, 2021 about Automotive systems-on-chips (SoCs) architecture with artificial intelligence (AI)/machine learning (ML) and Functional Safety. Stefano Lorenzini, Functional Safety Manager at Arteris IP, presented a nice contrast between auto AI SoCs and those designed for datacenters. Never mind the cost or power, in a car we need to provide near real-time performance for sensing, recognition and actuation. For IoT applications we assume AI on a serious budget, power-sipping, running for 10 years on a coin cell battery. But that isn't the whole story. AI in the car is a sort of hybrid, with the added dimension of safety, which makes for unique architecture wrinkles in automotive AI.  
Topics: SoC NoC network-on-chip semiconductor ECC The Linley Group FlexNoC arteris ip semiwiki functional safety manager kurt shuler data centers noc interconnect AI SoCs AI/ML automotive AI Hardware Stefano Lorenzini