CN109426652A - 用于大数据分析加速器的技术 - Google Patents

用于大数据分析加速器的技术 Download PDF

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Publication number
CN109426652A
CN109426652A CN201811006539.2A CN201811006539A CN109426652A CN 109426652 A CN109426652 A CN 109426652A CN 201811006539 A CN201811006539 A CN 201811006539A CN 109426652 A CN109426652 A CN 109426652A
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China
Prior art keywords
output
database
decompressed
elements
calculating equipment
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CN201811006539.2A
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English (en)
Inventor
V·戈帕尔
J·D·吉尔福德
K·S·雅普
S·N·佩菲尔斯
D·F·卡特
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Intel Corp
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Intel Corp
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Priority claimed from US15/719,774 external-priority patent/US10628068B2/en
Application filed by Intel Corp filed Critical Intel Corp
Publication of CN109426652A publication Critical patent/CN109426652A/zh
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Abstract

用于数据库加速的技术包括具有数据库加速器的计算设备。数据库加速器对经压缩的数据库中的一个或多个经压缩的元素执行解压缩操作，以生成一个或多个经解压缩的元素。在对经压缩的元素进行解压缩之后，数据库加速器对一个或多个经解压缩的元素进行准备，以生成要由加速的过滤进行处理的一个或多个准备好的元素。然后，数据库加速器对一个或多个准备好的元素执行加速的过滤，以生成一个或多个输出元素。描述并要求保护其他实施例。

Description

用于大数据分析加速器的技术
相关申请的交叉引用
本申请要求于2016年11月29日提交的美国临时专利申请第62/427,268号以及于2017年8月30日提交的印度临时专利申请第201741030632号的权益。
背景技术
现代计算设备可以包括通用处理器核以及用于执行专门任务的各种硬件加速器。某些计算设备可以包括体现为现场可编程门阵列(FPGA)的一个或多个加速器，其可以包括可以由最终用户或系统集成商配置的可编程数字逻辑资源。
附图说明
本文中描述的概念在附图中通过示例的方式而不是通过限制的方式示出。为了说明的简单和清楚，附图中示出的元素不一定按比例绘制。在认为合适的情况下，在附图中重复附图标记以指示对应或类似的元素。
图1是根据各种实施例的其中可以实现本文中描述的一种或多种技术的数据中心的概念性概述的图；
图2是图1的数据中心的机架的逻辑配置的示例实施例的图；
图3是根据各种实施例的其中可以实现本文中描述的一种或多种技术的另一数据中心的示例实施例的图；
图4是根据各种实施例的其中可以实现本文中描述的一种或多种技术的数据中心的另一示例实施例的图；
图5是表示可以在图1、图3和图4的数据中心的各种托架(sled)之中建立的链路层连接的连接方案的图；
图6是根据一些实施例的可以表示图1-4中描绘的机架中的任何特定的一个机架的架构的机架架构的图；
图7是可以与图6的机架架构一起使用的托架的示例实施例的图；
图8是用于对以扩展能力为特征的托架提供支持的机架架构的示例实施例的图；
图9是根据图8的机架架构实现的机架的示例实施例的图；
图10是设计用于与图9的机架结合使用的托架的示例实施例的图；
图11是根据各种实施例的其中可以实现本文中描述的一种或多种技术的数据中心的示例实施例的图；
图12是用于数据库加速的计算设备的至少一个实施例的简化框图；
图13是可以由图12的计算设备的加速器建立的环境的至少一个实施例的简化框图；以及
图14是可以由图12-13的计算设备执行的用于数据库加速的方法的至少一个实施例的简化流程图。
具体实施方式
虽然本公开的概念易于具有各种修改和替代形式，但是其具体实施例已经通过示例的方式在附图中示出并且将在本文中详细描述。然而，应当理解，并不旨在将本公开的概念限制于所公开的特定形式，而是相反，意图是覆盖与本公开和所附权利要求一致的所有修改、等同物和替代方案。
说明书中对“一个实施例”、“实施例”、“说明性实施例”等的引用指示所描述的实施例可以包括特定特征、结构或特性，但是每个实施例可以一定或可以不一定包括该特定特征、结构或特性。此外，这些短语不一定指代同一实施例。此外，当结合实施例描述特定特征、结构或特性时，认为结合其他实施例实现这样的特征、结构或特性在本领域技术人员的知识范围内，而无论是否未明确描述。另外，应当意识到，以“至少一个A、B和C”的形式包括在列表中的项目可以表示(A)；(B)；(C)；(A和B)；(A和C)；(B和C)；或(A、B和C)。类似地，以“A、B或C中的至少一个”的形式列出的项目可以表示(A)；(B)；(C)；(A和B)；(A和C)；(B和C)；或(A、B和C)。
在一些情况下，所公开的实施例可以以硬件、固件、软件或其任何组合来实现。所公开的实施例还可以实现为由暂时性或非暂时性机器可读(例如，计算机可读)存储介质携带或存储在其上的指令，这些指令可以由一个或多个处理器读取和执行。机器可读存储介质可以体现为用于以机器可读形式存储或传输信息的任何存储设备、机构或其他物理结构(例如，易失性或非易失性存储器、介质盘或其他介质设备)。
在附图中，可以以特定布置和/或顺序示出一些结构或方法特征。然而，应当意识到，可能不要求这样的特定布置和/或排序。而是，在一些实施例中，这些特征可以以不同于说明性附图中所示的方式和/或顺序来布置。另外，在特定附图中包含结构或方法特征并不意味着暗示在所有实施例中都要求这样的特征，并且在一些实施例中，可以不包括这些特征或者可以将这些特征与其他特征组合。
图1示出了根据各种实施例的数据中心100的概念性概述，该数据中心100通常可以表示其中/对其而言可以实现本文中描述的一种或多种技术的数据中心或其他类型的计算网络。如图1所示，数据中心100通常可以包含多个机架，其中的每个机架可以存放包括相应的一组物理资源的计算设备。在图1中描绘的特定非限制性示例中，数据中心100包含四个机架102A至102D，其存放包括相应的各组物理资源105A至105D的计算设备。根据该示例，数据中心100的共同的一组物理资源106包括分布在机架102A至102D之中的各组物理资源105A至105D。物理资源106可以包括多种类型的资源，例如，处理器、协处理器、加速器、现场可编程门阵列(FPGA)、存储器和存储装置。实施例不限于这些示例。
说明性数据中心100在许多方面不同于典型的数据中心。例如，在说明性实施例中，其上放置诸如CPU、存储器和其他组件之类的组件的电路板(“托架”)被设计用于提高热性能。特别地，在说明性实施例中，托架比典型的板浅。换言之，托架从前到后更短，冷却风扇位于其中。这减少了空气必须穿过板上的组件的路径的长度。此外，托架上的组件与典型的电路板相比间隔得更远，并且这些组件被布置为减少或消除遮蔽(即，一个组件在另一组件的空气流动路径中)。在说明性实施例中，诸如处理器之类的处理组件位于托架的顶侧，而诸如双列直插存储器模块(DIMM)之类的附近存储器位于托架的底侧。由于该设计提供的增强空气流动，组件可以以比典型系统高的频率和功率水平操作，从而提高性能。此外，托架被配置为与每个机架102A、102B、102C、102D中的电力和数据通信电缆盲配合，增强了机架被快速移除、升级、重新安装和/或更换的能力。类似地，位于托架上的个体组件(例如，处理器、加速器、存储器和数据存储驱动器)被配置为由于其彼此间隔增加而容易升级。在说明性实施例中，组件另外包括硬件证实特征以证明其真实性。
此外，在说明性实施例中，数据中心100利用支持多个其他网络架构(包括以太网和Omni-Path)的单个网络架构(“结构”)。在说明性实施例中，托架经由光纤耦合到交换机，光纤相比典型的双绞线布线(例如，类别5、类别5e、类别6等)提供更高的带宽和更低的延迟。由于高带宽、低延迟互连和网络架构，数据中心100可以在使用中将物理地分解的资源(例如，存储器、加速器(例如，图形加速器、FPGA、专用集成电路(ASIC)等)以及数据存储驱动器)池化，并且基于需要将其提供给计算资源(例如，处理器)，使得计算资源能够访问池化的资源，就好像这些资源在本地一样。说明性数据中心100另外接收各种资源的使用情况信息，基于过去的资源使用情况来预测不同类型的工作负荷的资源使用情况，并且基于该信息来动态地重新分配资源。
数据中心100的机架102A、102B、102C、102D可以包括便于将各种类型的维护任务自动化的物理设计特征。例如，数据中心100可以使用这样的机架来实现：这些机架被设计为是机器人化地访问的并且接受和存放可机器人化地操纵的资源托架。此外，在说明性实施例中，机架102A、102B、102C、102D包括集成电源，其接收比对电源而言典型的电压更大的电压。增加的电压使得电源能够向每个托架上的组件提供附加的电力，使得组件能够以高于典型频率的频率进行操作。
图2示出了数据中心100的机架202的示例性逻辑配置。如图2所示，机架202通常可以存放多个托架，其中的每个托架可以包括相应的一组物理资源。在图2中描绘的特定非限制性示例中，机架202存放包括相应的各组物理资源205-1至205-4的托架204-1至204-4，这些物理资源中的每个构成包括在机架202中的共同的一组物理资源206的一部分。关于图1，如果机架202表示例如机架102A，则物理资源206可以对应于机架102A中包括的物理资源105A。在该示例的上下文中，物理资源105A因此可以由相应的各组物理资源组成，包括包含在机架202的托架204-1至204-4中的物理存储装置资源205-1、物理加速器资源205-2、物理存储器资源205-3和物理计算资源205-5。实施例不限于此示例。每个托架可以包含各种类型的物理资源(例如，计算、存储器、加速器、存储装置)中的每种类型的物理资源的池。通过使可机器人化地访问和可机器人化地操纵的托架包括分解的资源，每种类型的资源能够彼此独立地并且以其自己的优化刷新速率进行升级。
图3示出了根据各种实施例的数据中心300的示例，该数据中心300通常可以表示其中/对其而言可以实现本文中描述的一种或多种技术的数据中心。在图3中描绘的特定非限制性示例中，数据中心300包括机架302-1至302-32。在各种实施例中，数据中心300的机架可以以限定和/或容纳各种访问路径的方式来布置。例如，如图3所示，数据中心300的机架可以以限定和/或容纳访问路径311A、311B、311C和311D的方式来布置。在一些实施例中，这种访问路径的存在通常可以使得自动化维护设备(例如，机器人化维护设备)能够物理地访问存放在数据中心300的各种机架中的计算设备并执行自动化维护任务(例如，替换故障的托架，升级托架)。在各种实施例中，可以选择访问路径311A、311B、311C和311D的尺寸，机架302-1至302-32的尺寸和/或数据中心300的物理布局的一个或多个其他方面，以促进这种自动化操作。实施例不限于此上下文。
图4示出了根据各种实施例的数据中心400的示例，该数据中心400通常可以表示其中/对其而言可以实现本文中描述的一种或多种技术的数据中心。如图4所示，数据中心400可以以光结构412为特征。光结构412通常可以包括光信令介质(例如，光布线)和光交换基础设施的组合，数据中心400中的任何特定托架可以经由其向数据中心400中的其他托架中的每个托架发送信号(并且从数据中心400中的其他托架中的每个托架接收信号)。光结构412向任何给定托架提供的信令连接可以包括到同一机架中的其他托架和其他机架中的托架的连接。在图4中描绘的特定非限制性示例中，数据中心400包括四个机架402A至402D。机架402A至402D存放相应的托架对404A-1和404A-2、404B-1和404B-2、440C-1和404C-2以及404D-1和404D-2。因此，在该示例中，数据中心400包括总共八个托架。经由光结构412，每个这样的托架可以具有与数据中心400中的七个其他托架中的每个托架的信令连接。例如，经由光结构412，机架402A中的托架404A-1可以具有与机架402A中的托架404A-2以及分布在数据中心400的其他机架402B、402C和402D之中的六个其他托架404B-1、404B-2、440C-1、440C-2、440D-1和404D-2的信令连接。实施例不限于此示例。
图5示出了连接方案500的概述，该连接方案500通常可以表示在一些实施例中可以在数据中心(例如，图1、图3和图4的示例数据中心100、300和400中的任何一个)的各种托架之中建立的链路层连接。可以使用以双模光交换基础设施514为特征的光结构来实现连接方案500。双模光交换基础设施514通常可以包括能够根据多个链路层协议经由相同统一的一组光信令介质接收通信并且适当地交换这种通信的交换基础设施。在各种实施例中，可以使用一个或多个双模光交换机515来实现双模光交换基础设施514。在各种实施例中，双模光交换机515通常可以包括高基数交换机。在一些实施例中，双模光交换机515可以包括多层交换机，例如，四层交换机。在各种实施例中，双模光交换机515可以以集成硅光子为特征，与常规交换设备相比，使得双模光交换机515能够以显著减少的延迟交换通信。在一些实施例中，双模光交换机515可以以叶-脊架构构成叶交换机530，另外包括一个或多个双模光脊交换机520。
在各种实施例中，双模光交换机能够经由光结构的光信令介质接收携带互联网协议(IP分组)的以太网协议通信和根据第二、高性能计算(HPC)链路层协议(例如，Intel的Omni-Path架构，Infiniband)的通信两者。如图5关于具有到光结构的光信令连接的任何特定托架对504A和504B所反映的，连接方案500因此可以经由以太网链路和HPC链路两者对链路层连接提供支持。因此，单个高带宽、低延迟交换结构可以支持以太网通信和HPC通信两者。实施例不限于此示例。
图6示出了根据一些实施例的机架架构600的总体概述，该机架架构600可以表示图1至图4中描绘的机架中的任何特定的一个机架的架构。如图6所反映的，机架架构600通常可以以多个托架空间为特征，托架可以插入托架空间中，托架空间中的每个可以是经由机架访问区域601可机器人化地访问的。在图6中描绘的特定非限制性示例中，机架架构600以五个托架空间603-1至603-5为特征。托架空间603-1至603-5以相应的多目的连接器模块(MPCM)616-1至616-5为特征。
图7示出了托架704的示例，托架704可以表示这种类型的托架。如图7所示，托架704可以包括一组物理资源705以及MPCM 716，MPCM 716被设计为当托架704插入托架空间(例如，图6中的托架空间603-1至603-5中的任一个)时与配对MPCM耦合。托架704还可以以扩展连接器717为特征。扩展连接器717通常可以包括插座、插槽或其他类型的连接元件，其能够接受一种或多种类型的扩展模块(例如，扩展托架718)。通过与扩展托架718上的配对连接器耦合，扩展连接器717可以为物理资源705提供对驻留在扩展托架718上的补充计算资源705B的访问。实施例不限于此上下文。
图8示出了机架架构800的示例，该机架架构800可以表示可以被实现以便对以扩展能力为特征的托架(例如，图7的托架704)提供支持的机架架构。在图8中描绘的特定非限制性示例中，机架架构800包括七个托架空间803-1至803-7，其以相应的MPCM 816-1至816-7为特征。托架空间803-1至803-7包括相应的主区域803-1A至803-7A和相应的扩展区域803-1B至803-7B。关于每个这样的托架空间，当对应的MPCM与插入的托架的配对MPCM耦合时，主区域通常可以构成托架空间中的物理地容纳插入的托架的区域。在插入的托架配置有扩展模块的情况下，扩展区域通常可以构成托架空间中的可以物理地容纳这种模块(例如，图7的扩展托架718)的区域。
图9示出了根据一些实施例的机架902的示例，该机架902可以表示根据图8的机架架构800实现的机架。在图9中描绘的特定非限制性示例中，机架902以七个托架空间903-1至903-7为特征，其包括相应的主区域903-1A至903-7A和相应的扩展区域903-1B至903-7B。在各种实施例中，可以使用空气冷却系统来实现机架902中的温度控制。例如，如图9中所反映的，机架902可以以多个风扇919为特征，多个风扇919通常布置为在各种托架空间903-1至903-7内提供空气冷却。在一些实施例中，托架空间的高度大于常规的“1U”服务器高度。在这样的实施例中，与常规机架配置中使用的风扇相比，风扇919通常可以包括相对慢的大直径冷却风扇。相对于以较高速度运行的较小直径的冷却风扇，以较低速度运行较大直径的冷却风扇可以增加风扇寿命，同时仍提供相同的冷却量。托架比常规的机架尺寸在物理上更浅。此外，在每个托架上布置组件以减少热遮蔽(即，没有沿空气流动方向串联地布置)。因此，更宽、更浅的托架允许提高设备性能，因为由于改进的冷却，设备可以在更高的热封套(例如，250W)下操作(即，没有热遮蔽，设备之间有更多空间，对于较大的散热器有更多余地等)。
MPCM 916-1至916-7可以被配置为向插入的托架提供对由相应的电力模块920-1至920-7源送的电力的访问，其中的每个电力模块可以从外部电源921汲取电力。在各种实施例中，外部电源921可以向机架902输送交流(AC)电力，并且电力模块920-1至920-7可以被配置为将这种AC电力转换为直流(DC)电力以供源送至插入的托架。在一些实施例中，例如，电力模块920-1至920-7可以被配置为将277伏AC电力转换为12伏DC电力，以经由相应的MPCM 916-1至916-7提供给插入的托架。实施例不限于此示例。
MPCM 916-1至916-7还可以布置为向插入的托架提供与双模光交换基础设施914的光信令连接，双模光交换基础设施914可以与图5的双模光交换基础设施514相同或相似。在各种实施例中，包含在MPCM 916-1至916-7中的光连接器可以被设计为与插入的托架的MPCM中包含的配对光连接器耦合，以经由相应长度的通过光布线922-1至922-7向这种托架提供与双模光交换基础设施914的光信令连接。在一些实施例中，每个这种长度的光布线可以从其对应的MPCM延伸到在机架902的托架空间外部的光互连织机923。在各种实施例中，光互连织机923可以布置为穿过支撑柱或支架902的其他类型的负载承载元件。实施例不限于此上下文。由于插入的托架经由MPCM连接到光交换基础设施，因此可以节省典型地耗费在手动配置机架布线以容纳新插入的托架方面的资源。
图10示出了根据一些实施例的托架1004的示例，该托架1004可以表示设计用于与图9的机架902结合使用的托架。托架1004可以以MPCM1016为特征，MPCM 1016包括光连接器1016A和电力连接器1016B，并且被设计为与将MPCM 1016插入到托架空间中相结合而与托架空间的配对MPCM耦合。将MPCM 1016与这样的配对MPCM耦合可以使电力连接器1016与配对MPCM中包括的电力连接器耦合。这通常可以使得托架1004的物理资源1005能够经由电力连接器1016和电力传输介质1024从外部源来源送电力，电力传输介质1024将电力连接器1016导电地耦合到物理资源1005。
托架1004还可以包括双模光网络接口电路1026。双模光网络接口电路1026通常可以包括能够根据图9的双模光交换基础设施914支持的多个链路层协议中的每个通过光信令介质进行通信的电路。在一些实施例中，双模光网络接口电路1026能够进行以太网协议通信和根据第二、高性能协议的通信两者。在各种实施例中，双模光网络接口电路1026可以包括一个或多个光收发器模块1027，其中的每个光收发器模块1027能够通过一个或多个光通道中的每个光通道发送和接收光信号。实施例不限于此上下文。
将MPCM 1016与给定机架中的托架空间的配对MPCM耦合可以使光连接器1016A与配对MPCM中包括的光连接器耦合。这通常可以经由一组光通道1025中的每个光通道1025在托架的光布线与双模光网络接口电路1026之间建立光连接。双模光网络接口电路1026可以经由电信令介质1028与托架1004的物理资源1005进行通信。除了托架的尺寸和组件在托架上的布置用于提供改进的冷却并且使得能够在相对较高的热封套(例如，250W)下操作之外，如上面参考图9描述的，在一些实施例中，托架可以包括一个或多个附加特征以便于空气冷却，例如，布置为消散由物理资源1005产生的热量的热管和/或散热器。值得注意的是，尽管图10中所描绘的示例托架1004不以扩展连接器为特征，但是根据一些实施例以托架1004的设计元件为特征的任何给定托架也可以以扩展连接器为特征。实施例不限于此上下文。
图11示出了根据各种实施例的数据中心1100的示例，该数据中心1100通常可以表示其中/对其而言可以实现本文中描述的一种或多种技术的数据中心。如图11所反映的，可以实现物理基础设施管理框架1150A以便于管理数据中心1100的物理基础设施1100A。在各种实施例中，物理基础设施管理框架1150A的一个功能可以是管理数据中心1100内的自动化维护功能，例如，使用机器人化的维护设备来对物理基础设施1100A内的计算设备进行检修。在一些实施例中，物理基础设施1100A可以以高级遥测系统为特征，该高级遥测系统执行足够鲁棒以支持对物理基础设施1100A的远程自动化管理的遥测报告。在各种实施例中，由这种高级遥测系统提供的遥测信息可以支持诸如故障预测/预防能力和容量规划能力之类的特征。在一些实施例中，物理基础设施管理框架1150A还可以被配置为使用硬件证实技术来管理对物理基础设施组件的认证。例如，机器人可以在安装之前通过分析从与要安装的每个组件相关联的射频识别(RFID)标签收集的信息来验证组件的真实性。实施例不限于此上下文。
如图11所示，数据中心1100的物理基础设施1100A可以包括光结构1112，其可以包括双模光交换基础设施1114。光结构1112和双模光交换基础设施1114可以分别与图4的光结构412和图5的双模光交换基础设施514相同或相似，并且可以在数据中心1100的托架之中提供高带宽、低延迟、多协议连接。如上面参考图1讨论的，在各种实施例中，这种连接的可用性可以使得分解和动态地池化诸如加速器、存储器和存储装置之类的资源成为可能。在一些实施例中，例如，一个或多个池化加速器托架1130可以包括在数据中心1100的物理基础设施1100A之中，其中的每个池化加速器托架1130可以包括经由光结构1112和双模光交换基础设施1114而其他托架可全局访问的、加速器资源(例如，协处理器和/或FPGA)的池。
在另一个示例中，在各种实施例中，一个或多个池化存储托架1132可以包括在数据中心1100的物理基础设施1100A之中，其中的每个池化存储托架1132可以包括经由光结构1112和双模光交换基础设施1114而可供其他托架全局访问的、存储资源的池。在一些实施例中，这种池化存储托架1132可以包括诸如固态驱动器(SSD)之类的固态存储设备的池。在各种实施例中，一个或多个高性能处理托架1134可以包括在数据中心1100的物理基础设施1100A之中。在一些实施例中，高性能处理托架1134可以包括高性能处理器的池，以及增强空气冷却以产生高达250W或更高的较高热封套的冷却特征。在各种实施例中，任何给定的高性能处理托架1134可以以扩展连接器1117为特征，该扩展连接器1117可以接受远存储器扩展托架，使得该高性能处理托架1134本地可用的远存储器从包括在该托架上的处理器和附近存储器分解。在一些实施例中，这样的高性能处理托架1134可以使用包括低延迟SSD存储装置的扩展托架配置有远存储器。光基础设施允许一个托架上的计算资源利用远程加速器/FPGA、存储器和/或SSD资源，这些资源在位于数据中心中的相同机架或任何其他机架上的托架上分解。远程资源可以位于上面参考图5描述的脊-叶网络架构中的一次交换机跳跃外或两次交换机跳跃外。实施例不限于此上下文。
在各种实施例中，可以将一个或多个抽象层应用于物理基础设施1100A的物理资源，以便定义虚拟基础设施，例如，软件定义的基础设施1100B。在一些实施例中，可以分配软件定义的基础设施1100B的虚拟计算资源1136以支持云服务1140的提供。在各种实施例中，可以将特定的各组虚拟计算资源1136分组以供以SDI服务1138的形式提供给云服务1140。云服务1140的示例可以包括但不限于软件即服务(SaaS)服务1142、平台即服务(PaaS)服务1144以及基础设施即服务(IaaS)服务1146。
在一些实施例中，可以使用虚拟基础设施管理框架1150B来进行对软件定义的基础设施1100B的管理。在各种实施例中，虚拟基础设施管理框架1150B可以被设计为与管理将虚拟计算资源1136和/或SDI服务1138分配给云服务1140相结合地实现工作负载指纹识别技术和/或机器学习技术。在一些实施例中，虚拟基础设施管理框架1150B可以与执行这样的资源分配相结合地使用/咨询遥测数据。在各种实施例中，可以实现应用/服务管理框架1150C以便为云服务1140提供服务质量(QoS)管理能力。实施例不限于此上下文。
现在参考图12，用于数据库加速的说明性计算设备1200包括处理器1220、输入/输出(I/O)子系统1222、存储器1224、数据存储设备1226和加速器1230。计算设备1200可以体现为服务器计算机、机架服务器、刀片服务器、计算节点和/或数据中心中的托架(例如，如上面结合图2描述的托架204，如上面结合图11描述的物理基础设施1100A的托架，或数据中心的另一托架)。
在使用中，如下面描述的，计算设备1200使用加速器1230来对数据库的元素执行压缩、解压缩和各种过滤。计算设备1200可以存储要由加速器1230访问的经压缩的数据库、经解压缩的数据库、经修改的数据库等。加速器1230可以访问存储在诸如主存储器1224之类的外部存储器设备中的数据，以执行如下面描述的功能。数据可以包括元素的列，其可以体现为无符号整数的打包数组。每个元素通过索引来识别，索引可以是整数或其他标识符。通过利用加速器1230访问经压缩的数据库并且执行解压缩，然后执行一次或多次过滤，计算设备1200消除了将与经解压缩的数据库相关联的大量数据写入存储器1224的需要。即，仅数据处理的输出可以输出到存储器。这通过使加速器1230对数据执行解压缩、压缩、过滤等来减少执行这些功能所要求的存储器和/或带宽的量。因此，计算设备1200可以利用加速器1230来改进存储器利用率，特别是对于多租户计算设备1200，例如，数据中心中的设备。当然，通过使用加速器1230，计算设备1200还可以改进通过仅软件实现方式的性能。
处理器1220可以体现为能够执行本文描述的功能的任何类型的处理器。例如，处理器1220可以体现为(多个)单核或多核处理器、数字信号处理器、微控制器或其他处理器或处理/控制电路。类似地，存储器1224可以体现为能够执行本文描述的功能的任何类型的易失性或非易失性存储器或数据存储装置。在操作中，存储器1224可以存储在计算设备1200的操作期间使用的各种数据和软件，例如，操作系统、应用、程序、库和驱动程序。存储器1224经由I/O子系统1222通信地耦合到处理器1220，I/O子系统1222可以体现为促进与处理器1220、存储器1224和计算设备的其他组件的输入/输出操作的电路和/或组件。例如，I/O子系统1222可以体现为或以其他方式包括存储器控制器中心、输入/输出控制中心、传感器中心、固件设备、通信链路(即，点对点链路、总线链路、电线、电缆、光导、印刷电路板迹线等)和/或促进输入/输出操作的其他组件和子系统。在一些实施例中，I/O子系统1222可以形成片上系统(SoC)的一部分并且与处理器1220、存储器1224以及计算设备1200的其他组件一起合并在单个集成电路芯片上。
数据存储设备1226可以体现为被配置用于数据的短期或长期存储的任何类型的设备或多个设备，例如，存储器设备和电路、存储卡、硬盘驱动器、固态驱动器、非易失性闪速存储器或其他数据存储设备。计算设备1200还可以包括通信子系统1228，其可以体现为能够通过计算机网络(未示出)实现计算设备1200与其他远程设备之间的通信的任何通信电路、设备或其集合。通信子系统1228可以被配置为使用任何一种或多种通信技术(例如，有线通信或无线通信)和相关联的协议(例如，以太网、 WiMAX、3G、4G、LTE等)来实现这种通信。
如图12所示，计算设备1200包括加速器1230。加速器1230可以体现为任何协处理器、专用集成电路(ASIC)、现场可编程门阵列(FPGA)、功能块、IP核或计算设备1200的能够执行本文描述的功能的其他硬件加速器。加速器1230可以经由诸如外围总线(例如，快速PCI总线)或处理器间互连(例如，管芯内互连(IDI)或QuickPath互连(QPI))之类的高速连接接口、经由诸如Omni-Path架构之类的结构互连或经由任何其他适当的互连耦合到处理器1220。另外，尽管在图12中示出为与处理器1220和/或I/O子系统1222分离的分立组件，但是应当理解，在一些实施例中，加速器1230、处理器1220、I/O子系统1222和/或存储器1224可以并入相同的封装和/或相同的计算机芯片中，例如，在相同的SoC中。在一些实施例中，加速器1230可以作为计算设备1200的网络接口控制器(NIC)的一部分并入和/或包括在与NIC相同的多芯片封装中。在一些实施例中，加速器1230可以作为I/O子系统1222的一部分(例如，作为存储器控制器的一部分)并入。
计算设备1200还可以包括一个或多个外围设备1232。外围设备1232可以包括任何数量的附加输入/输出设备、接口设备、硬件加速器和/或其他外围设备。例如，在一些实施例中，外围设备1232可以包括触摸屏、图形电路、图形处理单元(GPU)和/或处理器图形、音频设备、麦克风、照相机、键盘、鼠标、网络接口，和/或其他输入/输出设备、接口设备和/或外围设备。
现在参考图13，在说明性实施例中，加速器1230在操作期间建立环境1300。说明性环境1300包括数据库压缩器1302、数据库准备模块1304、过滤管理器1306和数据库压缩器1308。环境1300的各种组件可以体现为硬件、固件、软件或其组合。因此，在一些实施例中，环境1300的组件中的一个或多个组件可以体现为电路或电子设备的集合(例如，数据库压缩器电路1302、数据库准备电路1304，过滤管理器电路1306和/或数据库压缩器电路1308)。应当意识到，在这样的实施例中，数据库压缩器电路1302、数据库准备电路1304、过滤管理器电路1306和/或数据库压缩器电路1308中的一个或多个可以形成处理器1220、I/O子系统1222、加速器1230和/或计算设备1200的其他组件的一部分。另外，在一些实施例中，说明性组件中的一个或多个可以形成另一组件的一部分和/或说明性组件中的一个或多个可以彼此独立。
数据库解压缩器1302被配置为从存储装置1226或存储器1224中取回经压缩的数据库，并且执行对经压缩的元素中的一个或多个经压缩的元素的解压缩。结果生成经解压缩的数据库，其包括经解压缩的元素。这些元素可以以柱状格式或适合于要操纵的数据库的任何其他格式存储。可以通过如上面描述的索引来识别每个元素。可以针对元素的输出引用索引。例如，如果加速器1230正在执行关于数据库中的哪些值高于阈值的确定，则输出可以包含高于阈值的每个元素的索引。
数据库准备模块1304被配置为准备数据库的元素以用于过滤操作。为此，数据库准备模块1304将来自数据库解压缩器1302的经解压缩的元素操纵为要由过滤操作处理的目标格式。例如，数据库准备模块1304可以执行比特操纵，例如，数据重新对齐、比特重新映射、比特广播或其他修改。数据准备可以取决于特定的数据库属性，例如，数据元素大小和/或数据库过滤操作。另外，在一些实施例中，数据库准备模块1304可以直接从源操纵数据元素，而无需解压缩。数据库准备模块1304还可以准备来自过滤操作的输出元素。数据库准备模块1304可以扩大或减小每个元素的比特宽度或将元素转换为索引数组。元素可以包括比特向量，并且索引数组中的每个索引对应于比特向量中的置位比特。
过滤管理器1306被配置为管理加速器1230可以对数据库元素执行的各种过滤操作。过滤操作可以包括结合数据库查询执行的一个或多个操作。过滤管理器1306可以在将数据库元素准备为目标格式之后执行诸如提取、按比特逻辑运算、扫描、生成、变换、聚合、排序或设置成员资格或这些操作的任何组合之类的过滤操作。在一些实施例中，过滤操作可以包括可以对数据库执行的其他过滤。过滤管理器1306还可以在执行第一过滤操作之后随后执行另一过滤操作。例如，为了执行聚合，过滤管理器1306可以聚合输出元素以生成聚合数据，这可以包括计算群体计数、最小值或最大值。
数据库压缩器1308被配置为压缩过滤管理器1306的输出，以生成经压缩的数据库中的经压缩的元素，这可以减少写入存储器1224的数据量。在一些实施例中，数据库压缩器1308可以在利用过滤管理器1306执行过滤操作之后或者在利用过滤管理器1306执行一系列过滤操作之后执行压缩。所使用的压缩算法可以是或可以不是用于解压缩数据的相同算法。压缩算法可以是数据或操作特定的(例如，暗示的或明确地配置的)。在压缩输出元素之后，加速器1230可以将经压缩的输出写入存储器1224。可替代地，加速器1230可以将输出写入存储器1224而不压缩输出。
现在参考图14，在使用中，计算设备1200可以执行用于数据库加速的方法1400。应当意识到，在一些实施例中，方法1400的操作可以由如图13所示的、计算设备1200的加速器1230的环境1300中的一个或多个组件来执行。方法1400开始于框1402，其中加速器1230确定是否对存储器1224或存储装置1226中的数据库进行解压缩。这可以基于存储器1224或存储装置1226中是否存在需要由过滤操作处理的经压缩的数据库来确定。如果加速器1230确定解压缩不是必须的(例如，存储器1224中的数据库未被压缩)，则方法1400向前分支到下面描述的框1410。如果加速器1230确定要对数据库进行解压缩，则方法1400前进到框1404。
在框1404中，加速器1230对经压缩的数据库进行解压缩。经压缩的数据库可以以任何无损压缩格式存储，包括字典编码、行程编码(RLE)或基于LZ77的算法(例如，DEFLATE)。在说明性实施例中，使用DEFLATE压缩数据库列数据，并且通过加速器1230的加速的硬件功能对数据库列数据进行解压缩。在一些实施例中，为了对数据库进行解压缩，在框1406中，加速器1230可以取回存储在数据存储设备1226中的经压缩的数据库列数据。在经压缩的数据库列数据处于存储器1224中之后，在框1408中，加速器1230对经压缩的数据库列数据执行解压缩以生成经解压缩的元素。经解压缩的元素可以体现为n比特无符号整数的打包数组，其中整数的宽度可以取决于数据库列、模式或其他数据定义。输入数据可以以大字节序(big-endian)或小字节序(little-endian)格式来组织。作为n＝1的特殊情况，输入数据可以体现为比特向量。
在对数据进行解压缩之后，在框1410中，加速器1230准备来自解压缩的数据以用于过滤操作。在框1412中，加速器1230可以将每个元素的格式调整为对应于用于指定过滤操作的目标格式。例如，加速器可以扩大或减小每个元素的比特宽度或将元素转换为索引数组。每个过滤操作可以指定其要求每个元素处于何种格式以供该过滤操作进行处理。加速器1230可以基于这些规范来格式化元素。
在框1414中，加速器1230对准备好的数据执行过滤。过滤可以包括在数据库查询期间典型地执行的常见操作。例如，过滤可以体现为提取、按比特逻辑运算、扫描、生成、变换、聚合、排序或设置成员资格。在一些实施例中，过滤可以以硬件执行操作，这些操作使用处理器1200以软件执行是低效的或以其他方式很慢，而将其他操作留给处理器1200。某些过滤可能要求两个或更多个数据元素的输入流。在一些实施例中，当加速器1230处理两个输入流时，必须绕过加速器1230的解压缩引擎(即，列数据可能未被压缩)，并且两个输入流中的一个必须是比特向量。在这些实施例中，解压缩和过滤可以在单独的通路中执行，例如，使用中间存储器缓冲区。当然，在其他实施例中，加速器1230可以对输入数据流的组成没有任何限制。例如，在一些实施例中，每个输入流可以被解压缩或不独立于另一个流，并且在一些实施例中，可以使用不是比特向量的多个输入流。
在框1416中，加速器1230从在框1414中执行过滤而生成输出元素。输出元素可以体现为类似于输入数据的比特向量和/或数据元素的打包数组。与输入数据相比，输出数据可以具有不同的比特宽度和/或不同数量的元素。例如，提取过滤可以对数据元素执行宽度转换或者填充数据元素。作为另一示例，按比特逻辑运算可以对两个输入数据元素流中的每个元素执行按比特逻辑运算(例如，AND、OR、XOR)。扫描元素可以将元素与下边界和上边界进行比较并输出比特向量。因此，通过仔细选择边界，扫描过滤可以用于执行相等、不等和数学比较运算。生成过滤可以用于生成一列恒定和/或随机数据。排序过滤可以生成经排序的数据元素列表。
在生成输出元素之后，在框1418中，加速器1230可以修改输出数据。在一些实施例中，为了修改输出数据，在框1420中，加速器1230调整每个元素的比特宽度。例如，加速器1230可以向每个元素添加前导零。另外，在一些实施例中，在框1422中，加速器1230可以将输出数据转换为索引。例如，这可以包括输出与满足指定条件的数据元素相对应的索引数组。
在一些实施例中，在修改输出数据之后，在框1424中，加速器1230针对输出数据生成聚合数据。这可以包括计算输出数据的群体计数、最小值或最大值。群体计数可以体现为比特向量中非零比特的数量。加速器1230还可以识别比特向量中的第一个和最后一个置位比特的索引。在一些实施例中，可以抑制输出数据中的一些或全部。例如，当生成群体计数时，加速器1230可以抑制比特向量并且仅输出群体计数。
在框1426中，加速器1230可以对输出数据执行压缩。在执行压缩之后，在框1428中，加速器1230确定是否执行附加过滤。如果加速器1230确定需要执行另一次过滤，则方法1400返回到框1404以继续处理数据。如果加速器1230确定不需要另一次过滤，则方法1400前进到框1430，其中加速器1230将可以被压缩的输出数据写入存储器1224。在写入输出数据之后，方法1400循环返回到框1402以继续执行数据库操作。
示例
以下提供本文公开的技术的说明性示例。这些技术的实施例可以包括下面描述的示例中的任何一个或多个以及其任何组合。
示例1包括一种用于数据库加速的计算设备，该计算设备包括数据库加速器，其中，数据库加速器包括：数据库解压缩器，其用于对经压缩的数据库中的一个或多个经压缩的元素进行解压缩，以生成一个或多个经解压缩的元素；数据库准备模块，其用于对一个或多个经解压缩的元素进行准备，以生成要由加速的过滤进行处理的一个或多个准备好的元素；以及过滤管理器，其用于对一个或多个准备好的元素执行加速的过滤，以生成一个或多个输出元素。
示例2包括示例1的主题，并且其中，经压缩的数据库中的一个或多个经压缩的元素以柱状格式存储。
示例3包括示例1和2中任一示例的主题，并且其中，对一个或多个经解压缩的元素进行准备包括：将一个或多个经解压缩的元素中的每个经解压缩的元素格式化为与加速的过滤兼容的目标格式。
示例4包括示例1-3中任一示例的主题，并且还包括：数据库压缩器，其用于对输出元素进行压缩以生成经压缩的输出元素，其中，计算设备响应于对输出元素进行的压缩而将经压缩的输出元素写入存储器。
示例5包括示例1-4中任一示例的主题，并且其中，对一个或多个准备好的元素执行加速的过滤包括执行提取、按比特逻辑运算、扫描、生成、变换、聚合、排序或设置成员资格。
示例6包括示例1-5中任一示例的主题，并且其中，利用数据库加速器来执行加速的过滤包括利用现场可编程门阵列来执行加速的过滤。
示例7包括示例1-6中任一示例的主题，并且其中，利用数据库加速器来执行加速的过滤包括利用专用集成电路来执行加速的过滤。
示例8包括示例1-7中任一示例的主题，并且其中，过滤管理器用于响应于加速的过滤对一个或多个准备好的元素的执行而对一个或多个输出元素执行第二加速的过滤。
示例9包括示例1-8中任一示例的主题，并且其中，数据库准备模块还用于响应于加速的过滤的执行而针对与第二加速的过滤兼容的目标格式对输出元素进行准备，其中，第二加速的过滤的执行包括响应于对输出元素进行的准备而执行第二加速的过滤。
示例10包括示例1-9中任一示例的主题，并且其中，过滤管理器还用于聚合输出元素以生成聚合数据。
示例11包括示例1-10中任一示例的主题，并且其中，聚合输出元素包括计算群体计数、最小值、最大值或总和。
示例12包括示例1-11中任一示例的主题，并且其中，聚合输出元素包括对输出元素执行算术运算或统计运算。
示例13包括示例1-12中任一示例的主题，并且其中：经解压缩的元素中的每个经解压缩的元素包括无符号整数，并且一个或多个经解压缩的元素包括经解压缩的元素的打包数组；并且输出元素中的每个输出元素包括无符号整数，并且一个或多个输出元素包括输出元素的打包数组。
示例14包括示例1-13中任一示例的主题，并且其中，数据库准备模块还用于响应于加速的过滤的执行而修改一个或多个输出元素。
示例15包括示例1-14中任一示例的主题，并且其中，修改一个或多个输出元素包括：扩大每个输出元素的比特宽度，截短每个输出元素的比特宽度，向每个输出元素附加(append)值，或者向每个输出元素预加(pre-pend)值。
示例16包括示例1-15中任一示例的主题，并且其中，修改一个或多个输出元素包括将一个或多个输出元素转换为索引数组，其中，一个或多个输出元素包括比特向量，并且其中，索引数组中的每个索引对应于比特向量中的置位比特。
示例17包括一种用于数据库加速的方法，该方法包括：由计算设备的数据库加速器对经压缩的数据库中的一个或多个经压缩的元素进行解压缩，以生成一个或多个经解压缩的元素；由数据库加速器对一个或多个经解压缩的元素进行准备，以生成用于由加速的过滤进行处理的一个或多个准备好的元素；以及由数据库加速器对一个或多个准备好的元素执行加速的过滤，以生成一个或多个输出元素。
示例18包括示例17的主题，并且其中，经压缩的数据库中的一个或多个经压缩的元素以柱状格式存储。
示例19包括示例17和18中任一示例的主题，并且其中，对一个或多个经解压缩的元素进行准备包括：将一个或多个经解压缩的元素中的每个经解压缩的元素格式化为与加速的过滤兼容的目标格式。
示例20包括示例17-19中任一示例的主题，并且还包括：由数据库加速器对输出元素进行压缩以生成经压缩的输出元素；以及由数据库加速器响应于对输出元素进行压缩而将经压缩的输出元素写入存储器。
示例21包括示例17-20中任一示例的主题，并且其中，对一个或多个准备好的元素执行加速的过滤包括执行提取、按比特逻辑运算、扫描、生成、变换、聚合、排序或设置成员资格。
示例22包括示例17-21中任一示例的主题，并且其中，利用数据库加速器来执行加速的过滤包括利用现场可编程门阵列来执行加速的过滤。
示例23包括示例17-22中任一示例的主题，并且其中，利用数据库加速器来执行加速的过滤包括利用专用集成电路来执行加速的过滤。
示例24包括示例17-23中任一示例的主题，并且还包括：由数据库加速器，响应于对一个或多个准备好的元素执行加速的过滤而对一个或多个输出元素执行第二加速的过滤。
示例25包括示例17-24中任一示例的主题，并且还包括：由数据库加速器，响应于执行加速的过滤而针对与第二加速的过滤兼容的目标格式对输出元素进行准备；其中，执行第二加速的过滤包括响应于对输出元素进行准备而执行第二加速的过滤。
示例26包括示例17-25中任一示例的主题，并且还包括由数据库加速器聚合输出元素以生成聚合数据。
示例27包括示例17-26中任一示例的主题，并且其中，聚合输出元素包括计算群体计数、最小值、最大值或总和。
示例28包括示例17-27中任一示例的主题，并且其中，聚合输出元素包括对输出元素执行算术运算或统计运算。
示例29包括示例17-28中任一示例的主题，并且其中：经解压缩的元素中的每个经解压缩的元素包括无符号整数，并且一个或多个经解压缩的元素包括经解压缩的元素的打包数组；并且输出元素中的每个输出元素包括无符号整数，并且一个或多个输出元素包括输出元素的打包数组。
示例30包括示例17-29中任一示例的主题，并且还包括响应于执行加速的过滤而修改一个或多个输出元素。
示例31包括示例17-30中任一示例的主题，并且其中，修改一个或多个输出元素包括扩大每个输出元素的比特宽度，截短每个输出元素的比特宽度，向每个输出元素附加值，或者向每个输出元素预加值。
示例32包括示例17-31中任一示例的主题，并且其中，修改一个或多个输出元素包括将一个或多个输出元素转换为索引数组，其中，一个或多个输出元素包括比特向量，并且其中，索引数组中的每个索引对应于比特向量中的置位比特。
示例33包括一种计算设备，其包括：处理器；以及其中存储有多个指令的存储器，该多个指令当由处理器执行时使计算设备执行示例17-32中任一示例的方法。
示例34包括一种或多种非暂时性计算机可读存储介质，包括存储在其上的多个指令，该多个指令响应于被执行而导致计算设备执行示例17-32中任一示例的方法。
示例35包括一种计算设备，其包括用于执行示例17-32中任一示例的方法的单元。
示例36包括一种用于数据库加速的计算设备，该计算设备包括：用于由计算设备的数据库加速器对经压缩的数据库中的一个或多个经压缩的元素进行解压缩以生成一个或多个经解压缩的元素的单元；用于由数据库加速器对一个或多个经解压缩的元素进行准备以生成用于由加速的过滤进行处理的一个或多个准备好的元素的单元；以及用于由数据库加速器对一个或多个准备好的元素执行加速的过滤以生成一个或多个输出元素的单元。
示例37包括示例36的主题，并且其中，经压缩的数据库中的一个或多个经压缩的元素以柱状格式存储。
示例38包括示例36和37中任一示例的主题，并且其中，用于对一个或多个经解压缩的元素进行准备的单元包括：用于将一个或多个经解压缩的元素中的每个经解压缩的元素格式化为与加速的过滤兼容的目标格式的单元。
示例39包括示例36-38中任一示例的主题，并且还包括：用于由数据库加速器对输出元素进行压缩以生成经压缩的输出元素的单元；以及用于由数据库加速器响应于对输出元素进行压缩而将经压缩的输出元素写入存储器的单元。
示例40包括示例36-39中任一示例的主题，并且其中，用于对一个或多个准备好的元素执行加速的过滤的单元包括用于执行提取、按比特逻辑运算、扫描、生成、变换、聚合、排序或设置成员资格的单元。
示例41包括示例36-40中任一示例的主题，并且其中，用于利用数据库加速器来执行加速的过滤的单元包括用于利用现场可编程门阵列来执行加速的过滤的单元。
示例42包括示例36-41中任一示例的主题，并且其中，用于利用数据库加速器来执行加速的过滤的单元包括用于利用专用集成电路来执行加速的过滤的单元。
示例43包括示例36-42中任一示例的主题，并且还包括用于由数据库加速器响应于对一个或多个准备好的元素执行加速的过滤而对一个或多个输出元素执行第二加速的过滤的单元。
示例44包括示例36-43中任一示例的主题，并且还包括：用于由数据库加速器响应于执行加速的过滤而针对与第二加速的过滤兼容的目标格式对输出元素进行准备的单元；其中，用于执行第二加速的过滤的单元包括用于响应于对输出元素进行准备而执行第二加速的过滤的单元。
示例45包括示例36-44中任一示例的主题，并且还包括用于由数据库加速器聚合输出元素以生成聚合数据的单元。
示例46包括示例36-45中任一示例的主题，并且其中，用于聚合输出元素的单元包括用于计算群体计数、最小值、最大值或总和的单元。
示例47包括示例36-46中任一示例的主题，并且其中，用于聚合输出元素的单元包括用于对输出元素执行算术运算或统计运算的单元。
示例48包括示例36-47中任一示例的主题，并且其中：经解压缩的元素中的每个经解压缩的元素包括无符号整数，并且一个或多个经解压缩的元素包括经解压缩的元素的打包数组；并且输出元素中的每个输出元素包括无符号整数，并且一个或多个输出元素包括输出元素的打包数组。
示例49包括示例36-48中任一示例的主题，并且还包括用于响应于执行加速的过滤而修改一个或多个输出元素的单元。
示例50包括示例36-49中任一示例的主题，并且其中，用于修改一个或多个输出元素的单元包括用于扩大每个输出元素的比特宽度，截短每个输出元素的比特宽度，向每个输出元素附加值，或向每个输出元素预加值的单元。
示例51包括示例36-50中任一示例的主题，并且其中，用于修改一个或多个输出元素的单元包括用于将一个或多个输出元素转换为索引数组的单元，其中，一个或多个输出元素包括比特向量，并且其中，索引数组中的每个索引对应于比特向量中的置位比特。

Claims (25)

1.一种用于数据库加速的计算设备，所述计算设备包括数据库加速器，其中，所述数据库加速器包括：
数据库解压缩器，其用于对经压缩的数据库中的一个或多个经压缩的元素进行解压缩，以生成一个或多个经解压缩的元素；
数据库准备模块，其用于对所述一个或多个经解压缩的元素进行准备，以生成要由加速的过滤进行处理的一个或多个准备好的元素；以及
过滤管理器，其用于对所述一个或多个准备好的元素执行所述加速的过滤，以生成一个或多个输出元素。
2.根据权利要求1所述的计算设备，其中，对所述一个或多个经解压缩的元素进行准备包括：将所述一个或多个经解压缩的元素中的每个经解压缩的元素格式化为与所述加速的过滤兼容的目标格式。
3.根据权利要求1所述的计算设备，还包括数据库压缩器，其用于对所述输出元素进行压缩以生成经压缩的输出元素，其中，所述计算设备响应于对所述输出元素进行的压缩而将所述经压缩的输出元素写入存储器。
4.根据权利要求1所述的计算设备，其中，对所述一个或多个准备好的元素执行所述加速的过滤包括执行提取、按比特逻辑运算、扫描、生成、变换、聚合、排序或设置成员资格。
5.根据权利要求1所述的计算设备，其中，利用所述数据库加速器来执行所述加速的过滤包括利用现场可编程门阵列来执行所述加速的过滤。
6.根据权利要求1所述的计算设备，其中，利用所述数据库加速器来执行所述加速的过滤包括利用专用集成电路来执行所述加速的过滤。
7.根据权利要求1所述的计算设备，其中，所述过滤管理器还用于聚合所述输出元素以生成聚合数据。
8.根据权利要求7所述的计算设备，其中，聚合所述输出元素包括计算群体计数、最小值、最大值或总和。
9.根据权利要求7所述的计算设备，其中，聚合所述输出元素包括对所述输出元素执行算术运算或统计运算。
10.根据权利要求1所述的计算设备，其中：
所述经解压缩的元素中的每个经解压缩的元素包括无符号整数，并且所述一个或多个经解压缩的元素包括所述经解压缩的元素的打包数组；并且
所述输出元素中的每个输出元素包括无符号整数，并且所述一个或多个输出元素包括所述输出元素的打包数组。
11.根据权利要求10所述的计算设备，其中，所述数据库准备模块还用于响应于所述加速的过滤的执行而修改所述一个或多个输出元素。
12.根据权利要求11所述的计算设备，其中，修改所述一个或多个输出元素包括：扩大每个输出元素的比特宽度，截短每个输出元素的比特宽度，向每个输出元素附加值，或者向每个输出元素预加值。
13.根据权利要求11所述的计算设备，其中，修改所述一个或多个输出元素包括将所述一个或多个输出元素转换为索引数组，其中，所述一个或多个输出元素包括比特向量，并且其中，所述索引数组中的每个索引对应于所述比特向量中的置位比特。
14.一种用于数据库加速的方法，所述方法包括：
由计算设备的数据库加速器对经压缩的数据库中的一个或多个经压缩的元素进行解压缩，以生成一个或多个经解压缩的元素；
由所述数据库加速器对所述一个或多个经解压缩的元素进行准备，以生成用于由加速的过滤进行处理的一个或多个准备好的元素；以及
由所述数据库加速器对所述一个或多个准备好的元素执行所述加速的过滤，以生成一个或多个输出元素。
15.根据权利要求14所述的方法，其中，对所述一个或多个经解压缩的元素进行准备包括：将所述一个或多个经解压缩的元素中的每个经解压缩的元素格式化为与所述加速的过滤兼容的目标格式。
16.根据权利要求14所述的方法，还包括：
由所述数据库加速器对所述输出元素进行压缩以生成经压缩的输出元素；以及
由所述数据库加速器，响应于对所述输出元素进行压缩而将所述经压缩的输出元素写入存储器。
17.根据权利要求14所述的方法，还包括由所述数据库加速器聚合所述输出元素以生成聚合数据。
18.根据权利要求14所述的方法，其中：
所述经解压缩的元素中的每个经解压缩的元素包括无符号整数，并且所述一个或多个经解压缩的元素包括所述经解压缩的元素的打包数组；并且
所述输出元素中的每个输出元素包括无符号整数，并且所述一个或多个输出元素包括所述输出元素的打包数组。
19.根据权利要求18所述的方法，还包括响应于执行所述加速的过滤而修改所述一个或多个输出元素。
20.一种用于数据库加速的计算设备，所述计算设备包括：
用于由所述计算设备的数据库加速器对经压缩的数据库中的一个或多个经压缩的元素进行解压缩以生成一个或多个经解压缩的元素的单元；
用于由所述数据库加速器对所述一个或多个经解压缩的元素进行准备以生成用于由加速的过滤进行处理的一个或多个准备好的元素的单元；以及
用于由所述数据库加速器对所述一个或多个准备好的元素执行所述加速的过滤以生成一个或多个输出元素的单元。
21.根据权利要求20所述的计算设备，其中，用于对所述一个或多个经解压缩的元素进行准备的单元包括：用于将所述一个或多个经解压缩的元素中的每个经解压缩的元素格式化为与所述加速的过滤兼容的目标格式的单元。
22.根据权利要求20所述的计算设备，还包括：
用于由所述数据库加速器对所述输出元素进行压缩以生成经压缩的输出元素的单元；以及
用于由所述数据库加速器响应于对所述输出元素进行压缩而将所述经压缩的输出元素写入存储器的单元。
23.根据权利要求20所述的计算设备，还包括用于由所述数据库加速器聚合所述输出元素以生成聚合数据的单元。
24.根据权利要求20所述的计算设备，其中：
所述经解压缩的元素中的每个经解压缩的元素包括无符号整数，并且所述一个或多个经解压缩的元素包括所述经解压缩的元素的打包数组；并且
所述输出元素中的每个输出元素包括无符号整数，并且所述一个或多个输出元素包括所述输出元素的打包数组。
25.根据权利要求24所述的计算设备，还包括用于响应于执行所述加速的过滤而修改所述一个或多个输出元素的单元。
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