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The Era of Error-Tolerant Computing

Errors will abound in future processors...and that's okay

3 min read

The computer's perfectionist streak is coming to an end. Speaking at the International Symposium on Low Power electronics and Design, experts said power consumption concerns are driving computing toward a design philosophy in which errors are either allowed to happen and ignored, or corrected only where necessary. Probabilistic outcomes will replace the deterministic form of data processing that has prevailed for the last half century.

Naresh Shanbhag, a professor in the department of electrical and computer engineering at the University of Illinois at Urbana-Champaign, refers to error-resilient computing (also called probabilistic computing) by the more formal name of stochastic processing. Whatever the name, the approach, Shanbhag says, is not to automatically circle back and correct errors once they are identified, because that consumes power. "If the application is such that small errors can be tolerated, we let them happen," he says. "Depending on the application, we keep error rates under a threshold, using algorithmic or circuit techniques." For many applications such as graphics processing or drawing inferences from huge amounts of data, errors in reasonable numbers do not materially impact the quality of the results. After all, your eye wouldn't even notice the presence of a single bad pixel in most images.

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3 Ways 3D Chip Tech Is Upending Computing

AMD, Graphcore, and Intel show why the industry’s leading edge is going vertical

8 min read
A stack of 3 images.  One of a chip, another is a group of chips and a single grey chip.
Intel; Graphcore; AMD

A crop of high-performance processors is showing that the new direction for continuing Moore’s Law is all about up. Each generation of processor needs to perform better than the last, and, at its most basic, that means integrating more logic onto the silicon. But there are two problems: One is that our ability to shrink transistors and the logic and memory blocks they make up is slowing down. The other is that chips have reached their size limits. Photolithography tools can pattern only an area of about 850 square millimeters, which is about the size of a top-of-the-line Nvidia GPU.

For a few years now, developers of systems-on-chips have begun to break up their ever-larger designs into smaller chiplets and link them together inside the same package to effectively increase the silicon area, among other advantages. In CPUs, these links have mostly been so-called 2.5D, where the chiplets are set beside each other and connected using short, dense interconnects. Momentum for this type of integration will likely only grow now that most of the major manufacturers have agreed on a 2.5D chiplet-to-chiplet communications standard.

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