Spectre And Meltdown: How Cache Works

The year so far has been filled with news of Spectre and Meltdown. These exploits take advantage of features like speculative execution, and memory access timing. What they have in common is the fact that all modern processors use cache to access memory faster. We’ve all heard of cache, but what exactly is it, and how does it allow our computers to run faster?

In the simplest terms, cache is a fast memory. Computers have two storage systems: primary storage (RAM) and secondary storage (Hard Disk, SSD). From the processor’s point of view, loading data or instructions from RAM is slow — the CPU has to wait and do nothing for 100 cycles or more while the data is loaded. Loading from disk is even slower; millions of cycles are wasted. Cache is a small amount of very fast memory which is used to hold commonly accessed data and instructions. This means the processor only has to wait for the cache to be loaded once. After that, the data is accessible with no waiting.

A common (though aging) analogy for cache uses books to represent data: If you needed a specific book to look up an important piece of information, you would first check the books on your desk (cache memory). If your book isn’t there, you’d then go to the books on your shelves (RAM). If that search turned up empty, you’d head over to the local library (Hard Drive) and check out the book. Once back home, you would keep the book on your desk for quick reference — not immediately return it to the library shelves. This is how cache reading works.

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They’re Putting Soy In Your Wires, Man

I’ve got a friend who tells me at every opportunity that soy is the downfall of humanity. Whatever ails us as a society, it’s the soy beans that did it. They increase violent tendencies, they make us fat and lazy, they run farmers out of business, and so on. He laments at how hard it is to find food that doesn’t include soy in some capacity, and for a while was resigned to eating nothing but chicken hot dogs and bags of frozen peas; anything else had unacceptable levels of the “Devil’s Bean”. Overall he’s a really great guy, kind of person who could fix anything with a roll of duct tape and a trip to the scrap pile, but you might think twice if he invites you over for dinner.

A column of soy soldiers stand at the ready.

So when he recently told me about all the trouble people are having with soy-based electrical wiring, I thought it was just the latest conspiracy theory to join his usual stories. I told him it didn’t make any sense, there’s no way somebody managed to develop a reliable soy-derived conductor. “No, no,” he says, “not the conductor. They are making the insulation out of soy, and animals are chewing through it.”

Now that’s a bit different. I was already well aware of the growing popularity of bioplastics: the PLA used in desktop 3D printers is one such example, generally derived from corn. It certainly wasn’t unreasonable to think somebody had tried to make “green” electrical wiring by using a bioplastic insulation. While I wasn’t about to sit down to a hot bag of peas for dinner, I had to admit that maybe in this case his claims deserved a look.

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Software Design Patterns For Real Hardware

Here on Hackaday, we’re generally designers of hacks that live in the real world. Nevertheless, I’m convinced that some of the most interesting feats are at the mercy of what’s possible in software, not hardware. Without the right software, no 3D printer could print and no quadcopter could fly. The source code that drives these machines may take months of refinement to flesh out their structure. In a nutshell, these software packages are complicated, and they don’t happen overnight.

So how do they happen; better yet: how could we make that happen? How do we write software that’s flexible enough to coexist peacefully on all sorts of hardware variations?

What separates the big open-source software projects like ROS, LinuxCNC, and Multiwii from the occastional hackathon code are the underlying principles that govern how they’re written. In object-oriented programming, these principles are called design patterns. In the next couple posts, I’m going to crack the lid on a few of these. What’s more, I’ll package them into real-world examples so that we can see these patterns interact with real hardware. The next time you pop open the source code for a big open source hardware project, I hope you can tease out some of these patterns in the code. Better yet, I hope you carry these patterns into your next robot and machine project. Let’s get started.

For readability, all of the examples run in Python3. The snippets below are truncated for brevity, but the real examples in the repository will work if you’ve got a similar hardware setup.

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Local Infrastructure: The Devil Is In The Details

About two months ago I rode my bike to work like any other day, but on the way home a construction project seemed to have spontaneously started at one of the bridges that I pass over. Three lanes had merged into one which, for a federal highway, seemed like a poorly planned traffic pattern for a such a major construction project. As it happens, about an hour after I biked across this bridge that morning both outside sections of the bridge fell into the water. There was no other physical damage that seemed to explain why parts of a bridge on U.S. 1 would suddenly collapse.

The intriguing thing about this bridge collapse was that the outer retaining wall and about half of the sidewalk on both the northbound side and the southbound side had fallen into the water at the same time. This likely wasn’t caused by something like a boat impact, car accident, or an overweight truck. Indeed, Florida Department of Transportation (FDOT) investigated the incident and found that two post tension wires that held these sections of the bridge together had failed, making it unsafe for pedestrians and bicyclists but also for any boaters below. Continue reading “Local Infrastructure: The Devil Is In The Details”

Spectre And Meltdown: Attackers Always Have The Advantage

While the whole industry is scrambling on Spectre, Meltdown focused most of the spotlight on Intel and there is no shortage of outrage in Internet comments. Like many great discoveries, this one is obvious with the power of hindsight. So much so that the spectrum of reactions have spanned an extreme range. From “It’s so obvious, Intel engineers must be idiots” to “It’s so obvious, Intel engineers must have known! They kept it from us in a conspiracy with the NSA!”

We won’t try to sway those who choose to believe in a conspiracy that’s simultaneously secret and obvious to everyone. However, as evidence of non-obviousness, some very smart people got remarkably close to the Meltdown effect last summer, without getting it all the way. [Trammel Hudson] did some digging and found a paper from the early 1990s (PDF) that warns of the dangers of fetching info into the cache that might cross priviledge boundaries, but it wasn’t weaponized until recently. In short, these are old vulnerabilities, but exploiting them was hard enough that it took twenty years to do it.

Building a new CPU is the work of a large team over several years. But they weren’t all working on the same thing for all that time. Any single feature would have been the work of a small team of engineers over a period of months. During development they fixed many problems we’ll never see. But at the end of the day, they are only human. They can be 99.9% perfect and that won’t be good enough, because once hardware is released into the world: it is open season on that 0.1% the team missed.

The odds are stacked in the attacker’s favor. The team on defense has a handful of people working a few months to protect against all known and yet-to-be discovered attacks. It is a tough match against the attackers coming afterwards: there are a lot more of them, they’re continually refining the state of the art, they have twenty years to work on a problem if they need to, and they only need to find a single flaw to win. In that light, exploits like Spectre and Meltdown will probably always be with us.

Let’s look at some factors that paved the way to Intel’s current embarrassing situation.

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You Got A 3D Printer, Now What?

Given the incredibly low prices on some of the models currently on the market, it’s more than likely a number of Hackaday readers have come out of the holiday season with a shiny new desktop 3D printer. It’s even possible some of you have already made the realization that 3D printing is a bit harder than you imagined. Sure the newer generation of 3D printers make it easier than ever, but it’s still not the same “click and forget” experience of printing on paper, for instance.

In light of this, I thought it might be nice to start off the new year with some advice for those who’ve suddenly found themselves lost in a forest of PLA. Some of this information may seem obvious to those of us who’ve spent years huddled over a print bed, but as with many technical pursuits, we tend to take for granted the knowledge gained from experience. For my own part, the challenges I faced years ago with my first wooden 3D printer were wholly different than what I imagined. I assumed that the real challenge would be getting the machine assembled and running, but the time it took to build the machine was nothing in comparison to the hours and hours of trial and error it took before I gained the confidence to really utilize the technology.

Of course, everyone’s experience is bound to be different, and we’d love to hear about yours in the comments. Grand successes, crushing defeats, and everything in between. It’s all part of the learning process, and all valuable information for those who are just starting out.

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The 348,296th Article About Cryptocurrency

The public has latched onto the recent market events with an intense curiosity brought about by a greed for instant riches. In the last year alone, the value of Bitcoin has risen by 1,731%. We’re talking gold rush V2.0, baby. Money talks, and with a resounding $615 billion held up in cryptocurrencies, it is clear why this is assuredly not the first cryptocurrency article you have read — maybe even today. An unfortunate side effect of mass interest in a subject is the wildfire-like spread of misinformation. So, what exactly is a blockchain, and what can you still do now that everyone has finally jumped on the cryptocurrency bandwagon?

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