Watching the Side Channel

How Does Synopsys Randomize Power?

by Bryon Moyer

Everybody’s trying to break into your… whatever it is you make. No matter what you make or how secure you try to make it, someone will still try to break it. For profit or for bragging rights.

And if the electronics governing the actual communications to and from your device – the main “channel” – are well protected, good job! But that means someone may look elsewhere for a way to break your secrets, using so-called “side-channels.” These typically consist of power or EMI analysis: patterns in both can lead to clues about keys and such, and they have been successfully employed to crack security.


Our 3D Printed Universe

Prototyping and Beyond with FATHOM 3D Printing

by Amelia Dalton

Move over niche applications, 3D printing is headed to prime time! In this week’s Fish Fry, we take a closer look at the evolution of 3D printing and investigate how 3D printed materials are changing the prototyping landscape. Rich Stump from FATHOM joins me to discuss the how 3D printed material allows them to help designers and engineers make the “un-makeable”. We also chat about how enterprise and consumer 3D printing differ, cutting edge 3D printing applications, and what the future holds.


Managing the Automotive Automation Transition

Will You Know How Someone Else’s Car Works?

by Bryon Moyer

Are fully automated cars just around the corner? If you listen to breathless media stories, you’d probably believe so. But that may not be the case – not only could full automation be further away, but there may also be a long transition period before we get there – a time when, critically, there may be all kinds of cars on the roads that have different levels of automation.

Last week’s ICCAD conference featured a keynote by Nissan’s Maarten Sierhuis, addressing some of the realities of self-driving cars. His main point was to counter some of the press that suggests that full automation is imminent: it’s far harder than people realize. The discussion was illuminating, but it also raised for me a question: during this extended transition, if you borrow someone else’s car or, say, rent a car, how can you quickly assess what levels of automation are present in the unfamiliar vehicle?


Can You Get Sued for Bad Code?

Legal Liability is Still User-Defined in the World of Software

by Jim Turley

You’ve just installed a shiny new multimillion-dollar computer system used to dispatch ambulances in a large, metropolitan city. You and your colleagues have spent years developing the software, which allows first-responders to efficiently locate the nearest ambulance in any part of the city. When an emergency call comes in, your computer immediately pinpoints the nearest ambulance, alerts the dispatcher, and sends help on the way. It’s a triumph.

Except that it doesn’t work. In fact, it’s so bad that experienced dispatchers would rather use a pencil and paper instead of your horribly buggy system. Rather than speeding up response times, ambulances are getting delayed or misdirected. Some aren’t even dispatched at all, long after the emergency call has come in. These unexplainable delays have probably cost lives. And it’s your fault.


Siemens Buys Mentor Graphics

End of an EDA Era

by Kevin Morris

Electronic Design Automation (EDA) is one of the strangest and most interesting segments of the technology industry. This week, it gets a little stranger as we hear that Siemens is planning to buy Mentor Graphics for $4.5 billion cash. Over the past few years, Mentor has survived multiple takeover attempts, including a $1.6B unsolicited offer from rival Cadence Design Systems in 2008, and a 2010 attack from activist investor Carl Icahn, a chapter the company finally closed by repurchasing half his stake (amounting to about 7% of the company) at the beginning of this year for $146M.


More New Memories

These Target XiP, IoT – Among Other Things

by Bryon Moyer

Seems like we’re never happy with our memories. No matter how hard we work, how clever we get, there’s always something left to be desired.

Which is why, of course, we have complicated system memory architectures mixing different memory types with different characteristics so that we can, as a whole, compensate for the deficiencies. Your typical computing platform contains three radically different types of memory: static, dynamic, and non-volatile (NVM) – and yet it’s still not satisfying.

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