Michael Steinhart

GPUs Deliver Supercharged Analytics

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Michael Steinhart
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Re: CPU v GPU
Michael Steinhart   6/30/2014 11:42:18 PM
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Thanks for the insight and welcome, Craigmeister. Gal did mention Teradata and Netezza several times in the interview, but I don't have apples-to-apples comparison numbers, so I didn't want to get too detailed on competing platforms.

Craigmeister
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Re: CPU v GPU
Craigmeister   6/30/2014 8:36:45 AM
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My impression was that the Sqream product is sort of a comoditized version of IBM's Netezza, which is a proprietary array of blade servers each with a programable processing card and its own storage. These are also very expensive.

Also, speaking of doing one thing well, video cards usually have hardware floating point processors (FPU) vs. the software FPU processing that exist in CPUs. This likely makes things like aggregation very fast.

SaneIT
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Re: CPU v GPU
SaneIT   6/30/2014 7:18:39 AM
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That is the answer at the lowest level.  If you're going to spend a lot of resources moving to a GPU based farm you have to weigh what you will actually be getting out.  Like any data project most times it is easier to optimize what you have than it is to re-tool.

Michael Steinhart
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Re: CPU v GPU
Michael Steinhart   6/28/2014 10:51:13 PM
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So the question for Sqream is, how much configuration and customization does your software need in order to work. Is it possible, though, that because it's handling traditional SQL queries, the process isn't as complicated as it might be with a more versatile tool?

SaneIT
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Re: CPU v GPU
SaneIT   6/27/2014 7:04:05 AM
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Yes middleware can be used to do the conversion but it's not like you just buy a software license, insert an install disk and the middleware installer wizard figures everything out.  That middleware has some heavy lifting to do and requires some quality time spent on configuration and optimization.

Michael Steinhart
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Re: CPU v GPU
Michael Steinhart   6/26/2014 2:27:05 PM
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Thanks for the insight - but isn't that what 'middleware' offerings like Sqream's are designed to do? Take an existing instruction set and parallelize it without any need for additional coding?

BethSchultz
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Re: CPU v GPU
BethSchultz   6/26/2014 8:10:31 AM
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Aha! I knew there was a catch, and rewriting apps to use with a GPU cluster certainly qualifies as one of them. Thanks SaneIT.

SaneIT
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Re: CPU v GPU
SaneIT   6/26/2014 7:15:18 AM
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I'm a techie first, so this falls right into my wheelhouse.  I have not used GPUs for analytics, my experience was rendering images and video for cinematic use in the gaming industry.  The concepts are the same, parallel data that needs to be blended into a singular data set.  The downside is that if you have a system in place currently that it is not likely to easily migrate from a CPU backed farm to a GPU backed farm.  Since GPUs are much simpler your application will have to be written specifically for use with a GPU cluster.  That can be a major undertaking.

BethSchultz
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Re: CPU v GPU
BethSchultz   6/25/2014 10:53:59 PM
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I don't know enough about the technology here myself, but given what we've learned so far from this post and the comments, I would suppose GPU architectures will remain a speciality in the data analytics realm if for no other reason than how entrenched the CPU is.

Michael Steinhart
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Re: CPU v GPU
Michael Steinhart   6/25/2014 10:21:58 PM
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My admittedly limited understanding is that, as long as the instructions are fairly simple and can run in parallel, GPUs are a superior architecture. They're designed to render high-resolution images in games, so they need to work fast.

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