<story><title>BlazingDB uses GPUs to manipulate huge databases in no time</title><url>https://techcrunch.com/2016/09/12/blazingdb-uses-gpus-to-manipulate-huge-databases-in-no-time/</url></story><parent_chain><item><author>hendzen</author><text>This has been tried many times. Unless you are doing a computation with sufficient arithmetic intensity [0] the cost of shipping the data over PCIe and back dominates any gain you might get over a CPU.&lt;p&gt;[0] - &lt;a href=&quot;http:&amp;#x2F;&amp;#x2F;www.nersc.gov&amp;#x2F;users&amp;#x2F;application-performance&amp;#x2F;measuring-arithmetic-intensity&amp;#x2F;&quot; rel=&quot;nofollow&quot;&gt;http:&amp;#x2F;&amp;#x2F;www.nersc.gov&amp;#x2F;users&amp;#x2F;application-performance&amp;#x2F;measuring...&lt;/a&gt;</text></item></parent_chain><comment><author>felipe_aramburu</author><text>Seems kind of like a blanket statement to make if you have not investigated this for yourself. So let me give you some example use cases.&lt;p&gt;Decompression for processing:
We can roundtrip decompress 8 byte integers RRleDeltaRle 4x on an AWS g2.2xlarge faster when we use the GPU. This includes sending the data TO the GPU and brining it back. Our decompression segments on CPU were set up so that every thread was processing a segment to be decompressed so we were using every avaiable thread at about 100%.&lt;p&gt;Sorting data:
Here the difference can be startling. On an aws g2.2xlarge we are able to sort  orders of magnitude faster than you can on GPU. Checkout thrust to run some exmaples 
&lt;a href=&quot;http:&amp;#x2F;&amp;#x2F;docs.nvidia.com&amp;#x2F;cuda&amp;#x2F;thrust&amp;#x2F;#axzz4K7CRY352&quot; rel=&quot;nofollow&quot;&gt;http:&amp;#x2F;&amp;#x2F;docs.nvidia.com&amp;#x2F;cuda&amp;#x2F;thrust&amp;#x2F;#axzz4K7CRY352&lt;/a&gt;&lt;p&gt;A few modifications there can let you run this with both and NVIDIA backend and one that runs on CPU threads. It will run orders of magnitude faster on GPU than CPU on a small gpu instance on amazon. Even a laptop gpu would still outperform the cpu sorting capacity by at least an order of magnitude.</text></comment>
<story><title>BlazingDB uses GPUs to manipulate huge databases in no time</title><url>https://techcrunch.com/2016/09/12/blazingdb-uses-gpus-to-manipulate-huge-databases-in-no-time/</url></story><parent_chain><item><author>hendzen</author><text>This has been tried many times. Unless you are doing a computation with sufficient arithmetic intensity [0] the cost of shipping the data over PCIe and back dominates any gain you might get over a CPU.&lt;p&gt;[0] - &lt;a href=&quot;http:&amp;#x2F;&amp;#x2F;www.nersc.gov&amp;#x2F;users&amp;#x2F;application-performance&amp;#x2F;measuring-arithmetic-intensity&amp;#x2F;&quot; rel=&quot;nofollow&quot;&gt;http:&amp;#x2F;&amp;#x2F;www.nersc.gov&amp;#x2F;users&amp;#x2F;application-performance&amp;#x2F;measuring...&lt;/a&gt;</text></item></parent_chain><comment><author>gfody</author><text>Seems like a great application of AMD&amp;#x27;s Fiji GPU w&amp;#x2F;onboard flash: &lt;a href=&quot;http:&amp;#x2F;&amp;#x2F;www.anandtech.com&amp;#x2F;show&amp;#x2F;10518&amp;#x2F;amd-announces-radeon-pro-ssg-fiji-with-m2-ssds-onboard&quot; rel=&quot;nofollow&quot;&gt;http:&amp;#x2F;&amp;#x2F;www.anandtech.com&amp;#x2F;show&amp;#x2F;10518&amp;#x2F;amd-announces-radeon-pro...&lt;/a&gt;</text></comment>