CN109313584B - 用于管理加速器资源的分配的技术 - Google Patents

用于管理加速器资源的分配的技术 Download PDF

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Publication number
CN109313584B
CN109313584B CN201780038806.1A CN201780038806A CN109313584B CN 109313584 B CN109313584 B CN 109313584B CN 201780038806 A CN201780038806 A CN 201780038806A CN 109313584 B CN109313584 B CN 109313584B
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job
accelerator resources
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CN109313584A (zh
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S.M.巴莱
R.坎纳
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Intel Corp
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Intel Corp
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Abstract

用于动态地管理加速器资源分配的技术包括调配器服务器。所述调配器服务器用于将工作负载指派给所管理的节点以用于执行，确定针对一个或多个加速器资源的、用于加速工作负载内一个或多个作业的执行的所预测需求，在所预测的需求之前供给一个或多个加速器资源来加速所述一个或多个作业，以及将所述一个或多个所供给的加速器资源分配给所管理的节点来加速所述一个或多个作业的执行。还描述并且要求保护其它实施例。

Description

用于管理加速器资源的分配的技术
对相关申请的交叉引用
本申请对以下申请要求优先权：题为“TECHNOLOGIES FOR MANAGING ALLOCATIONOF ACCELERATOR RESOURCES”、申请序列号为15/407,329的美国发明专利申请，其提交于2017年1月17日，并且对2016年7月22日提交的、申请号为62/365,969的美国临时专利申请要求优先权；2016年8月18日提交的、申请号为62/376,859的美国临时专利申请；以及2016年11月29日提交的、申请号为62/427,268的美国临时专利申请。
背景
在典型的基于云的计算环境（例如数据中心）中，多个计算节点可以代表客户而执行工作负载（例如过程、应用、服务等等）。工作负载中的一个或多个可以包括功能（例如作业）集，所述功能可以通过使用加速器资源而被加速，所述加速器资源诸如现场可编程门阵列（FPGA）、专用图形处理器、或用于加速特殊类型作业的其它专门化设备。在典型的数据中心中，计算节点中的全部或子集可以物理地配备（例如，在与中央处理单元相同的板上）有一个或多个加速器资源。然而，在这样的数据中心中，加速器资源可能变得不被使用，或可能仅仅在工作负载正被执行的时间子集中被使用，这是因为被指派给计算节点的许多作业可能不包括服从加速的作业。此外，甚至是在其中当工作负载被指派给计算节点的时候每个计算节点是从跨数据中心分布的资源被组装的数据中心中，关于所指派的工作负载是否可受益于加速的信息可能是不可得到的。因而，计算节点可以在没有能够对工作负载执行有益的加速器资源的情况下被组装，或可以在具有在工作负载执行期间未被充分利用（例如空闲多于阈值量的时间）的一个或多个加速器资源的情况下被组装。因而，典型数据中心中加速器资源的分配是有问题的，并且可经常导致资源的低效使用，并且作为结果，导致针对数据中心运营商的不必要成本。
附图说明
在附图中作为示例而不是作为限制地图示了本文中所述的概念。为了图示的简单和清楚，各图中所图示的元素不一定是按比例绘制的。在被视为适当的情况下，已在各图之中重复了参考标记以指示对应或类似的元素。
图1是其中根据各种实施例可以实现一个或多个本文中所述的技术的数据中心的概念性概览图解；
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解；
图3是其中根据各种实施例可以实现一个或多个本文中所述的技术的另一数据中心的示例实施例的图解；
图4是其中根据各种实施例可以实现一个或多个本文中所述的技术的数据中心的另一示例实施例的图解；
图5是连接性方案的图解，所述连接性方案表示可以在图1、3和4的数据中心的各个橇板（sled）之间建立的链路层连接性；
图6是机架架构的图解，所述机架架构可以表示在图1-4中所描绘的、根据一些实施例的机架中任何特定一个的架构；
图7是可以与图6的机架架构一起使用的橇板的示例实施例的图解；
图8是用于为表征扩展能力的橇板提供支持的机架架构的示例实施例的图解；
图9是根据图8的机架架构所实现的机架的示例实施例的图解；
图10是被设计用于结合图9的机架而使用的橇板的示例实施例的图解；
图11是其中根据各种实施例可以实现一个或多个本文中所述的技术的数据中心的示例实施例的图解；
图12是用于管理加速器资源向所管理的节点的分配的系统的至少一个实施例的简化框图；
图13是图12的系统的调配器服务器（orchestrator server）的至少一个实施例的简化框图；
图14是可以由图12和13的调配器服务器建立的环境的至少一个实施例的简化框图；以及
图15-17是可以由图12-14的调配器服务器执行的、用于在所管理的节点执行工作负载时管理在所管理的节点之间的加速器资源的分配的方法的至少一个实施例的简化流程图。
具体实施方式
虽然本公开内容的概念易受各种修改和可替换形式，但是其特定实施例已经作为示例在附图中被示出并且将在本文中被详细描述。然而，应当理解的是，没有意图将本公开内容的概念限制到所公开的特定形式，而是相反地，意图是要覆盖与本公开内容以及所附权利要求一致的所有修改、等同物和可替换方案。
说明书中对“一个实施例”、“实施例”、“说明性实施例”等等的提及指示所描述的实施例可以包括特定的特征、结构或特性，但是每个实施例可以或可以不一定包括该特定的特征、结构或特性。此外，这样的短语不一定指代相同的实施例。此外，当结合实施例描述了特定的特征、结构或特性的时候，所主张的是无论是否被明确地描述，结合其它实施例来影响这样的特征、结构或特性在本领域技术人员的知识范围内。另外，应当领会到，在以“A、B、和C中至少一个”的形式的列表中所包括的项可以意指（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中至少一个”的形式所列举的项可以意指（A）；（B）；（C）；（A和B）；（A和C）；（B和C）；或（A、B和C）。
所公开的实施例可以在一些情况中用硬件、固件、软件、或其任何组合来被实现。所公开的实施例还可以被实现为由暂时性或非暂时性机器可读（例如计算机可读）存储介质所承载的或被存储在其上的指令，所述指令可以被一个或多个处理器读取和执行。机器可读存储介质可以被具体化为用于以机器可读的形式存储或传输信息的任何存储设备、机制或其它物理结构（例如易失性或非易失性存储器、媒体盘或其它媒体设备）。
在附图中，可以用特定的布置和/或定序来示出一些结构性特征或方法特征。然而，应当领会到，这样的特定布置和/或定序可以不是必需的。相反，在一些实施例中，可以用与说明性各图中所示的不同的方式和/或次序来布置这样的特征。另外，将结构性特征或方法特征包括在特定的图中不意图暗示在所有的实施例中需要这样的特征，并且在一些实施例中，这样的特征可以不被包括或可以与其它特征相组合。
图1图示了数据中心100的概念性概览，所述数据中心100可以一般地表示其中/针对其可以根据各种实施例而实现一个或多个本文中所述的技术的数据中心或其它类型的计算网络。如图1中所示，数据中心100通常可以包含多个机架，其中的每一个可以收容计算装备，所述计算装备包括物理资源的相应集合。在图1中所描绘的特定、非限制性示例中，数据中心100包含四个机架102A到102D，其收容计算装备，所述计算装备包括物理资源（PCR）的相应集合105A到105D。根据该示例，数据中心100的物理资源106的集体集合包括物理资源的各种集合105A到105D，其分布在机架102A到102D之中。物理资源106可以包括多种类型的资源，诸如例如处理器、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。
说明性的数据中心100以许多方式不同于典型的数据中心。例如，在说明性实施例中，诸如CPU、存储器之类的组件以及其它组件被安置在其上的电路板（“橇板”）被设计用于增大的热性能。特别地，在说明性实施例中，橇板比典型的板更遮蔽。换言之，橇板从前面到冷却风扇位于其中的背面更短。这减小空气必须跨板上的组件而行进的路径的长度。此外，橇板上的组件与典型电路板中相比被间隔开更远，并且所述组件被布置成减小或消除遮蔽（即，一个组件在另一组件的气流路径中）。在说明性实施例中，诸如处理器之类的处理组件位于橇板的顶侧上，而诸如DIMM之类的近旁存储器位于橇板的底侧上。作为通过该设计所提供的增强的气流的结果，与典型系统中相比，组件可以用更高的频率和功率水平来运作，从而增大性能。此外，橇板被配置成与每个机架102A、102B、102C、102D中的功率和数据通信线缆盲配对，其增强它们被快速移除、升级、重安装和/或取代的能力。类似地，位于橇板上的单独组件、诸如处理器、加速器、存储器和数据存储驱动器被配置成被容易地升级，这是由于它们距彼此的增大的间隔所致。在说明性实施例中，组件另外包括硬件鉴证特征来证明其真实性。
此外，在说明性实施例中，数据中心100利用单个网络架构（“构造（fabric）”），所述单个网络架构支持多个其它网络架构，包括以太网和全路径（Omni-Path）。在说明性实施例中，橇板被耦合以经由光纤而切换，所述光纤与典型的双绞线布线（例如类别5、类别5e、类别6等等）相比提供更高的带宽和更低的等待时间。由于高带宽、低等待时间互连和网络架构，数据中心100可以在使用中使资源池化，所述资源诸如物理上解聚的存储器、加速器（例如图形加速器、FPGA、ASIC等等）以及数据存储驱动器，并且在按需的基础上将它们提供给计算资源（例如处理器），从而使得计算资源能够访问经池化的资源，就好像它们在本地那样。说明性数据中心100另外接收针对各种资源的使用信息、基于过去的资源使用而预测针对不同类型工作负载的资源使用，并且基于该信息来动态地重分配资源。
数据中心100的机架102A、102B、102C、102D可以包括物理设计特征，所述物理设计特征促进各种类型的维护任务的自动化。例如，数据中心100可以通过使用机架而被实现，所述机架被设计成被机器人化地访问、并且接受和收容机器人化地可操纵的资源橇板。此外，在说明性实施例中，机架102A、102B、102C、102D包括集成的功率源，所述集成的功率源接收比典型用于功率源的更大的电压。增大的电压使得功率源能够向每个橇板上的组件提供附加的功率，其使得组件能够以比典型频率更高的频率运作。
图2图示了数据中心100的机架202的示例性逻辑配置。如图2中所示，机架202通常可以收容多个橇板，其中的每一个可以包括物理资源的相应集合。在图2中所描绘的特定、非限制性示例中，机架202收容橇板204-1到204-4，所述橇板204-1到204-4包括物理资源的相应集合205-1到205-4，其中的每一个构成被包括在机架202中的物理资源206的集体集合的一部分。关于图1，如果机架202表示例如机架102A，那么物理资源206可以对应于被包括在机架102A中的物理资源105A。在该示例的上下文中，物理资源105A因而可以由物理资源的相应集合构成，包括：被包括在机架202的橇板204-1到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、以及物理计算资源205-5。实施例不限于该示例。每个橇板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）中每一个的池。通过具有机器人化可访问并且机器人化可操纵的橇板，所述橇板包括解聚的资源，每种类型的资源可以独立于彼此地并且以其自己的经优化的刷新率被升级。
图3图示了数据中心300的示例，所述数据中心300可以一般地表示其中/针对其可以根据各种实施例而实现一个或多个本文中所述的技术的一个。在图3中所描绘的特定、非限制性示例中，数据中心300包括机架302-1到302-32。在各种实施例中，数据中心300的机架可以用这样的方式被布置使得限定和/或适应各种访问路径。例如，如图3中所示，数据中心300的机架可以用这样的方式被布置使得限定和/或适应访问路径311A、311B、311C和311D。在一些实施例中，这样的访问路径的存在通常可以使得自动化的维护装备、诸如机器人维护装备能够物理地访问被收容在数据中心300的各种机架中的计算装备并且执行自动化维护任务（例如替换出故障的橇板、升级橇板）。在各种实施例中，访问路径311A、311B、311C和311D的尺寸、机架302-1到302-32的尺寸和/或数据中心300的物理布局的一个或多个其它方面可以被选择成促进这样的自动化操作。实施例不限于该上下文中。
图4图示了数据中心400的示例，所述数据中心400可以一般地表示其中/针对其可以根据各种实施例而实现一个或多个本文中所述的技术的一个。如图4中所示，数据中心400可以表征光纤412。光纤412通常可以包括光学信令媒介（诸如光学布线）以及光学交换基础设施的组合，经由其，数据中心400中的任何特定橇板可以将信号发送到数据中心400中其它橇板中的每一个（并且从其接收信号）。光纤412提供给任何给定橇板的信令连接性可以包括对于相同机架中的其它橇板以及其它机架中的橇板二者的连接性。在图4中所描绘的特定、非限制性示例中，数据中心400包括四个机架402A到402D。机架402A到402D收容相应橇板对404A-1和404A-2、404B-1和404B-2、404C-1和404C-2、以及404D-1和404D-2。因而，在该示例中，数据中心400包括总共八个橇板。经由光纤412，每个这样的橇板可以具有与数据中心400中七个其它橇板中每一个的信令连接性。例如，经由光纤412，机架402A中的橇板404A-1可以具有与机架402A中的橇板404 A-2、以及分布在数据中心400的其它机架402B、402C和402D之中的六个其它橇板404B-1、404B-2、404C-1、404C-2、404D-1和404D-2的信令连接性。实施例不限于该示例。
图5图示了连接性方案500的概览，所述连接性方案500可以一般地表示在一些实施例中可以在数据中心、诸如图1、3和4的示例数据中心100、300和400中任一个的各个橇板之间建立的链路层连接性。连接性方案500可以通过使用光纤来被实现，所述光纤表征双重模式光学交换基础设施514。双重模式光学交换基础设施514通常可以包括如下交换基础设施：所述交换基础设施能够经由光学信令媒介的相同统一集合而接收根据多个链路层协议的通信，并且恰当地交换这样的通信。在各种实施例中，双重模式光学交换基础设施514可以通过使用一个或多个双重模式光学交换机515来被实现。在各种实施例中，双重模式光学交换机515通常可以包括高基交换机。在一些实施例中，双重模式光学交换机515可以包括多重交换机、诸如四重交换机。在各种实施例中，双重模式光学交换机515可以表征集成硅的光电子器件，其使得它们能够在与常规交换设备相比显著缩减的等待时间的情况下交换通信。在一些实施例中，双重模式光学交换机515可以构成叶-脊架构中的叶交换机530，所述叶-脊架构另外包括一个或多个双重模式光学脊交换机520。
在各种实施例中，双重模式光学交换机可以能够经由光纤的光学信令媒介而接收以下二者：承载因特网协议（IP分组）的以太网协议通信，以及根据第二、高性能计算（HPC）链路层协议（例如因特尔的全路径架构的、无限带宽）的通信。如图5中所反映的，关于具有对光纤的光学信令连接性的任何特定橇板对504A和504B，连接性方案500可以因而经由以太网链路和HPC链路二者来为链路层连接性提供支持。因而，以太网和HPC通信二者可以被单个高带宽、低等待时间的交换构造支持。实施例不限于该示例。
图6图示了机架架构600的一般性概览，所述机架架构600可以表示在图1至4中所描绘的、根据一些实施例的机架中任何特定一个的架构。如图6中所反映的，机架架构600一般可以表征多个橇板空间，往所述橇板空间中可以插入橇板，所述橇板中的每一个可以经由机架访问区601而机器人化地可访问。在图6中所描绘的特定、非限制性示例中，机架架构600表征五个橇板空间603-1到603-5。橇板空间603-1到603-5表征相应的多用途连接器模块（MPCM）616-1到616-5。
图7图示了可以表示这样的类型的橇板的橇板704的示例。如图7中所示，橇板704可以包括物理资源705的集合，以及被设计成当橇板704被插入到橇板空间、诸如图6的橇板空间603-1至603-5中任一个中时与配对物MPCM耦合的MPCM 716。橇板704还可以表征扩展连接器717。扩展连接器717一般可以包括插口、插槽或其它类型的连接元件，其能够接受一个或多个类型的扩展模块、诸如扩展橇板718。通过与扩展橇板718上的配对物连接器耦合，扩展连接器717可以为物理资源705提供对驻留在扩展橇板718上的补充计算资源705B的访问。实施例不限于该上下文中。
图8图示了机架架构800的示例，所述机架架构800可以表示可被实现以便为表征扩展能力的橇板、诸如图7的橇板704提供支持的机架架构。在图8中所描绘的特定、非限制性示例中，机架架构800包括七个橇板空间803-1至803-7，其表征相应的MPCM 816-1至816-7。橇板空间803-1至803-7包括相应的主区803-1A至803-7A，以及相应的扩展区803-1B至803-7B。关于每个这样的橇板空间，当对应的MPCM与所插入的橇板的配对物MPCM耦合的时候，主区一般可以构成物理地适应所插入橇板的橇板空间的一区。扩展区一般可以构成在所插入的橇板被配置有扩展模块的情况中可以物理地适应这样的模块、诸如图7的扩展橇板718的橇板空间的一区。
图9图示了机架902的示例，所述机架902可以表示根据一些实施例的、根据图8的机架架构800所实现的机架。在图9中所描绘的特定、非限制性示例中，机架902表征七个橇板空间903-1至903-7，其包括相应的主区903-1A至903-7A，以及相应的扩展区903-1B至903-7B。在各种实施例中，机架902中的温度控制可以通过使用空气冷却系统来被实现。例如，如图9中所反映的，机架902可以表征多个风扇919，所述风扇919一般被布置成提供各个橇板空间903-1至903-7内的空气冷却。在一些实施例中，橇板空间的高度大于常规的“1U”服务器高度。在这样的实施例中，风扇919一般可以包括如与在常规机架配置中所使用的风扇相比相对缓慢、大直径的冷却风扇。以较低速度运行较大直径冷却风扇相对于以较高速度运行的较小直径冷却风扇可增加风扇寿命，而同时仍提供相同量的冷却。橇板在物理上比常规的机架尺寸更遮蔽（shadow）。此外，组件被布置在每个橇板上，以减少热遮蔽（即没有连续地被布置在气流方向上）。作为结果，较宽、较遮蔽的橇板允许设备性能中的增加，因为由于经改善的冷却（即没有热遮蔽（thermal shadowing）、设备之间更多的空间、用于较大散热器的更多空间等等）能够以更高的热限度（envelope）（例如250W）来操作设备。
MPCM 916-1至916-7可以被配置成为所插入的橇板提供对相应功率模块920-1至920-7所源发的功率的接入，所述功率模块920-1至920-7中的每一个可以从外部功率源921汲取功率。在各种实施例中，外部功率源921可以将交流（AC）功率递送到机架902，并且功率模块920-1至920-7可以被配置成将这样的AC功率变换成直流（DC）功率，从而被源发到所插入的橇板。在一些实施例中，例如，功率模块920-1至920-7可以被配置成将277伏特的AC功率变换成12伏特的DC功率以用于经由相应的MPCM 916-1至916-7而被供给到所插入的橇板。实施例不限于该示例。
MPCM 916-1至916-7还可以被布置成为所插入的橇板提供对于双重模式光学交换基础设施914的光学信令连接性，所述双重模式光学交换基础设施914可以与图5的双重模式光学交换基础设施514相同或类似。在各种实施例中，被包含在MPCM 916-1至916-7中的光学连接器可以被设计成与所插入橇板的MPCM中所包含的配对物光学连接器耦合，用以经由相应长度的光学布线922-1至922-7而为这样的橇板提供对于双重模式光学交换基础设施914的光学信令连接性。在一些实施例中，每个这样长度的光学布线可以从其对应的MPCM延伸到在机架902的橇板空间外部的光学互连织机（loom）923。在各种实施例中，光学互连织机923可以被布置成通过机架902的支撑杆或其它类型的承重元件。实施例不限于该上下文中。由于所插入的橇板经由MPCM而连接到光学交换基础设施，所以能够节省在手动配置机架布线以适应新插入的橇板中典型花费的资源。
图10图示了机架1004的示例，所述机架1004可以表示根据一些实施例的、被设计用于结合图9的机架902而使用的橇板。橇板1004可以表征MPCM 1016，所述MPCM 1016包括光学连接器1016A与功率连接器1016B，并且被设计成结合MPCM 1016往该橇板空间中的插入而与橇板空间的配对物MPCM耦合。耦合MPCM 1016与这样的配对物MPCM可以使得功率连接器1016与配对物MPCM中所包括的功率连接器耦合。这通常可以使得橇板1004的物理资源1005能够经由功率连接器1016以及将功率连接器1016导电地耦合到物理资源1005的功率传输媒介1024而从外部源中源发功率。
橇板1004还可以包括双重模式光学网络接口电路1026。双重模式光学网络接口电路1026通常可以包括如下电路：所述电路能够根据受图9的双重模式光学交换基础设施914所支持的多个链路层协议中的每一个、通过光学信令媒介而通信。在一些实施例中，双重模式光学网络接口电路1026可以能够进行以下二者：以太网协议通信以及根据第二、高性能协议的通信。在各种实施例中，双重模式光学网络接口电路1026可以包括一个或多个光学收发器模块1027，其中的每一个可以能够通过一个或多个光学信道中的每一个而发射和接收光学信号。实施例不限于该上下文中。
耦合MPCM 1016与给定机架中橇板空间的配对物MPCM可以使得光学连接器1016A与配对物MPCM中所包括的光学连接器相耦合。这可以一般地经由光学信道1025集合中的每一个而在橇板的光学布线与双重模式光学网络接口电路1026之间建立光学连接性。双重模式光学网络接口电路1026可以经由电学信令媒介1028而与橇板1004的物理资源1005通信。附加于用于提供经改善的冷却以及使能实现以相对较高的热限度（例如250W）的操作的橇板尺寸以及橇板上组件的布置，如以上参考图9所描述的，在一些实施例中，橇板可以包括用于促进空气冷却的一个或多个附加特征，诸如被布置成耗散由物理资源1005所生成的热的热管和/或散热器。值得注意的是，尽管图10中所描绘的示例橇板1004不表征扩展连接器，但是表征橇板1004的设计元件的任何给定橇板根据一些实施例还可以表征扩展连接器。实施例不限于该上下文中。
图11图示了数据中心1100的示例，所述数据中心1100可以一般地表示其中/针对其可以根据各种实施例而实现一个或多个本文中所述的技术的一个。如图11中所反映的，物理基础设施管理框架1150A可以被实现以促进数据中心1100的物理基础设施1100A的管理。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内的自动化的维护功能，诸如使用机器人维护装备来服务物理基础设施1100A内的计算装备。在一些实施例中，物理基础设施1100A可以表征高级遥测系统，其执行的遥测报告足够稳健以支持物理基础设施1100A的远程自动化管理。在各种实施例中，由这样的高级遥测系统所提供的遥测信息可以支持诸如以下的特征：故障预测/预防能力以及容量计划能力。在一些实施例中，物理基础设施管理框架1150A还可以被配置成通过使用硬件鉴证技术来管理物理基础设施组件的认证。例如，机器人可以在安装之前、通过分析从与每个待安装的组件相关联的射频标识（RFID）标签所收集的信息来验证组件的真实性。实施例不限于该上下文中。
如图11中所示，数据中心1100的物理基础设施1100A可以包括光纤1112，所述光纤1112可以包括双重模式光学交换基础设施1114。光纤1112和双重模式光学交换基础设施1114可以分别与图4的光纤412和图5的双重模式光学交换基础设施514相同或类似，并且可以提供在数据中心1100的橇板之间的高带宽、低等待时间、多协议连接性。如以上所讨论的，参考图1，在各种实施例中，这样的连接性的可用性可以使得使资源、诸如加速器、存储器和存储装置解聚以及动态池化是可行的。在一些实施例中，例如，一个或多个经池化的加速器橇板1130可以被包括在数据中心1100的物理基础设施1100A之中，其中的每一个可以包括加速器资源的池，所述加速器资源诸如例如协处理器和/或FPGA，该池经由光纤1112与双重模式光学交换基础设施1114而对其它橇板是全局可访问的。
在另一示例中，在各种实施例中，一个或多个经池化的存储装置橇板1132可以被包括在数据中心1100的物理基础设施1100A之中，其中的每一个可以包括存储装置资源的池，该池经由光纤1112与双重模式光学交换基础设施1114而对其它橇板是可用、全局可访问的。在一些实施例中，这样的经池化的存储装置橇板1132可以包括固态存储设备、诸如固态驱动器（SSD）的池。在各种实施例中，一个或多个高性能处理橇板1134可以被包括在数据中心1100的物理基础设施1100A之中。在一些实施例中，高性能处理橇板1134可以包括高性能处理器的池，以及冷却特征，所述冷却特征增强空气冷却以产生高达250W或更多的更高热限度。在各种实施例中，任何给定的高性能处理橇板1134可以表征扩展连接器1117，所述扩展连接器1117可以接受远端存储器扩展橇板，使得本地可用于该高性能处理橇板1134的远端存储器从该橇板上所包括的处理器和近端存储器解聚。在一些实施例中，这样的高性能处理橇板1134可以通过使用包括低等待时间SSD存储装置的扩展橇板而被配置有远端存储器。光学基础设施允许一个橇板上的计算资源利用被解聚在位于相同机架或数据中心中任何其它机架上的橇板上的远程加速器/FPGA、存储器、和/或SSD资源。远程资源可以位于以上参考图5所描述的脊-叶网络架构中一个交换机跳跃远处或两个交换机跳跃远处。实施例不限于该上下文中。
在各种实施例中，一个或多个抽象层可以被应用于物理基础设施1100A的物理资源，以便限定虚拟基础设施、诸如软件限定的基础设施1100B。在一些实施例中，软件限定的基础设施1100B的虚拟计算资源1136可以被分配以支持云服务1140的供给。在各种实施例中，虚拟计算资源1136的特定集合可以被分组以用于供给到以SDI服务1138的形式的云服务1140。云服务1140的示例可以无限制地包括软件即服务（SaaS）服务1142、平台即服务（PaaS）服务1144、以及基础设施即服务（IaaS）的服务1146。
在一些实施例中，可以通过使用虚拟基础设施管理框架1150B来进行软件限定的基础设施1100B的管理。在各种实施例中，虚拟基础设施管理框架1150B可以被设计成实现工作负载指纹识别技术和/或机器学习技术，其结合管理虚拟计算资源1136和/或SDI服务1138往云服务1140的分配。在一些实施例中，虚拟基础设施管理框架1150B可以使用/咨询遥测数据，其结合执行这样的资源分配。在各种实施例中，应用/服务管理框架1150C可以被实现以便为云服务1140提供QoS管理能力。实施例不限于该上下文中。
如图12中所示，用于管理加速器资源（例如物理加速器资源205-2）在一组所管理的节点1260之间的分配的说明性系统1210包括调配器服务器1240，其与该组所管理的节点1260通信。每个所管理的节点1260可以被具体化为资源（例如物理资源206）的汇集，所述资源诸如计算资源（例如物理计算资源205-4）、存储装置资源（例如物理存储装置资源205-1）、加速器资源（例如物理加速器资源205-2）或其它资源（例如物理存储器资源205-3），其来自相同或不同的橇板（例如橇板204-1、204-2、204-3、204-4等等）或机架（例如机架302-1直到302-32中的一个或多个）。每个所管理的节点1260可以在工作负载将被指派给所管理的节点1260的时间或在任何其它时间由调配器服务器1240建立、限定、或“加速自旋（spunup）”，并且可以无论是否有任何工作负载在当前被指派给所管理的节点1260而存在。可以根据以上参考图1、3、4和11所描述的数据中心100、300、400、1100来实现系统1210。在说明性实施例中，该组所管理的节点1260包括所管理的节点1250、1252和1254。虽然在该组中示出了三个所管理的节点1260，但是应当理解的是，在其它实施例中，该组可以包括不同数目的所管理的节点1260（例如，成千上万）。系统1210可以位于数据中心中并且向客户端设备1220提供存储和计算服务（例如云服务），所述客户端设备1220通过网络1230而与系统1210通信。调配器服务器1240可以支持云操作环境，诸如OpenStack，并且所管理的节点1250可以执行一个或多个应用或过程（即工作负载），诸如在虚拟机或容器中，代表客户端设备1220的用户。
如本文中更详细地讨论的，调配器服务器1240在操作中被配置成将工作负载指派给所管理的节点1260，在工作负载被执行时从所管理的节点1260接收对性能和条件进行指示的遥测数据，标识工作负载内、将利用一个或多个加速器资源205-2来被加速的作业，供给（例如配置）加速器资源205-2来加速所标识的作业，并且将所供给的加速器资源205-2分配给所管理的节点1260用以加速所标识的作业。在说明性实施例中，加速器资源205-2包括现场可编程门阵列（FPGA），并且调配器服务器通过发送对FPGA的期望配置进行指示的比特流来供给FPGA以加速特定作业。调配器服务器1240在说明性实施例中基于对遥测数据进行评估以及对作业执行中的模式进行标识来确定何时很可能出现对于为特定作业加速的需求，并且提前将比特流发送到FPGA，以当出现加速需求的时候及时供给FPGA来加速作业。另外，调配器服务器可以接收资源分配目标数据，其指示将在工作负载执行期间被实现的一个或多个目标。在说明性实施例中，所述目标关于被分配给所管理的节点1260的资源的功率消耗、寿命预期、产热和/或性能。在工作负载被执行时，调配器服务器1240可以选择性地分配或解分配加速器资源205-2以实现资源分配目标。在说明性实施例中，可以测量目标的实现，其等于或以其它方式被定义为来自一个或多个所管理的节点1260的所测量值满足与目标相关联的标的值的程度。例如，在说明性实施例中，增大实现可以通过如下来履行：减小在所测量值（例如完成工作负载或工作负载中的操作所用的时间）与标的值（例如完成工作负载或工作负载中的操作的标的时间）之间的误差（例如差异）。相反，减小实现可以通过增大在所测量值与标的值之间的误差（例如差异）来被履行。
现在参考图13，调配器服务器1240可以被具体化为如下的任何类型的计算设备：所述计算设备能够执行本文中所述的功能，包括发布请求以使得云服务被执行，接收云服务的结果，将工作负载指派给计算设备，分析对工作负载被执行时的性能和条件（例如资源利用、一个或多个温度、风扇速度等等）进行指示的遥测数据，以及在工作负载被执行时管理资源、包括加速器资源205-2跨所管理节点1260的分配。例如，调配器服务器1240可以被具体化为计算机、分布式计算系统、一个或多个橇板（例如橇板204-1、204-2、204-3、204-4等等）、服务器（例如独立的、机架装配的、刀片式的等等）、多处理器系统、网络器具（例如物理的或虚拟的）、台式计算机、工作站、膝上型计算机、笔记本计算机、基于处理器的系统、或网络器具。如图13中所示，说明性的调配器服务器1240包括中央处理单元（CPU）1302、主存储器1304、输入/输出（I/O）子系统1306、通信电路1308、以及一个或多个数据存储设备1312。当然，在其它实施例中，调配器服务器1240可以包括其它或附加的组件，诸如通常存在于计算机中的那些（例如显示器、外围设备等等）。另外，在一些实施例中，说明性组件中的一个或多个可以被并入在另一组件中、或以其它方式形成另一组件的一部分。例如，在一些实施例中，主存储器1304、或其部分可以被并入在CPU 1302中。
CPU 1302可以被具体化为能够执行本文中所述功能的任何类型的处理器。CPU1302可以被具体化为单个或（多个）多核处理器、微控制器、或其它处理器或处理/控制电路。在一些实施例中，CPU 1302可以被具体化为、包括或被耦合到现场可编程门阵列（FPGA）、专用集成电路（ASIC）、可重配置的硬件或硬件电路、或用以促进本文中所述功能的执行的其它专门化硬件。类似地，主存储器1304可以被具体化为能够执行本文中所述功能的任何类型的易失性（例如动态随机存取存储器（DRAM）等等）或非易失性存储器或数据存储装置。在一些实施例中，主存储器1304中的全部或一部分可以被集成到CPU 1302中。在操作中，主存储器1304可以存储在操作期间使用的各种软件和数据，诸如遥测数据、资源分配目标数据、工作负载标签、工作负载分类、作业数据、资源分配数据、操作系统、应用、程序、库和驱动器。
I/O子系统1306可以被具体化为用于促进与CPU 1302、主存储器1304、以及调配器服务器1240的其它组件的输入/输出操作的电路和/或组件。例如，I/O子系统1306可以被具体化为、或以其它方式包括存储器控制器中心、输入/输出控制中心、集成的传感器中心、固件设备、通信链路（例如点对点链路、总线链路、导线、线缆、光导、印刷电路板迹线等等）、和/或用以促进输入/输出操作的其它组件和子系统。在一些实施例中，I/O子系统1306可以形成芯片上系统（SoC）的一部分，并且连同CPU 1302、主存储器1304、以及调配器服务器1240的其它组件中的一个或多个而被并入在单个集成电路芯片上。
通信电路1308可以被具体化为能够使能实现在调配器服务器1240与另一计算设备（例如客户端设备1220和/或所管理的节点1260）之间、通过网络1230的通信的任何通信电路、设备或其集合。通信电路1308可以被配置成使用任何一个或多个通信技术（例如有线或无线通信）和相关联的协议（例如以太网、蓝牙®、Wi-Fi®、 WiMAX等等）来实现这样的通信。
说明性通信电路1308包括网络接口控制器（NIC）1310，其也可以被称为主机构造接口（HFI）。NIC 1310可以被具体化为可以由调配器服务器1240用于与另一计算设备（例如客户端设备1220和/或所管理的节点1260）连接的一个或多个插入板、子卡、网络接口卡、控制器芯片、芯片组或其它设备。在一些实施例中，NIC 1310可以被具体化为包括一个或多个处理器的芯片上系统（SoC）的部分，或被包括在还包含一个或多个处理器的多芯片封装上。在一些实施例中，NIC 1310可以包括本地处理器（未示出）和/或本地存储器（未示出），这二者对于NIC 1310都在本地。在这样的实施例中，NIC 1310的本地处理器可以能够执行本文中所述的CPU 1302的功能中的一个或多个。另外地或可替换地，在这样的实施例中，NIC1310的本地存储器可以在板层级、插口层级、芯片层级、和/或其它层级上被集成到调配器服务器1240的一个或多个组件中。
所述一个或多个说明性数据存储设备1312可以被具体化为被配置用于数据的短期或长期存储的任何类型的设备，诸如例如存储器设备和电路、存储器卡、硬盘驱动器、固态驱动器或其它数据存储设备。每个数据存储设备1312可以包括系统分区，其存储针对数据存储设备1312的数据和固件代码。每个数据存储设备1312还可以包括操作系统分区，其存储针对操作系统的数据文件和可执行物。
另外地或可替换地，调配器服务器1240可以包括一个或多个外围设备1314。这样的外围设备1314可以包括通常存在于计算设备中的任何类型的外围设备，诸如显示器、扬声器、鼠标、键盘、和/或其它输入/输出设备、接口设备、和/或其它外围设备。
客户端设备1220和所管理的节点1260可以具有与在图13中所描述的那些类似的组件。调配器服务器1240的那些组件的描述等同地可适用于客户端设备1220和所管理的节点1260的组件的描述，并且在本文中为了描述的清楚而不被重复。此外，应当领会的是，客户端设备1220和所管理的节点1260中的任一个可以包括通常存在于计算设备中的其它组件、子组件和设备，其没有在以上参考调配器服务器1240被讨论并且在本文中为了描述的清楚而不被讨论。如以上所讨论的，每个所管理的节点1260可以包括跨多个橇板分布的资源，并且在这样的实施例中，CPU 1302、存储器1304和/或通信电路1308可以包括其位于相同橇板或不同橇板上的部分。
如上所述，客户端设备1220、调配器服务器1240、和所管理的节点1260说明性地经由网络1230而通信，所述网络1230可以被具体化为任何类型的有线或无线通信网络，包括全局网络（例如因特网）、局域网（LAN）或广域网（WAN）、蜂窝网络（例如全球移动通信系统（GSM）、3G、长期演进（LTE）、微波存取全球互通（WiMAX）等等 ）、数字订户线（DSL）网络、线缆网络（例如同轴网络、光纤网络等等）、或其任何组合。
现在参考图14，在说明性实施例中，调配器服务器1240可以在操作期间建立环境1400。说明性环境1400包括网络通信器1420、遥测监控器1430和资源管理器1440。环境1400的组件中的每一个可以被具体化为硬件、固件、软件或其组合。因而，在一些实施例中，环境1400的组件中的一个或多个可以被具体化为电路或电气设备集合（例如网络通信器电路1420、遥测监控器电路1430、资源管理器电路1440等等）。应当领会到，在这样的实施例中，网络通信器电路1420、遥测监控器电路1430、或资源管理器电路1440中的一个或多个可以形成CPU 1302、主存储器1304、I/O子系统1306、和/或调配器服务器1240的其它组件中的一个或多个的一部分。在说明性实施例中，环境1400包括遥测数据1402，所述遥测数据1402可以被具体化为对被分配给每个所管理的节点1260以及在所管理的节点1260执行被指派给它们的工作负载时执行的工作负载的单独作业（例如功能集）的资源的性能和条件（例如资源利用、操作频率、功率使用、一个或多个温度、风扇速度等等）进行指示的数据。另外，说明性环境1400包括资源分配目标数据1404，其指示将在工作负载执行期间满足的用户定义的阈值或目的（“目标”）。在说明性实施例中，所述目标关于被分配给所管理的节点1260的资源的功率消耗、寿命预期、产热和性能。此外，说明性环境1400包括工作负载标签1406，所述工作负载标签1406可以被具体化为对所管理的节点1260所执行的每个工作负载唯一地进行标识的任何标识符（例如过程号、可执行文件名、字母数字标记等等）。
另外，说明性环境1400包括工作负载分类1408，所述工作负载分类1408可以被具体化为对每个工作负载的一般资源利用趋势（例如处理器密集、存储器密集、网络带宽密集等等）进行指示的任何数据。此外，说明性环境1400包括作业数据1410，所述作业数据1410指示可以被加速的每个工作负载内的作业（例如功能集）。在说明性实施例中，作业数据1410被具体化为将被处理的作业的队列，作业内的功能类型的指示（例如压缩、加密、矩阵操作等等），与作业所使用的输入数据的格式和大小相关的信息（例如字节数、输入数据是否被格式化为矩阵或以其它方式被格式化、针对输入数据的编码方案等等），与每个作业相关联的全局唯一的标识符（GUID），指示针对每个工作负载以及跨数据中心1100中所执行的所有工作负载、在预定义的时间帧内特定的作业已在队列中多少次的计数器、每个作业驻留在队列中的平均时间量、和/或作业的其它特性。另外，说明性实施例1400包括资源分配数据1412，所述资源分配数据1412指示已经在任何给定时间被分配给每个所管理的节点1260的数据中心1100内的资源、包括加速器资源205-2。
在说明性环境1400中，网络通信器1420，其如以上所讨论的可以被具体化为硬件、固件、软件、虚拟化硬件、仿真架构、和/或其组合，被配置成促进分别向和自调配器服务器1240的进站和出站网络通信（例如网络业务、网络分组、网络流等等）。为了这样做，网络通信器1420被配置成接收和处理来自一个系统或计算设备（例如客户端设备1220）的数据分组，并且预备和发送数据分组到另一计算设备或系统（例如所管理的节点1260）。因此，在一些实施例中，网络通信器1420的功能性的至少一部分可以由通信电路1308执行，并且在说明性实施例中，由NIC 1310执行。
遥测监控器1430，其如以上所讨论的可以被具体化为硬件、固件、软件、虚拟化硬件、仿真架构、和/或其组合，被配置成在所管理的节点1260执行被指派给它们的工作负载时从所管理的节点1260收集遥测数据1402。遥测监控器1430可以在持续的基础上、针对更新的遥测数据1402而主动地轮询每个所管理的节点1260，或可以被动地从所管理的节点1260接收遥测数据1402，诸如通过针对更新的遥测数据1402而在特定的网络端口上进行收听。遥测监控器1430可以此外对遥测数据1402进行解析和分类，诸如通过将遥测数据1402分离成针对每个所管理节点1260的单独文件或数据集。
资源管理器1440，其可以被具体化为硬件、固件、软件、虚拟化硬件、仿真架构和/或其组合，被配置成将工作负载指派给所管理的节点，标识要加速的工作负载内的作业，预测何时将在工作负载内出现加速需求，在所预测的加速需求前供给（例如配置）加速器资源205-2，并且在持续的基础上调节加速器资源205-2向和自所管理节点1260的分配以改善工作负载执行的效率和/或满足其它资源分配目标（例如来自资源分配目标数据1404）。
为了这样做，资源管理器1440包括工作负载标注器1442、工作负载分类器1444、工作负载行为预测器1446、加速管理器1448和多目标分析器1450。在说明性实施例中，工作负载标注器1442被配置成将工作负载标签1406指派给当前被执行的或被预定于由所管理的节点1260执行的每个工作负载。工作负载标注器1442可以根据工作负载的可执行名称、工作负载的代码的全部或一部分的散列、或基于用于唯一地标识每个工作负载的任何其它方法来生成工作负载标签1406。在说明性实施例中，工作负载分类器1444被配置成基于每个工作负载的平均资源利用（例如一般利用处理器容量的65%，一般利用存储器容量的40%等等）来对每个经标注的工作负载进行分类。
在说明性实施例中，工作负载行为预测器1446被配置成分析遥测数据1402，以标识针对每个工作负载的遥测数据1402内的资源利用的不同阶段。每个资源利用阶段可以被具体化为如下时间段：在所述时间段中，被分配给所管理节点1260的一个或多个资源的资源利用满足预定义的阈值。例如，所分配的处理器容量的至少85%的利用可以指示高处理器利用阶段，并且所分配的存储器容量的至少85%的利用可以指示高存储器利用阶段。在说明性实施例中，工作负载行为预测器1446此外标识工作负载的资源利用阶段中的模式（例如高处理器利用阶段，继之以高存储器利用阶段，继之以低资源利用阶段，其然后再次继之以高处理器利用阶段）。工作负载行为预测器1446可以被配置成利用资源利用阶段模式的标识，确定给定工作负载的当前资源利用阶段，基于所述模式而预测下一资源利用阶段，以及确定直到向下一资源利用阶段的工作负载过渡为止的剩余时间量。
在说明性实施例中，加速管理器1448被配置成根据遥测数据1402而标识、生成作业数据1410，基于其类型、在作业队列中的驻留时间、作业多久被执行一次、以及其它因素来标识要加速的工作负载内的作业，协调选择和供给数据中心1100内可用的加速器资源205-2、诸如FPGA，以及管理加速器资源205-2的分配和/或解分配的定时以符合何时很可能将由工作负载发起（例如调用）待加速作业的预测时间。
在说明性实施例中，多目标分析器1450被配置成在工作负载执行期间是否满足效率目标和/或其它资源分配目标数据1404，以及确定对所管理节点1260之间的资源分配的调节以使能满足所述一个或多个目标。因而，关于加速器资源205-2的分配，多目标分析器1450与加速管理器1448协调以确定哪些加速器资源205-2被分配给哪些所管理的节点1260以及在什么时候。在说明性实施例中，多目标分析器1450可以包括数据中心1100的模型，其响应于对所管理节点1260之间的资源分配和/或资源内的组件设置（例如增大或减小时钟速度、启用或禁用针对扩展指令集的支持等等）的各种调节而模拟预期的效果，包括功率消耗、热生成、对计算能力的改变和其它因素。为了这样做，在说明性实施例中，多目标分析器1450包括资源分配器1452和资源设置调节器1454。在说明性实施例中，资源分配器1452被配置成向所管理的节点1260发布指令，以分配或解分配资源，如由多目标分析器1450和加速管理器1448所确定的那样，并且更新资源分配数据1412以指示在所管理的节点1260之间的资源分配的当前状态。类似地，在说明性实施例中，资源设置调节器1454被配置成向所管理的节点1260中的一个或多个发布指令，以调节被分配给所管理的节点1260的资源的设置，诸如通过调节固件设置以增大或减小处理器的时钟速度、增大或减小功率利用设置、和/或影响资源操作的其它设置。
应当领会的是，工作负载标注器1442、工作负载分类器1444、工作负载行为预测器1446、加速管理器1448、多目标分析器1450、资源分配器1452和资源设置调节器1454中的每一个可以分离地被具体化为硬件、固件、软件、虚拟化硬件、仿真架构和/或其组合。例如，工作负载标注器1442可以被具体化为硬件组件，而工作负载分类器1444、工作负载行为预测器1446、加速管理器1448、多目标分析器1450、资源分配器1452和资源设置调节器1454被具体化为虚拟化硬件组件或被具体化为硬件、固件、软件、虚拟化硬件、仿真架构、和/或其组合的某种其它组合。
现在参考图15，在使用中，调配器服务器1240可以执行方法1500，所述方法1500用于在所管理的节点1260执行工作负载时管理在所管理的节点1260之间的加速器资源205-2的分配。方法1500开始于框1502，其中调配器服务器1240确定是否要管理在所管理节点1260之间的资源分配。在说明性实施例中，如果调配器服务器1240上电、与所管理的节点1260通信、并且已经接收到来自客户端设备1220的要提供云服务（即执行一个或多个工作负载）的至少一个请求，则调配器服务器1240确定要管理资源分配。在其它实施例中，调配器服务器1240可以基于其它因素而确定是否要管理资源的分配。无论如何，响应于确定了要管理资源分配，在说明性实施例中，方法1500前进到框1504，其中调配器服务器1240可以获得资源分配目标数据（例如资源分配目标数据1404）。在这样做时，调配器服务器1240可以通过图形用户接口（未示出）从用户（例如管理员）、从配置文件、或从另一源获得资源分配目标数据1404。在说明性实施例中，调配器服务器1240可以获得性能目标数据，其指示将用来执行工作负载的标的速度（例如其中将完成工作负载执行的标的时间段、每秒的标的操作数等等），如在框1506中所指示的。在接收资源分配目标数据1404中，调配器服务器1240可以接收功率消耗目标数据，其指示在每个所管理的节点1260执行工作负载时被分配给它们的资源的标的功率使用或阈值功率使用量，如在框1508中所指示的。另外地或可替换地，调配器服务器1240可以接收可靠性目标数据，其指示一个或多个资源的标的寿命循环（例如数据存储设备的标的寿命循环、冷却风扇的标的寿命循环等等），如在框1510中所指示的。如在框1512中所指示的，调配器服务器1240还可以接收热学目标数据，其指示一个或多个资源（例如一个或多个CPU 1302等等）的一个或多个标的温度。
在框1514中，在说明性实施例中，调配器服务器1240将资源分配给所管理的节点1260。最初，调配器服务器1240尚未接收到任何遥测数据1402来告知关于哪些资源要分配给各种所管理节点1260的决定。因而，如在框1516中所指示的，调配器服务器1240可以初始不向任何所管理的节点1260分配任何加速器资源205-2。可替换地，如在框1518中所指示的，调配器服务器1240可以根据默认方案而在所管理的节点1260之间指派加速器资源205-2（例如在所管理的节点1260之间均匀地划分加速器资源205-2，在所管理的节点1260被定义时将预定义数目的加速器资源205-2分配给每个所管理的节点1260直到没有更多可用的加速器资源205-2可用为止，等等）。在这样做时，调配器服务器1240可以推迟将任何FPGA分配到所管理的节点1260，直到在工作负载已经被指派并且FPGA已经被供给（例如配置）以执行要加速的一个或多个作业之后为止，如本文中更详细描述的那样。在框1520中，调配器服务器1240将工作负载指派到所管理的节点1260以用于执行，并且如在框1522中所指示的，在工作负载被所管理的节点1260执行时开始接收遥测数据1402。随后，方法1500前进到图16的框1524，其中调配器服务器1240根据遥测数据1402而确定所预测的加速需求（例如，为此应当分配加速器资源205-2），如在本文中更详细地解释的那样。
现在参考图16，在根据遥测数据1402而确定所预测的加速需求中，调配器服务器1240可以标识用于加速的所指派工作负载内的作业，如在框1526中所指示的。如在框1528中所指示的，在说明性实施例中，调配器服务器1240可以分析作业队列（例如作业数据1410）以标识用于加速的所指派工作负载内的作业。在这样做时，调配器服务器1240可以确定每个作业驻留在队列中（例如在被完成之前）的平均时间量，如在框1530中所指示的。如在框1532中所指示的，调配器服务器1240可以将平滑算法、诸如指数平滑算法应用到由作业队列所指示的一个或多个时间，用以确定每个作业驻留在作业队列中的平均时间量。如在框1534中所指示的，调配器服务器1240可以确定所执行的作业的局部计数和全局计数，并且比较所述局部和全局计数与一个或多个阈值计数值。例如，调配器服务器1240可以维护为每个工作负载已经执行了每个作业多少次的计数（例如局部计数），以及无论特定的工作负载或与它相关联的所管理节点1260如何已经执行了每个作业多少次的计数。如果计数中的任一个满足（例如等于或超过）预定义的阈值，则调配器服务器1240可以将对应的作业标识为应当被加速（例如利用一个或多个加速器资源205-2来被执行）的一个。
仍参考图16，在确定所预测的加速需求中，调配器服务器1240可以附加地标识正被执行的作业的特性，如在框1536中所指示的。在这样做时，调配器服务器1240可以确定每个作业是否服从加速（例如，加速器资源是否能够比通用处理器1302更快或更高效地执行作业）。在这样做时，如在框1540中所指示的，调配器服务器1240可以确定每个作业的类型，诸如通过对功能类型进行分析和分类，如指示某些类型的操作（例如压缩操作、加密操作等等）。如在框1542中所指示的，调配器服务器1240可以确定由作业所使用的输入数据的特性，诸如输入数据是否被格式化为值的矩阵或以另一格式被格式化、输入数据的大小（例如以字节）和/或输入数据的特性。如上所述，可以在作业数据1410上执行分析，所述作业数据1410在说明性实施例中从管理节点1260所报告的遥测数据1402中生成。因而，在说明性实施例中，所管理的节点1260可以被配置成提供如下信息：所述信息指示每个作业内的功能的类型以及针对每个作业的输入数据特性。如在框1544中所指示的，在标识作业特性的过程中，调配器服务器1240可以将全局唯一的标识符（例如唯一的数、标记、字母数字序列、或其它标识符）指派给每个作业。全局唯一的标识符可以生成自与遥测数据1402对应的、从所管理的节点1260中的每个所管理节点1260报告的每个作业的标识符，诸如通过将工作负载标签的散列以及所管理节点1260的唯一标识符附到在来自所管理的节点1260的遥测数据1402中所指示的对应作业的标识符。在框1546中，调配器服务器1240可以确定加速需求的所预测时间（例如何时将很可能出现该需求）。如在框1548中所指示的，调配器服务器1240可以确定所预测的需求时间，这通过分析针对每个工作负载的作业执行的模式（例如作业A驻留在作业队列中10秒，继之以作业B，所述作业B驻留在作业队列中15秒，再次继之以作业A）。然后，方法1500前进到图17的框1550，其中调配器服务器1240在所预测的加速需求之前供给一个或多个加速器资源205-2以加速工作负载内的作业。
现在参考图17，在供给加速器资源205-2中，在说明性实施例中，调配器服务器1240选择要供给的一个或多个现场可编程门阵列，如在框1552中所指示的。如在框1554中所指示的，在说明性实施例中，调配器服务器1240优选如下FPGA：所述FPGA已经被配置（例如被供给）以执行在将来要被加速的给定作业。通过优选（例如在其它FPGA之上选择）已经被供给以执行待加速作业的FPGA，调配器服务器1240可以节省否则将被消耗来进行如下的时间：向FPGA提供对所期望的配置进行指示的比特流，并且等待FPGA根据所期望的配置来配置其现场可编程门。调配器服务器1240可以在资源分配数据1412中存储如下信息：所述信息指示哪些FPGA已经被供给来执行哪些作业。在框1556中，在说明性实施例中，调配器服务器1240确定要供给的FPGA的数目，这诸如通过对已经被标识用于加速的作业的数目进行计数，确定可用FPGA的数目，以及确定为每个作业使用一个可用FPGA或如果可用FPGA的数目小于要加速的作业的数目，则确定多达可用FPGA的数目。在框1558中，调配器服务器1240可以选择与其上通过通用处理器来执行工作负载的橇板（例如计算橇板204-4）不同的橇板（例如加速器橇板1130）上的FPGA。如在框1560中所指示的，调配器服务器1240可以根据标的热生成、标的功率消耗和/或标的经济成本来选择FPGA。例如，一些FPGA在热生成和/或功率消耗方面可以比其它FPGA更高效，因为它们由更小的或以其它方式更高效的组件所组成。因而，为不太高效的FPGA进行冷却和供电的成本可以大于为其它FPGA进行冷却和供电。在框1562中，调配器服务器1240可以确定针对每个FPGA的配置时间（例如，配置FPGA以执行作业将过去的时间量）。最初，调配器服务器1240可能不能访问对供给特定FPGA所需的时间量进行指示的数据，并且可以代替地使用默认估计的时间（例如两分钟）。如果并且当调配器服务器1240确实供给FPGA时，调配器服务器1240可以测量供给FPGA所过去的实际时间量并且在稍后的确定中参考该测量时间。
在框1564中，调配器服务器1240向要被供给的每个FPGA提供（例如发送）对每个FPGA的期望配置进行指示的比特流。比特流可以包括特定于特别FPGA的架构的一部分（例如，用于初始化FPGA以用于配置），以及对用于执行待加速的对应作业的FPGA内的门的期望配置进行指示的另一部分。在提供比特流中，在说明性实施例中，并且如在框1566中所指示的，调配器服务器1240通过用于对应FPGA的所确定的配置时间而在预定于执行待加速作业的所预测时间（例如，图16的框1546中预测的时间）之前（例如，在所预测需求的时间之前）提供比特流。例如，如果用于FPGA的配置时间是两分钟，则在说明性实施例中，调配器服务器1240在将执行对应作业之前至少两分钟（例如在作业进入作业队列之前两分钟）将比特流发送到FPGA。
然后，方法1500前进到框1568，其中调配器服务器1240将加速器资源205-2分配到所管理的节点1260以加速工作负载的执行（例如在图16的框1526中被标识用于加速的工作负载作业）。在框1570中，在说明性实施例中，调配器服务器1240将来自框1550的所供给的FPGA分配到与被标识用于加速的作业相关联的所管理节点1260。调配器服务器1240可以通过如下来这样做：向每个所管理的节点1260提供针对对应FPGA的地址信息，以使得所管理的节点1260能够与FPGA通信。如在框1572中所指示的，调配器服务器1240可以将其它加速器资源205-2（例如图形加速器等等）分配给所管理的节点1260，诸如，如果一个或多个作业不适合通过FPGA的加速，如在图16的框1538直到1542中所确定的那样，或者如果数据中心1100中的可用FPGA集合已经被耗尽。在框1574中，调配器服务器1240可以从一个或多个所管理的节点1260解分配一个多个加速器资源205-2（例如，如果对应的作业已经完成的话），从而补充可用加速器资源205-2的集合。如在框1576中所指示的，在分配和/或解分配加速器资源205-2中，在说明性实施例中，调配器服务器1240这样做以满足所述一个或多个资源分配目标（例如，在资源分配目标数据1404中的目标）。例如，如果使特定作业加速将会增加性能超过标的资源分配目标（例如每秒的操作数），并且将会在数据中心1100的一个或多个区域中使得热生成超过标的温度，则调配器服务器1240可以确定不将加速器资源205-2分配给该作业。在一些实施例中，调配器服务器1240可以在框1550中供给操作之前，鉴于资源分配目标来确定最终是否分配加速器资源205-2来加速特定的作业。随后，方法1500返回到图15的框1522，其中在工作负载被执行时，调配器服务器1240继续收集遥测数据1402。
示例
以下提供本文中所公开的技术的说明性示例。技术的实施例可以包括下述示例中任何一个或多个、以及其任何组合。
示例1包括一种用于动态地管理加速器资源分配的调配器服务器，所述调配器服务器包括一个或多个处理器；已经在其中存储了多个指令的一个或多个存储器设备，所述指令当被所述一个或多个处理器执行的时候使得调配器服务器将工作负载指派给所管理的节点以用于执行；确定针对一个或多个加速器资源的、用于加速工作负载内一个或多个作业的执行的所预测需求；在所预测的需求之前供给一个或多个加速器资源来加速所述一个或多个作业；以及将所述一个或多个所供给的加速器资源分配给所管理的节点来加速所述一个或多个作业的执行。
示例2包括示例1的主题，并且其中确定所预测的需求包括确定针对一个或多个现场可编程门阵列（FPGA）的需求。
示例3包括示例1和2中任一个的主题，并且其中供给所述一个或多个加速器资源包括向所述一个或多个FPGA提供一比特流，所述比特流指示用于加速所述一个或多个作业的执行的每个FPGA的配置。
示例4包括示例1-3中任一个的主题，并且其中确定所预测的需求包括确定将分配以满足所预测的需求的加速器资源的数目。
示例5包括示例1-4中任一个的主题，并且其中供给所述一个或多个加速器资源包括供给位于与其上当前执行工作负载的橇板不同的一个或多个橇板上的一个或多个加速器资源。
示例6包括示例1-5中任一个的主题，并且其中所述多个指令当被执行的时候此外使得调配器服务器确定用于供给所述一个或多个加速器资源中每一个的配置时间段；以及确定所预测需求的所预测时间；并且其中供给所述一个或多个加速器资源包括在早于所预测时间至少所述配置时间段的时间开始配置所述一个或多个加速器资源以用于对所述一个或多个作业的加速执行。
示例7包括示例1-6中任一个的主题，并且其中所述多个指令当被执行的时候此外使得调配器服务器标识将利用一个或多个现场可编程门阵列（FPGA）来被加速的工作负载内的一个或多个作业；关联每个标识的作业与全局唯一标识符，所述全局唯一标识符指示作业的特定接口或作业的定义中的一个或多个。
示例8包括示例1-7中任一个的主题，并且其中关联每个标识的作业与全局唯一标识符包括关联每个标识的作业与如下全局唯一标识符：所述全局唯一标识符指示对作业的输入的格式或输入的大小中的一个或多个。
示例9包括示例1-8中任一个的主题，并且其中所管理的节点是多个所管理节点中之一，并且工作负载是由所管理的节点执行的多个工作负载之一，并且所述多个指令当被执行的时候此外使得调配器服务器为每个工作负载确定对在每个工作负载中执行作业的次数进行指示的局部计数；确定对由所有所管理节点执行作业的次数进行指示的全局计数；确定所述局部计数或全局计数中的一个或多个是否满足阈值计数值；以及响应于确定了所述局部计数或全局计数中的一个或多个满足阈值计数值而将相关联的作业标识为待加速的作业。
示例10包括示例1-9中任一个的主题，并且其中所述多个指令当被执行的时候此外使得调配器服务器从多个加速器资源中标识用于加速所述一个或多个作业的所述一个或多个加速器资源。
示例11包括示例1-10中任一个的主题，并且其中标识所述一个或多个加速器资源包括确定加速器资源中的一个或多个是否已经被配置成执行作业中的一个或多个；以及响应于确定了加速器资源中的一个或多个已经被配置成执行作业中的一个或多个而选择所述一个或多个已经配置过的加速器资源来用于所述一个或多个作业的加速。
示例12包括示例1-11中任一个的主题，并且其中标识所述一个或多个加速器资源包括根据以下各项中的一个或多个来选择所述一个或多个加速器资源：标的热生成、标的功率使用、或利用所述一个或多个加速器资源的标的经济成本。
示例13包括示例1-12中任一个的主题，并且其中所管理的节点是多个所管理节点之一，并且工作负载是由所管理节点执行的多个工作负载之一，并且其中确定需求包括建立作业队列，所述作业队列指示针对将被执行的所有工作负载的所有作业；确定其中每个作业驻留在作业队列中的平均时间段；以及根据针对每个作业的平均时间段来确定针对每个作业的需求。
示例14包括示例1-13中任一个的主题，并且其中确定针对每个作业的需求此外包括将指数平均算法应用到其中每个作业驻留在作业队列中的时间段。
示例15包括一种用于动态地管理加速器资源分配的方法，所述方法包括：通过调配器服务器来将工作负载指派到所管理的节点以用于执行；通过调配器服务器来确定针对一个或多个加速器资源的、用于加速工作负载内一个或多个作业的执行的所预测需求；通过调配器服务器并且在所预测的需求之前供给一个或多个加速器资源来加速所述一个或多个作业；以及通过调配器服务器来将所述一个或多个所供给的加速器资源分配给所管理的节点来加速所述一个或多个作业的执行。
示例16包括示例15的主题，并且其中确定所预测的需求包括确定针对一个或多个现场可编程门阵列（FPGA）的需求。
示例17包括示例15和16中任一个的主题，并且其中供给所述一个或多个加速器资源包括向所述一个或多个FPGA提供一比特流，所述比特流指示用于加速所述一个或多个作业的执行的每个FPGA的配置。
示例18包括示例15-17中任一个的主题，并且其中确定所预测的需求包括确定将分配以满足所预测的需求的加速器资源的数目。
示例19包括示例15-18中任一个的主题，并且其中供给所述一个或多个加速器资源包括供给位于与其上当前执行工作负载的橇板不同的一个或多个橇板上的一个或多个加速器资源。
示例20包括示例15-19中任一个的主题，并且此外包括通过调配器服务器来确定用于供给所述一个或多个加速器资源中每一个的配置时间段；以及通过调配器服务器来确定所预测需求的所预测时间；并且其中供给所述一个或多个加速器资源包括在早于所预测时间至少所述配置时间段的时间开始配置所述一个或多个加速器资源以用于对所述一个或多个作业的加速执行。
示例21包括示例15-20中任一个的主题，并且此外包括通过调配器服务器来标识将利用一个或多个现场可编程门阵列（FPGA）来被加速的工作负载内的一个或多个作业；以及通过调配器服务器来关联每个标识的作业与全局唯一标识符，所述全局唯一标识符指示作业的特定接口或作业的定义中的一个或多个。
示例22包括示例15-21中任一个的主题，并且其中关联每个标识的作业与全局唯一标识符包括关联每个标识的作业与如下全局唯一标识符：所述全局唯一标识符指示对作业的输入的格式或输入的大小中的一个或多个。
示例23包括示例15-22中任一个的主题，并且其中所管理的节点是多个所管理节点中之一，并且工作负载是由所管理的节点执行的多个工作负载之一，所述方法此外包括通过调配器服务器并且为每个工作负载确定对在每个工作负载中执行作业的次数进行指示的局部计数；通过调配器服务器确定对由所有所管理节点执行作业的次数进行指示的全局计数；通过调配器服务器确定所述局部计数或全局计数中的一个或多个是否满足阈值计数值；以及通过调配器服务器并且响应于确定了所述局部计数或全局计数中的一个或多个满足阈值计数值而将相关联的作业标识为待加速的作业。
示例24包括示例15-23中任一个的主题，并且此外包括通过调配器服务器且从多个加速器资源中标识用于加速所述一个或多个作业的所述一个或多个加速器资源。
示例25包括示例15-24中任一个的主题，并且其中标识所述一个或多个加速器资源包括确定加速器资源中的一个或多个是否已经被配置成执行作业中的一个或多个，所述方法此外包括通过调配器服务器响应于确定了加速器资源中的一个或多个已经被配置成执行作业中的一个或多个而选择所述一个或多个已经配置过的加速器资源来用于所述一个或多个作业的加速。
示例26包括示例15-25中任一个的主题，并且其中标识所述一个或多个加速器资源包括根据以下各项中的一个或多个来选择所述一个或多个加速器资源：标的热生成、标的功率使用、或利用所述一个或多个加速器资源的标的经济成本。
示例27包括示例15-26中任一个的主题，并且其中所管理的节点是多个所管理节点之一，并且工作负载是由所管理节点执行的多个工作负载之一，并且其中确定需求包括建立作业队列，所述作业队列指示针对将被执行的所有工作负载的所有作业；确定其中每个作业驻留在作业队列中的平均时间段；以及根据针对每个作业的平均时间段来确定针对每个作业的需求。
示例28包括示例15-27中任一个的主题，并且其中确定针对每个作业的需求此外包括将指数平均算法应用到其中每个作业驻留在作业队列中的时间段。
示例29包括一种调配器服务器，其包括用于执行示例15-28中任一个的方法的构件。
示例30包括一种用于动态地管理加速器资源分配的调配器服务器，所述调配器服务器包括一个或多个处理器；已经在其中存储了多个指令的一个或多个存储器设备，所述指令当被所述一个或多个处理器执行的时候使得调配器服务器执行示例15-28中任一个的方法。
示例31包括一个或多个机器可读存储介质，其包括被存储在其上的多个指令，所述指令响应于被执行，使得调配器服务器执行示例15-28中任一个的方法。
示例32包括一种用于动态地管理加速器资源分配的调配器服务器，所述调配器服务器包括资源管理器电路，其用于将工作负载指派给所管理的节点以用于执行，确定针对一个或多个加速器资源的、用于加速工作负载内一个或多个作业的执行的所预测需求，在所预测的需求之前供给一个或多个加速器资源来加速所述一个或多个作业，以及将所述一个或多个所供给的加速器资源分配给所管理的节点来加速所述一个或多个作业的执行。
示例33包括示例32的主题，并且其中确定所预测的需求包括确定针对一个或多个现场可编程门阵列（FPGA）的需求。
示例34包括示例32和33中任一个的主题，并且其中供给所述一个或多个加速器资源包括向所述一个或多个FPGA提供一比特流，所述比特流指示用于加速所述一个或多个作业的执行的每个FPGA的配置。
示例35包括示例32-34中任一个的主题，并且其中确定所预测的需求包括确定将分配以满足所预测的需求的加速器资源的数目。
示例36包括示例32-35中任一个的主题，并且其中供给所述一个或多个加速器资源包括供给位于与其上当前执行工作负载的橇板不同的一个或多个橇板上的一个或多个加速器资源。
示例37包括示例32-36中任一个的主题，并且其中所述资源管理器电路此外将确定用于供给所述一个或多个加速器资源中每一个的配置时间段；以及确定所预测需求的所预测时间；并且其中供给所述一个或多个加速器资源包括在早于所预测时间至少所述配置时间段的时间开始配置所述一个或多个加速器资源以用于对所述一个或多个作业的加速执行。
示例38包括示例32-37中任一个的主题，并且其中资源管理器电路此外将标识将利用一个或多个现场可编程门阵列（FPGA）来被加速的工作负载内的一个或多个作业；关联每个标识的作业与全局唯一标识符，所述全局唯一标识符指示作业的特定接口或作业的定义中的一个或多个。
示例39包括示例32-38中任一个的主题，并且其中关联每个标识的作业与全局唯一标识符包括关联每个标识的作业与如下全局唯一标识符：所述全局唯一标识符指示对作业的输入的格式或输入的大小中的一个或多个。
示例40包括示例32-39中任一个的主题，并且其中所管理的节点是多个所管理节点中之一，并且工作负载是由所管理的节点执行的多个工作负载之一，并且所述资源管理器电路此外将为每个工作负载确定对在每个工作负载中执行作业的次数进行指示的局部计数；确定对由所有所管理节点执行作业的次数进行指示的全局计数；确定所述局部计数或全局计数中的一个或多个是否满足阈值计数值；以及响应于确定了所述局部计数或全局计数中的一个或多个满足阈值计数值而将相关联的作业标识为待加速的作业。
示例41包括示例32-40中任一个的主题，并且其中所述资源管理器电路此外将从多个加速器资源中标识用于加速所述一个或多个作业的所述一个或多个加速器资源。
示例42包括示例32-41中任一个的主题，并且其中标识所述一个或多个加速器资源包括确定加速器资源中的一个或多个是否已经被配置成执行作业中的一个或多个；以及响应于确定了加速器资源中的一个或多个已经被配置成执行作业中的一个或多个而选择所述一个或多个已经配置过的加速器资源来用于所述一个或多个作业的加速。
示例43包括示例32-42中任一个的主题，并且其中标识所述一个或多个加速器资源包括根据以下各项中的一个或多个来选择所述一个或多个加速器资源：标的热生成、标的功率使用、或利用所述一个或多个加速器资源的标的经济成本。
示例44包括示例32-43中任一个的主题，并且其中所管理的节点是多个所管理节点之一，并且工作负载是由所管理节点执行的多个工作负载之一，并且其中确定需求包括建立作业队列，所述作业队列指示针对将被执行的所有工作负载的所有作业；确定其中每个作业驻留在作业队列中的平均时间段；以及根据针对每个作业的平均时间段来确定针对每个作业的需求。
示例45包括示例32-44中任一个的主题，并且其中确定针对每个作业的需求此外包括将指数平均算法应用到其中每个作业驻留在作业队列中的时间段。
示例46包括一种用于动态地管理加速器资源分配的调配器服务器，所述调配器服务器包括用于将工作负载指派给所管理的节点以用于执行的电路；用于确定针对一个或多个加速器资源的、用于加速工作负载内一个或多个作业的执行的所预测需求的构件；用于通过调配器服务器并且在所预测的需求之前供给一个或多个加速器资源来加速所述一个或多个作业的电路；以及用于将所述一个或多个所供给的加速器资源分配给所管理的节点来加速所述一个或多个作业的执行的电路。
示例47包括示例46的主题，并且其中所述用于确定所预测的需求的构件包括用于确定针对一个或多个现场可编程门阵列（FPGA）的需求的构件。
示例48包括示例46和47中任一个的主题，并且其中所述用于供给所述一个或多个加速器资源的电路包括用于向所述一个或多个FPGA提供一比特流的电路，所述比特流指示用于加速所述一个或多个作业的执行的每个FPGA的配置。
示例49包括示例46-48中任一个的主题，并且其中用于确定所预测的需求的构件包括用于确定将分配以满足所预测的需求的加速器资源的数目的构件。
示例50包括示例46-49中任一个的主题，并且其中所述用于供给所述一个或多个加速器资源的电路包括用于供给位于与其上当前执行工作负载的橇板不同的一个或多个橇板上的一个或多个加速器资源的电路。
示例51包括示例46-50中任一个的主题，并且此外包括用于确定用以供给所述一个或多个加速器资源中每一个的配置时间段的电路；以及用于确定所预测需求的所预测时间的构件；以及其中所述用于供给所述一个或多个加速器资源的电路包括用于在早于所预测时间至少所述配置时间段的时间开始配置所述一个或多个加速器资源以用于对所述一个或多个作业的加速执行的电路。
示例52包括示例46-51中任一个的主题，并且此外包括用于标识将利用一个或多个现场可编程门阵列（FPGA）来被加速的工作负载内的一个或多个作业的构件；以及用于关联每个标识的作业与全局唯一标识符的电路，所述全局唯一标识符指示作业的特定接口或作业的定义中的一个或多个。
示例53包括示例46-52中任一个的主题，并且其中所述用于关联每个标识的作业与全局唯一标识符的电路包括用于关联每个标识的作业与如下全局唯一标识符的电路：所述全局唯一标识符指示对作业的输入的格式或输入的大小中的一个或多个。
示例54包括示例46-53中任一个的主题，并且其中所管理的节点是多个所管理节点之一，并且工作负载是由所管理节点执行的多个工作负载之一，所述调配器服务器此外包括用于为每个工作负载确定对在每个工作负载中执行作业的次数进行指示的局部计数的电路；用于确定对由所有所管理节点执行作业的次数进行指示的全局计数的电路；用于确定所述局部计数或全局计数中的一个或多个是否满足阈值计数值的电路；以及用于响应于确定了所述局部计数或全局计数中的一个或多个满足阈值计数值而将相关联的作业标识为待加速的作业的电路。
示例55包括示例46-54中任一个的主题，并且此外包括用于从多个加速器资源中标识用于加速所述一个或多个作业的所述一个或多个加速器资源的电路。
示例56包括示例46-55中任一个的主题，并且其中所述用于标识所述一个或多个加速器资源的电路包括用于确定加速器资源中的一个或多个是否已经被配置成执行作业中的一个或多个的电路，所述调配器服务器此外包括用于响应于确定了加速器资源中的一个或多个已经被配置成执行作业中的一个或多个而选择所述一个或多个已经配置过的加速器资源来用于所述一个或多个作业的加速的电路。
示例57包括示例46-56中任一个的主题，并且其中所述用于标识所述一个或多个加速器资源的电路包括用于根据以下各项中的一个或多个来选择所述一个或多个加速器资源的电路：标的热生成、标的功率使用、或利用所述一个或多个加速器资源的标的经济成本。
示例58包括示例46-57中任一个的主题，并且其中所管理的节点是多个所管理节点之一，并且工作负载是由所管理节点执行的多个工作负载之一，并且其中用于确定需求的构件包括用于建立作业队列的电路，所述作业队列指示针对将被执行的所有工作负载的所有作业；用于确定其中每个作业驻留在作业队列中的平均时间段的电路；以及用于根据针对每个作业的平均时间段来确定针对每个作业的需求的电路。
示例59包括示例46-58中任一个的主题，并且其中所述用于确定针对每个作业的需求的构件此外包括用于将指数平均算法应用到其中每个作业驻留在作业队列中的时间段的电路。

Claims (29)

1.一种用于动态地管理加速器资源分配的调配器服务器，所述调配器服务器包括：
一个或多个处理器；
已经在其中存储了多个指令的一个或多个存储器设备，所述指令当被所述一个或多个处理器执行的时候使得调配器服务器：
将工作负载指派给所管理的节点以用于执行；
从所管理的节点接收对性能和条件进行指示的遥测数据；
基于对遥测数据进行评估以及对一个或多个作业执行中的模式进行标识来确定针对一个或多个加速器资源的、用于加速工作负载内一个或多个作业的执行的所预测需求何时发生；
在所预测的需求之前供给一个或多个加速器资源来加速所述一个或多个作业；以及
将所述一个或多个所供给的加速器资源分配给所管理的节点来加速所述一个或多个作业的执行。
2.根据权利要求1所述的调配器服务器，其中确定所预测的需求包括确定针对一个或多个现场可编程门阵列(FPGA)的需求。
3.根据权利要求2所述的调配器服务器，其中供给所述一个或多个加速器资源包括向所述一个或多个FPGA提供一比特流，所述比特流指示用于加速所述一个或多个作业的执行的每个FPGA的配置。
4.根据权利要求1所述的调配器服务器，其中确定所预测的需求包括确定将分配以满足所预测的需求的加速器资源的数目。
5.根据权利要求1所述的调配器服务器，其中供给所述一个或多个加速器资源包括供给位于与其上当前执行工作负载的橇板不同的一个或多个橇板上的一个或多个加速器资源。
6.根据权利要求1所述的调配器服务器，其中所述多个指令当被执行的时候此外使得调配器服务器：
确定用于供给所述一个或多个加速器资源中每一个的配置时间段；以及
确定所预测需求的所预测时间；并且
其中供给所述一个或多个加速器资源包括在早于所预测时间至少所述配置时间段的时间开始配置所述一个或多个加速器资源以用于对所述一个或多个作业的加速执行。
7.根据权利要求1所述的调配器服务器，其中所述多个指令当被执行的时候此外使得调配器服务器：
标识将利用一个或多个现场可编程门阵列(FPGA)来被加速的工作负载内的一个或多个作业；
关联每个标识的作业与全局唯一标识符，所述全局唯一标识符指示作业的特定接口或作业的定义中的一个或多个。
8.根据权利要求7所述的调配器服务器，其中关联每个标识的作业与全局唯一标识符包括关联每个标识的作业与如下全局唯一标识符：所述全局唯一标识符指示对作业的输入的格式或输入的大小中的一个或多个。
9.根据权利要求1所述的调配器服务器，其中所管理的节点是多个所管理节点中之一，并且所述工作负载是由所管理节点执行的多个工作负载之一，并且所述多个指令当被执行的时候此外使得调配器服务器：
为每个工作负载确定对在每个工作负载中执行作业的次数进行指示的局部计数；
确定对由所有所管理节点执行作业的次数进行指示的全局计数；
确定所述局部计数或全局计数中的一个或多个是否满足阈值计数值；以及
响应于确定了所述局部计数或全局计数中的一个或多个满足阈值计数值而将相关联的作业标识为待加速的作业。
10.根据权利要求9所述的调配器服务器，其中所述多个指令当被执行的时候此外使得调配器服务器从多个加速器资源中标识用于加速所述一个或多个作业的所述一个或多个加速器资源。
11.根据权利要求10所述的调配器服务器，其中标识所述一个或多个加速器资源包括确定加速器资源中的一个或多个是否已经被配置成执行作业中的一个或多个；以及
响应于确定了加速器资源中的一个或多个已经被配置成执行作业中的一个或多个而选择所述一个或多个已经配置过的加速器资源来用于所述一个或多个作业的加速。
12.根据权利要求10所述的调配器服务器，其中标识所述一个或多个加速器资源包括根据以下各项中的一个或多个来选择所述一个或多个加速器资源：标的热生成、标的功率使用、或利用所述一个或多个加速器资源的标的经济成本。
13.根据权利要求1所述的调配器服务器，其中所管理的节点是多个所管理的节点之一，并且工作负载是由所管理的节点所执行的多个工作负载之一，并且其中确定需求包括：
建立对针对待执行的所有工作负载的所有作业进行指示的作业队列；
确定其中每个作业驻留在作业队列中的平均时间段；以及
根据针对每个作业的平均时间段来确定针对每个作业的需求。
14.根据权利要求13所述的调配器服务器，其中确定针对每个作业的需求此外包括将指数平均算法应用到其中每个作业驻留在作业队列中的时间段。
15.一种用于动态地管理加速器资源分配的调配器服务器，所述调配器服务器包括：
用于将工作负载指派给所管理的节点以用于执行的电路；
用于从所管理的节点接收对性能和条件进行指示的遥测数据的构件；
用于基于对遥测数据进行评估以及对一个或多个作业执行中的模式进行标识来确定针对一个或多个加速器资源的、用于加速工作负载内一个或多个作业的执行的所预测需求何时发生的构件；
用于通过调配器服务器并且在所预测的需求之前供给一个或多个加速器资源来加速所述一个或多个作业的电路；以及
用于将所述一个或多个所供给的加速器资源分配给所管理的节点来加速所述一个或多个作业的执行的电路。
16.根据权利要求15所述的调配器服务器，其中所述用于确定所预测的需求的构件包括用于确定针对一个或多个现场可编程门阵列(FPGA)的需求的构件。
17.根据权利要求16所述的调配器服务器，其中所述用于供给所述一个或多个加速器资源的电路包括用于向所述一个或多个FPGA提供一比特流的电路，所述比特流指示用于加速所述一个或多个作业的执行的每个FPGA的配置。
18.根据权利要求15所述的调配器服务器，其中所述用于确定所预测的需求的构件包括用于确定将分配以满足所预测的需求的加速器资源的数目的构件。
19.根据权利要求15所述的调配器服务器，其中所述用于供给所述一个或多个加速器资源的电路包括用于供给位于与其上当前执行工作负载的橇板不同的一个或多个橇板上的一个或多个加速器资源的电路。
20.根据权利要求15所述的调配器服务器，此外包括：
用于确定用来供给所述一个或多个加速器资源中每一个的配置时间段的电路；以及
用于确定所预测需求的所预测时间的构件；并且
其中所述用于供给所述一个或多个加速器资源的电路包括用于在早于所预测时间至少所述配置时间段的时间开始配置所述一个或多个加速器资源以用于对所述一个或多个作业的加速执行的电路。
21.根据权利要求15所述的调配器服务器，此外包括：
用于标识将利用一个或多个现场可编程门阵列(FPGA)来被加速的工作负载内的一个或多个作业的构件；以及
用于关联每个标识的作业与全局唯一标识符的电路，所述全局唯一标识符指示作业的特定接口或作业的定义中的一个或多个。
22.根据权利要求21所述的调配器服务器，其中所述用于关联每个标识的作业与全局唯一标识符的电路包括用于关联每个标识的作业与如下全局唯一标识符的电路：所述全局唯一标识符指示对作业的输入的格式或输入的大小中的一个或多个。
23.一种用于动态地管理加速器资源分配的方法，所述方法包括：
通过调配器服务器将工作负载指派给所管理的节点以用于执行；
通过调配器服务器从所管理的节点接收对性能和条件进行指示的遥测数据；基于对遥测数据进行评估以及对一个或多个作业执行中的模式进行标识通过调配器服务器来确定针对一个或多个加速器资源的、用于加速工作负载内一个或多个作业的执行的所预测需求何时发生；
通过调配器服务器并且在所预测的需求之前供给一个或多个加速器资源来加速所述一个或多个作业；以及
通过调配器服务器来将所述一个或多个所供给的加速器资源分配给所管理的节点来加速所述一个或多个作业的执行。
24.根据权利要求23所述的方法，其中确定所预测的需求包括确定针对一个或多个现场可编程门阵列(FPGA)的需求。
25.根据权利要求24所述的方法，其中供给所述一个或多个加速器资源包括向所述一个或多个FPGA提供一比特流，所述比特流指示用于加速所述一个或多个作业的执行的每个FPGA的配置。
26.一种用于动态地管理加速器资源分配的设备，所述设备包括：
用于将工作负载指派给所管理的节点以用于执行的装置；
用于从所管理的节点接收对性能和条件进行指示的遥测数据的装置；
用于基于对遥测数据进行评估以及对一个或多个作业执行中的模式进行标识确定针对一个或多个加速器资源的、用于加速工作负载内一个或多个作业的执行的所预测需求何时发生的装置；
用于在所预测的需求之前供给一个或多个加速器资源来加速所述一个或多个作业的装置；以及
用于将所述一个或多个所供给的加速器资源分配给所管理的节点来加速所述一个或多个作业的执行的装置。
27.根据权利要求26所述的设备，其中用于确定所预测的需求的装置包括用于确定针对一个或多个现场可编程门阵列(FPGA)的需求的装置。
28.根据权利要求27所述的设备，其中用于供给所述一个或多个加速器资源的装置包括用于向所述一个或多个FPGA提供一比特流的装置，所述比特流指示用于加速所述一个或多个作业的执行的每个FPGA的配置。
29.一种计算机可读介质，在其上具有指令，当指令被执行时导致计算机设备执行根据权利要求23-25中任一个的方法。
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CN201780039632.0A Pending CN109416648A (zh) 2016-07-22 2017-06-22 利用遥感数据在线分析进行协调的技术
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CN201780038941.6A Pending CN109328338A (zh) 2016-07-22 2017-06-22 用于确定和处理物理资源的度量数据的技术
CN201780038670.4A Active CN109313582B (zh) 2016-07-22 2017-06-22 用于动态远程资源分配的技术
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