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    <title>MongoDB Jira</title>
    <link>https://jira.mongodb.org</link>
    <description>This file is an XML representation of an issue</description>
    <language>en-us</language>    <build-info>
        <version>9.7.1</version>
        <build-number>970001</build-number>
        <build-date>13-04-2023</build-date>
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<item>
            <title>[SERVER-36151] GPU offloading</title>
                <link>https://jira.mongodb.org/browse/SERVER-36151</link>
                <project id="10000" key="SERVER">Core Server</project>
                    <description>&lt;p&gt;It would be nice to leverage the available and ever growing GPU resources available in machines in some fashion. It makes the most sense for heavy OLAP/Analytical queries &#8211; but the biggest internal feature we&apos;d need to add first is support for parallel query processing. Then the single user request can be divided up into N parts and executed in parallel by multiple threads, subsystems, or even &lt;span class=&quot;error&quot;&gt;&amp;#91;remote&amp;#93;&lt;/span&gt;&#160;processes. Then building on that, we could determine which parts would naturally perform well on GPU&apos;s &#8211; things like aggregations, sorting, grouping, etc. &#8211; and send that portion of the work to the GPU&apos;s using something like the CUDA API.&#160;&lt;/p&gt;</description>
                <environment></environment>
        <key id="572105">SERVER-36151</key>
            <summary>GPU offloading</summary>
                <type id="4" iconUrl="https://jira.mongodb.org/secure/viewavatar?size=xsmall&amp;avatarId=14710&amp;avatarType=issuetype">Improvement</type>
                                            <priority id="4" iconUrl="https://jira.mongodb.org/images/icons/priorities/minor.svg">Minor - P4</priority>
                        <status id="10038" iconUrl="https://jira.mongodb.org/images/icons/subtask.gif" description="">Backlog</status>
                    <statusCategory id="2" key="new" colorName="default"/>
                                    <resolution id="-1">Unresolved</resolution>
                                        <assignee username="backlog-query-execution">Backlog - Query Execution</assignee>
                                    <reporter username="dev.ashevchuk@gmail.com">Andrew Shevchuk</reporter>
                        <labels>
                            <label>parallel-processing</label>
                            <label>parallel-query</label>
                    </labels>
                <created>Mon, 16 Jul 2018 19:15:02 +0000</created>
                <updated>Tue, 6 Dec 2022 03:24:02 +0000</updated>
                                                                            <component>Querying</component>
                                        <votes>2</votes>
                                    <watches>13</watches>
                                                                                                                <comments>
                            <comment id="3322236" author="moroine.bentefrit@gmail.com" created="Wed, 5 Aug 2020 13:58:16 +0000"  >&lt;p&gt;&amp;gt;&#160;the biggest internal feature we&apos;d need to add first is support for parallel query processing&lt;/p&gt;

&lt;p&gt;It&apos;s actually what I&apos;m looking for. Currently, I have to split my aggregation pipeline into multiple smaller ones in order to speed up aggregation by using all available CPUs. The tradeoff is the result that need to be aggregated again manually in Javascript as I need to group...&lt;/p&gt;

&lt;p&gt;&#160;&lt;/p&gt;

&lt;p&gt;Do you have any ticket related to this feature which I can follow? I can&apos;t find anything related to this.&lt;/p&gt;

&lt;p&gt;&#160;&lt;/p&gt;

&lt;p&gt;Thanks,&lt;/p&gt;</comment>
                            <comment id="3216272" author="corporate.piyush@gmail.com" created="Sat, 20 Jun 2020 04:33:37 +0000"  >&lt;p&gt;Is this considered in any near future release ?&lt;/p&gt;

&lt;p&gt;Or at least MongoDB can exploit SIMD Vector Instruction at CPU level for queries and of course for aggregation pipeline.&#160;&lt;/p&gt;</comment>
                            <comment id="1961219" author="ashevchuk" created="Tue, 31 Jul 2018 11:03:41 +0000"  >&lt;p&gt;Yes, that&apos;s exactly what I thought.&lt;/p&gt;</comment>
                            <comment id="1958549" author="matt.lord" created="Fri, 27 Jul 2018 15:07:52 +0000"  >&lt;p&gt;Hi &lt;a href=&quot;https://jira.mongodb.org/secure/ViewProfile.jspa?name=ashevchuk&quot; class=&quot;user-hover&quot; rel=&quot;ashevchuk&quot;&gt;ashevchuk&lt;/a&gt;!&lt;/p&gt;

&lt;p&gt;Can you elaborate a bit on what you&apos;d like to see here?&lt;/p&gt;

&lt;p&gt;In the most abstract sense, of course we&apos;d like to leverage the available GPU resources in some fashion. It makes the most sense for heavy OLAP/Analytical queries &#8211; but the biggest internal feature we&apos;d need to add first is support for parallel query processing. Then the single request can be divided up into N parts and executed in parallel by multiple threads, subsystems, or even &lt;span class=&quot;error&quot;&gt;&amp;#91;remote&amp;#93;&lt;/span&gt;&#160;processes. Then building on that, we could determine which parts would naturally perform well on GPU&apos;s &#8211; things like aggregations, sorting, grouping, etc. &#8211; and send that portion of the work to the GPU&apos;s using something like the CUDA API.&#160;&lt;/p&gt;

&lt;p&gt;Is this essentially what you&apos;re thinking? If so, then I&apos;ll mark this as something we&apos;d eventually like to do.&#160;&lt;/p&gt;

&lt;p&gt;Thanks!&lt;/p&gt;

&lt;p&gt;Matt&lt;/p&gt;

&lt;p&gt;&#160;&lt;/p&gt;

&lt;p&gt;&#160;&lt;/p&gt;</comment>
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