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What are the key functions of compute? What are the benefits of containers? Why is compute essential to enterprise organizations? What is the Significance of compute in the context of computing? What are the Fundamentals of Compute? What is Compute Technologies and Paradigms? What is Compute in Cloud Computing? What is Compute in Edge Computing? What is Compute in Internet of Things (IoT)? What is Compute in Artificial Intelligence (AI)? What is Compute Performance and Optimization? Why HPE for compute? tabs" min-open-items="0 | @+LG => 1" max-open-items="1"> What are the key functions of compute? What are the key functions of compute? The key functions of compute include: Problem-solving: With compute from edge to cloud, you can prevent complex problems with AI-powered systems in just a fraction of a second. Data processing and storage: Compute involves the processes of receiving, analyzing, and storing data. This data includes any and all information that is collected and moved between business apps and the web. Once the data is processed and stored, it can be further analyzed and used by ITDMs and managers to develop solutions. Optimized opportunities: Optimized, intelligent compute systems support opportunities to tap into a new business segment or attain a new level of profitability. What are the benefits of containers? What are the benefits of containers? Containers provide developers with several benefits, including: Portability: Containers contain programs and their dependencies, allowing them to function reliably in development, testing, and production settings regardless of infrastructure. Scalability: Kubernetes and other orchestration technologies can effortlessly scale containers up or down to suit workload needs. Efficiency: By sharing the host operating system's kernel, containers utilize fewer system resources than conventional virtual machines (VMs), which results in quicker startup times and lower overhead. Isolation: Containers isolate applications from one other and the host system, boosting security, stability, and the flexibility to execute many workloads on one host. Fast deployment: Containers make it easier to launch apps by including everything needed to run them. This helps developers release updates and new features more quickly. Consistency across settings: Developers may assure that locally tested code operates similarly

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Prev Next Issue date: 2021-10-18Applies to: Virtuozzo Hybrid Infrastructure 4.7Virtuozzo Advisory ID: VZA-2021-0501. Overview¶In this release, Virtuozzo Hybrid Infrastructure provides a wide range of new features that enhance service providers’ interoperability and help expand their services. The improvements cover compute services, object storage, core storage, monitoring, high availability for the management node, updates, and the user interface. Additionally, this release delivers stability improvements and addresses issues found in previous releases.2. New Features¶[Compute service] Online resize of virtual machines. It is now possible to scale up a running virtual machine by adding more CPU and RAM resources to it with no downtime. CPU and RAM hot plug is configured for self-service users per domain.[Compute service] Ability to attach a virtual CD-ROM to a virtual machine. By mounting an ISO image to a virtual machine as a virtual CD-ROM, users can install additional software or restore a guest operating system.[Compute service] Rescue mode for Windows and Linux virtual machines from an ISO image. As a part of the rescue mode, you can boot any virtual machine from a recovery CD-ROM or a bootable ISO image.[Compute service] IPv6 support for virtual machines. Virtual machines can now be assigned IPv6 addresses. IPv6 subnets are available only for physical compute networks. In this release, IPv6 addresses are not supported for load balancers and Kubernetes clusters.[Compute service] PCI passthrough to virtual machines. You can accelerate a virtual machine by attaching a host PCI device to it. The following PCI devices are supported: a physical GPU card, an HBA adapter, and a virtual/physical function of an SR-IOV capable network card.[Compute service] Support for Kubernetes versions 1.20 and 1.21. Added the full support of Kubernetes versions 1.20 and 1.21 for deploying and upgrading Kubernetes clusters.[Compute service] Support for the baseline AMD EPYC CPU model. The baseline EPYC CPU model can be set for compute cluster. Management of the CPU model is available only in the command-line interface.[Compute service] Renewal of Kubernetes cluster certificates. Added the possibility to renew Kubernetes cluster CA certificates when they expire. Certificate renewal is available only in the command-line interface.[Compute service] Outgoing traffic usage

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Header (math.h)C numerics libraryHeader declares a set of functions to compute common mathematical operations and transformations:FunctionsTrigonometric functionscosCompute cosine (function)sinCompute sine (function)tanCompute tangent (function)acosCompute arc cosine (function)asinCompute arc sine (function)atanCompute arc tangent (function)atan2Compute arc tangent with two parameters (function)Hyperbolic functionscoshCompute hyperbolic cosine (function)sinhCompute hyperbolic sine (function)tanhCompute hyperbolic tangent (function)acosh Compute area hyperbolic cosine (function)asinh Compute area hyperbolic sine (function)atanh Compute area hyperbolic tangent (function)Exponential and logarithmic functionsexpCompute exponential function (function)frexpGet significand and exponent (function)ldexpGenerate value from significand and exponent (function)logCompute natural logarithm (function)log10Compute common logarithm (function)modfBreak into fractional and integral parts (function)exp2 Compute binary exponential function (function)expm1 Compute exponential minus one (function)ilogb Integer binary logarithm (function)log1p Compute logarithm plus one (function)log2 Compute binary logarithm (function)logb Compute floating-point base logarithm (function)scalbn Scale significand using floating-point base exponent (function)scalbln Scale significand using floating-point base exponent (long) (function)Power functionspowRaise to power (function)sqrtCompute square root (function)cbrt Compute cubic root (function)hypot Compute hypotenuse (function)Error and gamma functionserf Compute error function (function)erfc Compute complementary error function (function)tgamma Compute gamma function (function)lgamma Compute log-gamma function (function)Rounding and remainder functionsceilRound up value (function)floorRound down value (function)fmodCompute remainder of division (function)trunc Truncate value (function)round Round to nearest (function)lround Round to nearest and cast to long integer (function)llround Round to nearest and cast to long long integer (function)rint Round to integral value (function)lrint Round and cast to long integer (function)llrint Round and cast to long long integer (function)nearbyint Round to nearby integral value (function)remainder Compute remainder (IEC 60559) (function)remquo Compute remainder and quotient (function)Floating-point manipulation functionscopysign Copy sign (function)nan Generate quiet. computers,computer,slow computer,computer virus,computer memory,computer shorts,inside a computer,computer hardware,computer shorts video,lil herb computers,computers

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Computing connects multiple computers for increased computational power, while grid computing connects distributed resources to create a virtual supercomputer. High-performance computing (HPC) involves supercomputers and clusters for complex problem-solving, accelerators like GPUs and FPGAs for efficient computations, and the emerging field of quantum computing that leverages quantum mechanics to solve problems faster than classical computers. These compute technologies and paradigms offer various ways to enhance computational capabilities, improve performance, and tackle complex computational challenges. What is Compute in Cloud Computing? What is Compute in Cloud Computing? The term "compute" in the context of cloud computing refers to the supply and administration of virtualized resources for the accomplishment of computational activities. Here are some key aspects related to compute in cloud computing: Virtualized compute resources involve using virtual machines (VMs) and containers to create isolated environments for running applications. VMs emulate entire computer systems, while containers are lightweight and package applications with their dependencies. Containers are more efficient and scalable compared to VMs, providing faster startup times and easier portability across different computing environments. Infrastructure as a service (IaaS) is like renting computer resources from the cloud. It includes things like storage, networking, and computing power. With IaaS, users may choose the operating system and apps they want to use while using these services. Elasticity and scalability of compute resources mean that in cloud computing, you can easily adjust the amount of computing power you need. If your workload increases, you can quickly add more resources. If it decreases, you can reduce the resources. This flexibility ensures that your applications have the right amount of computing power to handle changes in demand. What is Compute in Edge Computing? What is Compute in Edge Computing? "Compute" refers to the processing and computational capabilities installed near the network's edge, closer to where data is created or consumed. In edge computing, the following are important compute-related factors: In edge computing, "compute" refers to the processing and computational capabilities deployed at the edge of the network, closer to where data is generated or consumed. Here are key aspects related to compute in edge computing: Edge

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Virtual machines are created from templates and are deployed on hypervisors (compute resources) that provide them with CPU, disk, network, and other necessary resources. To create a virtual machine, you need to launch a wizard. The wizard walks you through several steps to get your virtual machine up and running. In this document, you can find a detailed guide on how to create a virtual machine, but first, take a look at the following section.PrerequisitesBefore you begin to create a virtual machine, take into consideration the following:You should have at least one hypervisor (compute resource) configured and attached to a compute zone, a data store – to a data store zone and hypervisor (compute resource) or compute zone, a network – to a network zone and hypervisor (compute resource) or compute zone, a backup server – to a backup server zone and hypervisor (compute resource) or compute zone, and a bucket - to a user who creates a virtual machine.The selected template should reside on a backup server attached to a hypervisor (compute resource) or compute zone on which you want to build a virtual machine.New virtual machines built on Virtuozzo Hybrid Server hypervisors (compute resources) must be based on Virtuozzo Hybrid Server templates or ISO images.Refer to the Supported Guest Operating Systems to learn more about the limitations of templates.An Estimated Price per Hour in the wizard might be inaccurate if you don’t have necessary permissions enabled, such as Show Compute Zones/Compute Resources on Virtual Server Creation; and if you select the Any option for network resources.To create a virtual machineGo to your Control Panel > Cloud > Virtual Servers.Click the Add button () or the Create Virtual Server button to launch the wizard.Follow the step-by-step instructions below to complete the wizard.After you are finished, click the Create Virtual Server button.TemplatesThe Templates step allows you to select a template from which to build your virtual machine. The template is extracted when a virtual machine is provisioned or when a backup is taken, using this template. While a template is being extracted, it is locked so that it can’t be used simultaneously in other transactions. After the extraction is finished, the template is unlocked. If another transaction requires the locked template, the transaction will fail after five minutes of standby. If a transaction that locked a template eventually failed, it means that the extracted template is broken. The templates are stored at /onapp/templates/your_template.tgz, extracted templates – at /onapp/backups/templates/your_template, and locked templates – at /onapp/backups/templates/your_template.lock.To select a templateClick the Template Store icon on the left to see templates that are available in this store. You can see the following details for each template:LabelMin memory size that is required to create a

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Version 3 - Memory requirements110kB for complete installation on HP50G and HP49G+80kB for installation of Core modules (CLOSE, COGO, LEVEL and UTILS modules)QUICKCLOSE Feature listing & Comparison between Versions 2 and 3CLOSE MODULEV 2V 3COGO MODULEV 2V 3Compute misclose√√Easy entry of coordinate data√√Compute 2 missing distances√√Entry of height (RL) data option √Compute 2 missing bearings√√View, edit & delete data√√Compute missing brg & distance√√Job storage limit6anyInsert missing elements into data √user-defined job descriptor √Compute area√√Compute coordinates by traverse√√Display area in square feet √Compute traverse misclose√√Display area in acres, rood, perch √Compute radiations (sideshots)√√View and edit data entry√√Compute inverses/joins (stakeout)√√Job storage limit6anyCompute inverses in traverse mode √user-defined job descriptor √Compute points by line & offset √Compute coordinates√√points on curve by chainage & offset √Print coordinates to IR printer√√Compute intersection of two bearings√√Export coordinates to COGO√√Compute intersection of two distances√√Resume data entry√√Compute intersection of brg & dist √Print data to IR printer√√Compute 3 point resection√√Print data to ASCII text file √Compute area from points√√Summation of partial distances √Setout (stakeout) by line & offset√√Easy entry of reverse bearings√√Setout (stakeout) arc by chnge & offset √Undo data entry√√Compute eccentric stand point √Convert feet, inches, fractions√√Compute two point resection √Convert survey links√√Apply preset bearing corrections√√Convert US Survey decimal feet √Apply preset scale factor to distances√√Convert DMS to Decimal and vice-versa √import ASCII coordinate file√√convert area units √Import/export format options √On-the-fly bearing corrections√√print coordinate data to IR printer√√Entry of curved elements√√Export ASCII coordinate file√√Compute arc length & segment area√√Export COGO data to CLOSE module√√Mean of two DMS

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The rows of a report into subsets with the BREAK command, you can perform various computations on the rows in each subset. You do this with the functions of the SQL*Plus COMPUTE command. Use the BREAK and COMPUTE commands together in the following forms:BREAK ON break_columnCOMPUTE function LABEL label_name OF column column column... ON break_columnYou can include multiple break columns and actions, such as skipping lines in the BREAK command, as long as the column you name after ON in the COMPUTE command also appears after ON in the BREAK command. To include multiple break columns and actions in BREAK when using it in conjunction with COMPUTE, use these commands in the following forms:BREAK ON break_column_1 SKIP PAGE ON break_column_2 SKIP 1COMPUTE function LABEL label_name OF column column column... ON break_column_2The COMPUTE command has no effect without a corresponding BREAK command.You can COMPUTE on NUMBER columns and, in certain cases, on all types of columns. See COMPUTE for details.The following table lists compute functions and their effects:FunctionEffectSUMComputes the sum of the values in the column.MINIMUMComputes the minimum value in the column.MAXIMUMComputes the maximum value in the column.AVGComputes the average of the values in the column.STDComputes the standard deviation of the values in the column.VARIANCEComputes the variance of the values in the column.COUNTComputes the number of non-null values in the column.NUMBERComputes the number of rows in the column.Table 4 - 1. Compute FunctionsThe function you specify in the COMPUTE command applies to all columns you enter after OFF and before ON. The computed values print on a separate line when the value of the ordered column changes.Labels for ON REPORT and ON ROW computations appear in the first column; otherwise, they appear in the column specified in the ON clause.You can change the compute label by using COMPUTE LABEL. If you do not define a label for the computed value, SQL*Plus prints the unabbreviated function keyword.The compute label can be suppressed by using the NOPRINT option of the COLUMN command on the break column. See the COMPUTE command for more details.Example 4-12 Computing and Printing SubtotalsTo compute the total of SAL by department, first list the current BREAK definition:SQL> BREAKbreak on DEPTNO skip 0 page nodup on JOB skip 1 nodupNow enter the following COMPUTE command and run the current query:SQL> COMPUTE SUM OF SAL ON DEPTNOSQL> /SQL*Plus displays the following output: DEPTNO JOB ENAME SAL---------- --------- ---------- ---------- 10 CLERK MILLER 1300 MANAGER CLARK 2450********** ********* ----------sum 3750 DEPTNO JOB ENAME SAL---------- --------- ---------- ---------- 20 CLERK SMITH 800 ADAMS 1100********** ********* ----------sum 1900 DEPTNO JOB ENAME SAL---------- --------- ---------- ---------- 30 CLERK JAMES 950 SALESMAN ALLEN 1600 TURNER 1500 WARD 1250 MARTIN 1250********** ********* ----------sum 6550To compute the sum of salaries for departments 10 and 20 without printing the compute label:SQL> COLUMN DUMMY NOPRINTSQL> COMPUTE SUM OF SAL ON DUMMYSQL> BREAK ON DUMMY SKIP 1SQL> SELECT DEPTNO DUMMY, DEPTNO, ENAME, SAL 2 FROM EMP 3 WHERE DEPTNO SQL*Plus displays the following output: DEPTNO ENAME SAL---------- ---------- ---------- 10 KING. computers,computer,slow computer,computer virus,computer memory,computer shorts,inside a computer,computer hardware,computer shorts video,lil herb computers,computers 2,731 Free Clipart Images of Computer. pc computer screen laptop computer computer user laptop technology monitor programmer desktop computer computer monitor. technology computer. computer monitor computer. computer desktop. animals cat. computer monitor. computer monitor. computer monitor. computer monitor. desktop computer computer

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All world pipe shader stages (Vertex, Tessellation, Geometry).PES contains the stream (transform feedback) unit.The VPC unit performs clip and cull.RASTERScreen PipeThe Raster units receives primitives from the world pipe, and outputs pixels (fragments) and samples (coverage masks) for the PROP, Pixel Shader, and ROP to process.PROPScreen PipeThe Pre-ROP unit orchestrates the flow of depth and color pixels (fragments) and samples, for final output. PROP enforces the API ordering of pixel shading, depth testing, and color blending. Early-Z and Late-Z modes are handled in PROP.ZROPScreen PipeThe Depth Raster Operation unit performs depth tests, stencil tests, and depth/stencil buffer updates.CROPScreen PipeThe Color Raster Operation unit performs the final color blend and render-target updates. CROP implements the “advanced blend equation”SM Occupancy RowsThe SM Occupancy row shows warp slot residency over time. Each Turing SM has 32 warp slots, where launched warps reside while they take turns issuing instructions.Asynchronous ComputeThe only way to concurrently run compute and 3D is by simultaneously:sending 3D work to the DIRECT queuesending compute work to an ASYNC_COMPUTE queueOn Ampere, you can also dispatch concurrent compute workloads by dispatching it on both the DIRECT and ASYNC_COMPUTE queue.You can detect whether a program is taking advantage of async compute in several ways:The “Compute In Flight” row contains an “Async Compute In Flight” counter.Observe when the compute warps executed on the SM Occupancy row, and determine if they were Sync or Async based on the color of the “Compute In Flight” row.Look for multiple queue rows; the ASYNC_COMPUTE queue will appear as something other than Q0.Compute will only run simultaneously with graphics if submitted on from an ASYNC_COMPUTE queue. This can disambiguate the SM Occupancy row.Warp Can’t Launch ReasonsWhen a draw call or compute dispatch enqueues more work than can fit onto the SMs all-at-once, the SMs will report that “additional warps

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This section discusses the task of implementing a class for the compute engine. In general, a class that implements a remote interface should at least do the following:Declare the remote interfaces being implementedDefine the constructor for each remote objectProvide an implementation for each remote method in the remote interfacesAn RMI server program needs to create the initial remote objects and export them to the RMI runtime, which makes them available to receive incoming remote invocations. This setup procedure can be either encapsulated in a method of the remote object implementation class itself or included in another class entirely. The setup procedure should do the following:Create and install a security managerCreate and export one or more remote objectsRegister at least one remote object with the RMI registry (or with another naming service, such as a service accessible through the Java Naming and Directory Interface) for bootstrapping purposesThe complete implementation of the compute engine follows. The engine.ComputeEngine class implements the remote interface Compute and also includes the main method for setting up the compute engine. Here is the source code for the ComputeEngine class:package engine;import java.rmi.RemoteException;import java.rmi.registry.LocateRegistry;import java.rmi.registry.Registry;import java.rmi.server.UnicastRemoteObject;import compute.Compute;import compute.Task;public class ComputeEngine implements Compute { public ComputeEngine() { super(); } public T executeTask(Task t) { return t.execute(); } public static void main(String[] args) { if (System.getSecurityManager() == null) { System.setSecurityManager(new SecurityManager()); } try { String name = "Compute"; Compute engine = new ComputeEngine(); Compute stub = (Compute) UnicastRemoteObject.exportObject(engine, 0); Registry registry = LocateRegistry.getRegistry(); registry.rebind(name, stub); System.out.println("ComputeEngine bound"); } catch (Exception e) { System.err.println("ComputeEngine exception:"); e.printStackTrace(); } }}The following sections discuss each component of the compute engine implementation.Declaring the Remote Interfaces Being ImplementedThe implementation class for the compute engine is declared as follows:public class ComputeEngine implements ComputeThis declaration states that the class implements the Compute remote interface and therefore can be used for a remote object.The ComputeEngine class defines a remote object implementation class that implements a single remote interface and no other interfaces. The ComputeEngine class also contains two executable program elements that can only be invoked locally. The first of these elements is a constructor for ComputeEngine instances. The second of these elements is a main method that is used to create a ComputeEngine instance and make it available to clients.Defining the Constructor for the Remote ObjectThe ComputeEngine class has a single constructor that takes no arguments. The code for the constructor is as follows:public ComputeEngine() { super();}This constructor just. computers,computer,slow computer,computer virus,computer memory,computer shorts,inside a computer,computer hardware,computer shorts video,lil herb computers,computers 2,731 Free Clipart Images of Computer. pc computer screen laptop computer computer user laptop technology monitor programmer desktop computer computer monitor. technology computer. computer monitor computer. computer desktop. animals cat. computer monitor. computer monitor. computer monitor. computer monitor. desktop computer computer

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Title description ms.assetid ms.topic ms.date Direct3D 11 Features The programming guide contains information about how to use the Direct3D 11 programmable pipeline to create realtime 3D graphics for games, and for scientific and desktop applications. ee4dae04-1a52-4587-87c1-006abb687a91 reference 05/31/2018 The programming guide contains information about how to use the Direct3D 11 programmable pipeline to create realtime 3D graphics for games, and for scientific and desktop applications.Compute ShaderDynamic Shader LinkingMultithreadingTessellationFull Listing of FeaturesFeatures Added in Previous ReleasesRelated topicsCompute ShaderA compute shader is a programmable shader designed for general-purpose data-parallel processing. In other words, compute shaders allow a GPU to be used as a general-purpose parallel processor. The compute shader is similar to the other programmable pipeline shaders (such as vertex, pixel, geometry) in the way that it accesses inputs and outputs. The compute shader technology is also known as the DirectCompute technology. A compute shader is integrated into Direct3D and is accessible through a Direct3D device. It can directly share memory resources with graphics shaders by using the Direct3D device. However, it is not directly connected to other shader stages.A compute shader is designed for mass-market applications that perform computations at interactive rates, when the cost of transitioning between the API (and its associated software stack) and a CPU would consume too much overhead.A compute shader has its own set of states. A compute shader does not necessarily have a forced 1-1 mapping to either input records (like a vertex shader does) or output records (like the pixel shader does). Some features of the graphics shader are supported, but others have been removed so that new compute shader-specific features could be added.To support the compute shader-specific features, several new resource types are now available, such as read/write buffers, textures, and structured buffers.See Compute Shader Overview for additional information.Dynamic Shader LinkingRendering systems must deal with significant complexity when they manage shaders, while providing the opportunity to optimize shader code. This becomes an even greater challenge because shaders must support a variety of different materials in a rendered scene across various hardware configurations. To address this challenge, shader developers have often resorted to one of two general approaches. They have either created fully featured large, general-purpose shaders that can be used by a wide variety of scene items, which trade off some performance for flexibility, or created individual shaders for each geometry stream, material type, or light type combination needed.These large, general-purpose shaders handle this challenge by recompiling the same shader with different preprocessor definitions, and the latter method uses brute-force developer power to achieve the same result. The shader permutation explosion has often been a problem for developers who must now manage thousands of different shader permutations within their game and asset pipeline.Direct3D