
ARM Details “Project Trillium” Machine Learning Processor Architecture - signa11
https://www.anandtech.com/show/12791/arm-details-project-trillium-mlp-architecture
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joe_the_user
The more chip-makers in the "machine learning" space the better, I would say.
But I'd also hope for as much general purpose computing as possible.

Numeric convolution is just piece-wise vector multiplication and done a lot in
CNNs but it still seems more specialized than what a GPU has become - more or
less a glorified general purpose parallel processor using the SIMD model (in
Flynn's taxonomy).

[https://en.wikipedia.org/wiki/Flynn%27s_taxonomy](https://en.wikipedia.org/wiki/Flynn%27s_taxonomy)

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twtw
That's what I find particularly cool about stuff like nvidia DGX systems: they
are great at machine learning stuff, but they also have ridiculously high
performance for more traditional scientific computing (GROMACS, QUDA, etc). A
DGX-1V provides 50+ teraflops for fp64 at a price point that is within reach
for many university labs.

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geezerjay
> A DGX-1V provides 50+ teraflops for fp64 at a price point that is within
> reach for many university labs.

Universities do tend to have deep pockets, and research grants do tend to be
filed to max out the expenditure on equipment such as hardware. A university
being able to afford a piece of kit doesn't mean much about its affordability.

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dgacmu
Yeah.... Not so much. The only university labs I know that are using DGX had
them donated by Nvidia. For my lab, we cobble together consumer cards, as does
basically everyone else I know.

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twtw
As a point of interest, ARM is using NVIDIA's open source Deep Learning
Accelerator (NVDLA) IP in Project Trillium.

[https://nvidianews.nvidia.com/news/nvidia-and-arm-partner-
to...](https://nvidianews.nvidia.com/news/nvidia-and-arm-partner-to-bring-
deep-learning-to-billions-of-iot-devices)

[http://nvdla.org](http://nvdla.org)

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baybal2
There is more to it than this.

NVIDIA was rather vocal with "hey ARM, it is you who dragged us that into that
consumer market SoC epopeia in which we failed HARD, now we expect something
in return or we sever our relationship"

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elseless
ARM needs to get some skin in the accelerator game before RISC-V et. al.
commoditize its cash cow.

NVDLA is fairly permissively licensed (free for commercial use), but of course
Nvidia will steer the greater ecosystem around it. Perhaps ARM can be the Red
Hat to NVDLA's Linux, or something like that. Still seems a bit strange to me.

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phkahler
>> ARM needs to get some skin in the accelerator game before RISC-V et. al.
commoditize its cash cow.

For their own sake sure. I look forward to RISC-V taking over a large part of
the world ;-) The Esperanto chip looks so promising even without proprietary
extensions.

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chime
It says the processor is built for efficient convolutions. While that would be
great for CNNs, could the same be used to make RNNs more efficient? I.e. can
the problem of solving RNNs be reduced to solving CNNs?

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sanxiyn
No, it can't.

