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Meet Snitch: the Small and Agile RISC-V Processor

Tests suggest it is six times faster than other comparable processors

2 min read
​Test chip showing a 24-core Snitch system.

Test chip showing a 24-core Snitch system.

Zaruba et al.

This article is part of our exclusive IEEE Journal Watch series in partnership with IEEE Xplore.

As society's insatiable demand for computing power continues to grow, so too does the need for more efficient processors. A group of researchers in Switzerland has devised a new processor design that may help meet our computational-intensive needs. It is physically small and computationally agile—and aptly named Snitch. (Harry Potter fans will get the reference.)

Florian Zaruba, a postdoc at the Integrated Systems Laboratory at the Swiss Federal Institute of Technology (ETH) in Zürich—and a researcher involved in the creation of Snitch—notes that there's a trend with commercial, general-purpose cores, which are relying on larger and more energy-hungry processors. "Snitch is the opposite," he says.

Typically, processors try to find an efficient instruction order on the fly, which requires additional hardware and thus uses more power. But Snitch is able to execute the majority of its basic instructions instantaneously, bypassing the need for this extra, burdensome hardware.

Because of this efficient computing approach, Snitch—built around the streamlined, RISC-V chip architecture—can perform most basic instructions within a single clock cycle. As well, it was designed to execute longer latency instructions without stalling and waiting for their completion. "This leads to a very compact and high-performance design compared to conventional processors that achieve high performance," explains Zaruba.

Zaruba and his colleagues describe their design in a study published October 7 in IEEE Transactions on Computers, where they compared it to other benchmark designs. They found that a single Snitch processor with its custom extensions was two times more energy efficient than the other processors analyzed in the study. When multiple processors were used in parallel, Snitch proved to be 3.5 times more energy efficient and up to six times faster than the others.

Notably, there are other hardware components, such as GPUs, that also outperform standard processors in computing speed—but such feats tend to be for highly specialized tasks. Snitch, on the other hand, is much more versatile, performing a variety of tasks while still executing calculations quickly and efficiently.

On the other hand, Zaruba notes, Snitch is more complicated to program. Still, he says that he strongly believes energy efficiency will be the number one priority for next generation computers, and that Snitch's energy efficiency will make it appealing despite its more complex programming requirements.

The researchers have made Snitch's hardware design freely available, and note that they have seen growing interest from industry consortia, for example from the Open Hardware Group, in supporting commercialization efforts.

Moving forward, the team plans to build larger systems based on Snitch. "While we could already demonstrate a very energy-efficient and versatile 8-core Snitch cluster configuration in silicon, there are exciting opportunities ahead in building computing platforms scalable to thousands of Snitch cores, even spreading over multiple chiplets," says Zaruba, noting that his team is currently working towards this goal.

This article appears in the January 2022 print issue as "This RISC-V Powerhouse Goes Light on the Power."

The Conversation (0)
Illustration showing an astronaut performing mechanical repairs to a satellite uses two extra mechanical arms that project from a backpack.

Extra limbs, controlled by wearable electrode patches that read and interpret neural signals from the user, could have innumerable uses, such as assisting on spacewalk missions to repair satellites.

Chris Philpot

What could you do with an extra limb? Consider a surgeon performing a delicate operation, one that needs her expertise and steady hands—all three of them. As her two biological hands manipulate surgical instruments, a third robotic limb that’s attached to her torso plays a supporting role. Or picture a construction worker who is thankful for his extra robotic hand as it braces the heavy beam he’s fastening into place with his other two hands. Imagine wearing an exoskeleton that would let you handle multiple objects simultaneously, like Spiderman’s Dr. Octopus. Or contemplate the out-there music a composer could write for a pianist who has 12 fingers to spread across the keyboard.

Such scenarios may seem like science fiction, but recent progress in robotics and neuroscience makes extra robotic limbs conceivable with today’s technology. Our research groups at Imperial College London and the University of Freiburg, in Germany, together with partners in the European project NIMA, are now working to figure out whether such augmentation can be realized in practice to extend human abilities. The main questions we’re tackling involve both neuroscience and neurotechnology: Is the human brain capable of controlling additional body parts as effectively as it controls biological parts? And if so, what neural signals can be used for this control?

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