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Port DSS to ARM / Apple Silicon

This may be too obvious : 

User Story: As a Macintosh user who has enjoyed using DSS on my local computer, it would be great to use Dataiku DSS on a New Apple Silicon Computer. 

Value Proposition: 

  1. Having DSS working on Macintosh Computers has been an excellent entry point for folks interested in using DSS.  Installing DSS has been easy.  In two or three years Dataiku will lose this advantage of the ease of entry if it only supports Intel Computers.  
  2. Given the significant CPU & GPU performance gains in the first generation of the Apple M1 chip, it is likely that Apple’s Macintosh will be a performance leader in the laptop and desktop space for several years to come.
  3. Give the custom Neural Network Processor in the Apple Silicon Chips it is likely that there will be development that can uniquely be done within the M1 Macintosh environment. 

 

5 Comments
tgb417
Neuron
Neuron

Here is a link to an eager person asking about DSS on Apple Silicon.  

 

https://community.dataiku.com/t5/Setup-Configuration/DSS-on-ARM-or-AMD-Ryzan-9-Processors/m-p/9795/h...

tgb417
Neuron
Neuron
fsergot
Dataiker
Dataiker
Status changed to: In Backlog

Hello,

this support is indeed in our radar since the announcement from Apple, As said in the link, this is far from trivial but we know the importance of the Mac users community around DSS

DMKnemeijer
Level 2
Level 2

I support this! Not only would this enable Mac users to install Dataiku on their machines, but this will also allow us to migrate our Cloud Dataiku installation over to EC2 instances that are using the newer, ARM-based Graviton processors, which would lead to a much better price/performance 

natejgardner
Level 6

It would be great to be able to install Dataiku on ARM devices without Intel emulation.

Marvell and Ampere servers are rising in popularity in enterprise. Microsoft is also rumored to be working on ARM server hardware. ARM laptops are also becoming very popular, where users may like to install Dataiku locally for offline/local convenient data processing ability (I'm in that camp). This would be especially nice for mobility, especially when using limited mobile data plans. Running on locally on a Surface device or a Chromebook would be awesome for doing quick data exploration, validation, and processing on the go without needing to upload a large dataset to a server (e.g. field service type data analysis use-cases).