

Ask HN: Are there new hardware startups working on new CPUs or GPUs? - frik

Are there hardware startup companies that designs a new CPU&#x2F;GPU that interrupts the status-quo. (3GHz in 2004, 3.8GHz in 2006, ~4GHz in 2014)<p>We had some in the 1990s like 3dfx (GPU) and Cyrix (CPU):<p>http:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;3dfx<p>http:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Cyrix<p>We had a discussion about it (as off-topic discussion) today: https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=7658275
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pjc50
There's the Mill CPU people, and I personally worked briefly with a small CPU
startup, and there are startup-ish IP core companies out there .. but it's an
_extremely_ hard market to enter.

Simply ramping up the clock speed is not going to happen much; the problem of
waiting for your data to traverse the huge distance from the socketed DRAM all
the way over to the processor is already severe.

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tachyonbeam
There's several factors making it hard to enter the CPU market besides
technical challenges. One is that there's so many offerings already, covering
various niches (embedded, DSP, desktop, mobile, server, GPUs), all with
existing toolchains. Another is that accessing a fabrication plant is
extremely expensive/difficult/lengthy. Then there's all the IP and lawyer
issues. And finally, I'd say that CPUs are mostly a "solved problem". Can we
make better CPUs? Sure. But can you get enough millions invested to develop a
whole new family of CPUs and hope to compete with what's out there? That's
going to be very very hard.

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rhb
Not a general purpose CPU/GPU, but related:
[http://www.nervanasys.com/](http://www.nervanasys.com/)

Founded by experts in machine learning, neuroscience, processor architecture,
and chip design, Nervana Systems is bringing unprecedented scale and
simplicity to the application of brain-inspired algorithms. Deep learning has
emerged as the leading strategy for making sense of a wide variety of data but
is very computationally intensive. We are developing a scalable hardware
solution to solve these types of problems. By making unsupervised learning
dramatically faster and more scalable, customers at all levels can derive
meaningful insights from their data, an ability previously available only to
an elite few companies.

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trsohmers
In semi-stealth mode, but currently working on a new floating point focused
architecture that is rethinking a lot of concepts in order to focus on energy
efficiency in the high performance computing space. The biggest problem
historically has been software development related, as even if you have a
kickass new architecture, if you can't write software for it, it is worthless.
Thankfully we think we have a pretty good solution to this.

