By Junko Yoshida

CrowdStrike released a preliminary incident report on the catastrophic software update that caused a global IT outage last Friday.

The company’s proposed remedies, in a section entitled “How Do We Prevent This From Happening Again?” parallel recommendations in our previous story. 

CrowdStrike now says it will “implement a staggered deployment strategy for Rapid Response Content.” But some details in the preliminary report are surprising, particularly CrowdStrike’s explanation of how it implemented massively deploy its so-called “Rapid Response Content” without testing.

It turns out, as professor Phil Koopman of Carnegie Mellon University, concluded in our recent interview, that Crowdstrike tests software changes subject to phased release by IT groups. “But it pushes data changes straight to production with NO TESTING. The only precaution is a check by CrowdStrike’s own Content Validator.” The Content Validator was defective, added Koopman, “allowing bad content to get through.”

By Junko Yoshida

What’s at stake:
Renesas and NXP are rolling out software-defined vehicle development platforms. A platform encompassing hardware, software and cloud-based tools is a huge advancement compared to past offerings to the automotive industry. But no one dares to promise their effectiveness in a real world where OEMs design SDVs with hardware and software from multiple vendors.

To serve the plans of OEMs designing software-defined vehicles (SDVs), Renesas has unveiled an SDV development platform called “ROX” (R-Car Open Access),” boasting that it integrates “all essential hardware, operating systems (OS), software and tools” automakers need to rapidly develop next-generation vehicles “with secure and continuous software updates,” said Renesas.

Similarly, NXP Semiconductors announced earlier this year “CoreRide” designed to address the complexity, scalability and costs carmakers face as they transition their creaky E/E architecture to newer software-defined vehicle architectures.

This initiative by the two leading automotive chip suppliers illustrates their urgent perception that they must minimize the impact of the software crisis facing many car OEMs.

By Ron Wilson

What’s at stake:
There is growing discussion of AI in chip design. Could this be mainly marketing, or could it reflect a new weapon in the EDA armory? If the latter, AI could take on some of the most intractable challenges of designing multi-die systems.

Global industry is placing huge bets that artificial intelligence will create a step-function increase in productivity. From customer service to materials handling, from bond trading to medical research, this faith thrives across a broad domain. But what exactly do these faithful mean when they say AI? There are many species in that phylum. And how exactly will AI — demonstrably excellent at pattern recognition and parlor games, but with fundamental limitations when it comes to accuracy and predictability — make knowledge workers more productive?

The EDA industry, with its witheringly complex tasks, massive data sets, vastly skilled practitioners, and utter intolerance of error, offers an excellent laboratory for exploring these questions. The emerging field of high-performance multi-die modules in particular includes some of the most formidable challenges. And among the tasks in this area, the challenge of multi-physics analysis of modules — analyzing the interacting electromagnetic, thermal, and mechanical properties of a module design — can be most daunting. This may be a great place to ask our questions.