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  • Windows HPC Server links

    I've already described how to setup a Windows HPC Server for development. Before you dive into developing for the cluster, if you are new to this it is probably a good idea to learn the basics by reading some overview material. Below is a list of links.Direct Links to Windows HPC content1. Windows HPC Server 2008 Overview Datasheet (4 page pdf).2. Windows HPC Server 2008 Technical Overview (32 page doc).3. Windows HPC Server 2008 Getting Started Guide (26 page doc) which actually is available online as part of the TechNet technical library section on Windows HPC Server 2008, which includes much more useful data.4. Windows HPC Server 2008 Job Scheduler (38 page doc).5. Windows HPC Server 2008 Job Templates (56 page doc).6. Developing for the Windows HPC Server 2008 Platform (16 page doc or pdf version).Windows HPC sites7. Windows HPC Forums.8. HPC Developer Resources.9. Windows HPC Server 2008 Resource Kit - Developer.10. Windows HPC Server 2008 - TechNet.11. The Windows HPC Team Blog.HPC Course12. High-Performance Computing Fundamentals Course (pluralisight)13. Classic HPC Development using Visual C++ (course slides and materials in a ZIP). Author's blog post.14. From sequential to parallel code (course slides and materials in a ZIP). Author's blog post. Next time I will post resources specific to the most popular programming models for the cluster today: MPI and Cluster SOA - until then, happy reading! Comments about this post welcome at the original blog.

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  • Azure Grid Computing - Worker Roles as HPC Compute Nodes

    - by JoshReuben
    Overview ·        With HPC 2008 R2 SP1 You can add Azure worker roles as compute nodes in a local Windows HPC Server cluster. ·        The subscription for Windows Azure like any other Azure Service - charged for the time that the role instances are available, as well as for the compute and storage services that are used on the nodes. ·        Win-Win ? - Azure charges the computer hour cost (according to vm size) amortized over a month – so you save on purchasing compute node hardware. Microsoft wins because you need to purchase HPC to have a local head node for managing this compute cluster grid distributed in the cloud. ·        Blob storage is used to hold input & output files of each job. I can see how Parametric Sweep HPC jobs can be supported (where the same job is run multiple times on each node against different input units), but not MPI.NET (where different HPC Job instances function as coordinated agents and conduct master-slave inter-process communication), unless Azure is somehow tunneling MPI communication through inter-WorkerRole Azure Queues. ·        this is not the end of the story for Azure Grid Computing. If MS requires you to purchase a local HPC license (and administrate it), what's to stop a 3rd party from doing this and encapsulating exposing HPC WCF Broker Service to you for managing compute nodes? If MS doesn’t  provide head node as a service, someone else will! Process ·        requires creation of a worker node template that specifies a connection to an existing subscription for Windows Azure + an availability policy for the worker nodes. ·        After worker nodes are added to the cluster, you can start them, which provisions the Windows Azure role instances, and then bring them online to run HPC cluster jobs. ·        A Windows Azure worker role instance runs a HPC compatible Azure guest operating system which runs on the VMs that host your service. The guest operating system is updated monthly. You can choose to upgrade the guest OS for your service automatically each time an update is released - All role instances defined by your service will run on the guest operating system version that you specify. see Windows Azure Guest OS Releases and SDK Compatibility Matrix (http://go.microsoft.com/fwlink/?LinkId=190549). ·        use the hpcpack command to upload file packages and install files to run on the worker nodes. see hpcpack (http://go.microsoft.com/fwlink/?LinkID=205514). Requirements ·        assuming you have an azure subscription account and the HPC head node installed and configured. ·        Install HPC Pack 2008 R2 SP 1 -  see Microsoft HPC Pack 2008 R2 Service Pack 1 Release Notes (http://go.microsoft.com/fwlink/?LinkID=202812). ·        Configure the head node to connect to the Internet - connectivity is provided by the connection of the head node to the enterprise network. You may need to configure a proxy client on the head node. Any cluster network topology (1-5) is supported). ·        Configure the firewall - allow outbound TCP traffic on the following ports: 80,       443, 5901, 5902, 7998, 7999 ·        Note: HPC Server  uses Admin Mode (Elevated Privileges) in Windows Azure to give the service administrator of the subscription the necessary privileges to initialize HPC cluster services on the worker nodes. ·        Obtain a Windows Azure subscription certificate - the Windows Azure subscription must be configured with a public subscription (API) certificate -a valid X.509 certificate with a key size of at least 2048 bits. Generate a self-sign certificate & upload a .cer file to the Windows Azure Portal Account page > Manage my API Certificates link. see Using the Windows Azure Service Management API (http://go.microsoft.com/fwlink/?LinkId=205526). ·        import the certificate with an associated private key on the HPC cluster head node - into the trusted root store of the local computer account. Obtain Windows Azure Connection Information for HPC Server ·        required for each worker node template ·        copy from azure portal - Get from: navigation pane > Hosted Services > Storage Accounts & CDN ·        Subscription ID - a 32-char hex string in the form xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx. In Properties pane. ·        Subscription certificate thumbprint - a 40-char hex string (you need to remove spaces). In Management Certificates > Properties pane. ·        Service name - the value of <ServiceName> configured in the public URL of the service (http://<ServiceName>.cloudapp.net). In Hosted Services > Properties pane. ·        Blob Storage account name - the value of <StorageAccountName> configured in the public URL of the account (http://<StorageAccountName>.blob.core.windows.net). In Storage Accounts > Properties pane. Import the Azure Subscription Certificate on the HPC Head Node ·        enable the services for Windows HPC Server  to authenticate properly with the Windows Azure subscription. ·        use the Certificates MMC snap-in to import the certificate to the Trusted Root Certification Authorities store of the local computer account. The certificate must be in PFX format (.pfx or .p12 file) with a private key that is protected by a password. ·        see Certificates (http://go.microsoft.com/fwlink/?LinkId=163918). ·        To open the certificates snapin: Run > mmc. File > Add/Remove Snap-in > certificates > Computer account > Local Computer ·        To import the certificate via wizard - Certificates > Trusted Root Certification Authorities > Certificates > All Tasks > Import ·        After the certificate is imported, it appears in the details pane in the Certificates snap-in. You can open the certificate to check its status. Configure a Proxy Client on the HPC Head Node ·        the following Windows HPC Server services must be able to communicate over the Internet (through the firewall) with the services for Windows Azure: HPCManagement, HPCScheduler, HPCBrokerWorker. ·        Create a Windows Azure Worker Node Template ·        Edit HPC node templates in HPC Node Template Editor. ·        Specify: 1) Windows Azure subscription connection info (unique service name) for adding a set of worker nodes to the cluster + 2)worker node availability policy – rules for deploying / removing worker role instances in Windows Azure o   HPC Cluster Manager > Configuration > Navigation Pane > Node Templates > Actions pane > New à Create Node Template Wizard or Edit à Node Template Editor o   Choose Node Template Type page - Windows Azure worker node template o   Specify Template Name page – template name & description o   Provide Connection Information page – Azure Subscription ID (text) & Subscription certificate (browse) o   Provide Service Information page - Azure service name + blob storage account name (optionally click Retrieve Connection Information to get list of available from azure – possible LRT). o   Configure Azure Availability Policy page - how Windows Azure worker nodes start / stop (online / offline the worker role instance -  add / remove) – manual / automatic o   for automatic - In the Configure Windows Azure Worker Availability Policy dialog -select days and hours for worker nodes to start / stop. ·        To validate the Windows Azure connection information, on the template's Connection Information tab > Validate connection information. ·        You can upload a file package to the storage account that is specified in the template - eg upload application or service files that will run on the worker nodes. see hpcpack (http://go.microsoft.com/fwlink/?LinkID=205514). Add Azure Worker Nodes to the HPC Cluster ·        Use the Add Node Wizard – specify: 1) the worker node template, 2) The number of worker nodes   (within the quota of role instances in the azure subscription), and 3)           The VM size of the worker nodes : ExtraSmall, Small, Medium, Large, or ExtraLarge.  ·        to add worker nodes of different sizes, must run the Add Node Wizard separately for each size. ·        All worker nodes that are added to the cluster by using a specific worker node template define a set of worker nodes that will be deployed and managed together in Windows Azure when you start the nodes. This includes worker nodes that you add later by using the worker node template and, if you choose, worker nodes of different sizes. You cannot start, stop, or delete individual worker nodes. ·        To add Windows Azure worker nodes o   In HPC Cluster Manager: Node Management > Actions pane > Add Node à Add Node Wizard o   Select Deployment Method page - Add Azure Worker nodes o   Specify New Nodes page - select a worker node template, specify the number and size of the worker nodes ·        After you add worker nodes to the cluster, they are in the Not-Deployed state, and they have a health state of Unapproved. Before you can use the worker nodes to run jobs, you must start them and then bring them online. ·        Worker nodes are numbered consecutively in a naming series that begins with the root name AzureCN – this is non-configurable. Deploying Windows Azure Worker Nodes ·        To deploy the role instances in Windows Azure - start the worker nodes added to the HPC cluster and bring the nodes online so that they are available to run cluster jobs. This can be configured in the HPC Azure Worker Node Template – Azure Availability Policy -  to be automatic or manual. ·        The Start, Stop, and Delete actions take place on the set of worker nodes that are configured by a specific worker node template. You cannot perform one of these actions on a single worker node in a set. You also cannot perform a single action on two sets of worker nodes (specified by two different worker node templates). ·        ·          Starting a set of worker nodes deploys a set of worker role instances in Windows Azure, which can take some time to complete, depending on the number of worker nodes and the performance of Windows Azure. ·        To start worker nodes manually and bring them online o   In HPC Node Management > Navigation Pane > Nodes > List / Heat Map view - select one or more worker nodes. o   Actions pane > Start – in the Start Azure Worker Nodes dialog, select a node template. o   the state of the worker nodes changes from Not Deployed to track the provisioning progress – worker node Details Pane > Provisioning Log tab. o   If there were errors during the provisioning of one or more worker nodes, the state of those nodes is set to Unknown and the node health is set to Unapproved. To determine the reason for the failure, review the provisioning logs for the nodes. o   After a worker node starts successfully, the node state changes to Offline. To bring the nodes online, select the nodes that are in the Offline state > Bring Online. ·        Troubleshooting o   check node template. o   use telnet to test connectivity: telnet <ServiceName>.cloudapp.net 7999 o   check node status - Deployment status information appears in the service account information in the Windows Azure Portal - HPC queries this -  see  node status information for any failed nodes in HPC Node Management. ·        When role instances are deployed, file packages that were previously uploaded to the storage account using the hpcpack command are automatically installed. You can also upload file packages to storage after the worker nodes are started, and then manually install them on the worker nodes. see hpcpack (http://go.microsoft.com/fwlink/?LinkID=205514). ·        to remove a set of role instances in Windows Azure - stop the nodes by using HPC Cluster Manager (apply the Stop action). This deletes the role instances from the service and changes the state of the worker nodes in the HPC cluster to Not Deployed. ·        Each time that you start a set of worker nodes, two proxy role instances (size Small) are configured in Windows Azure to facilitate communication between HPC Cluster Manager and the worker nodes. The proxy role instances are not listed in HPC Cluster Manager after the worker nodes are added. However, the instances appear in the Windows Azure Portal. The proxy role instances incur charges in Windows Azure along with the worker node instances, and they count toward the quota of role instances in the subscription.

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  • Microsoft Windows HPC Server R2 Beta2

    - by Daniel Moth
    Internally and unofficially we refer to this as "HPC Server v3" and its Beta2 became available last week. Read the full story on this blog post from Ryan and this one from Don. There has been a lot of excitement on the web for this release with coverage from last Wednesday here, here, here, here, here and here. Don't forget that Visual Studio 2010 makes it easy to develop for HPC Server including the MPI Cluster Debugger integration that I explained here and here. Comments about this post welcome at the original blog.

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  • Windows Azure Use Case: High-Performance Computing (HPC)

    - by BuckWoody
    This is one in a series of posts on when and where to use a distributed architecture design in your organization's computing needs. You can find the main post here: http://blogs.msdn.com/b/buckwoody/archive/2011/01/18/windows-azure-and-sql-azure-use-cases.aspx  Description: High-Performance Computing (also called Technical Computing) at its most simplistic is a layout of computer workloads where a “head node” accepts work requests, and parses them out to “worker nodes'”. This is useful in cases such as scientific simulations, drug research, MatLab work and where other large compute loads are required. It’s not the immediate-result type computing many are used to; instead, a “job” or group of work requests is sent to a cluster of computers and the worker nodes work on individual parts of the calculations and return the work to the scheduler or head node for the requestor in a batch-request fashion. This is typical to the way that many mainframe computing use-cases work. You can use commodity-based computers to create an HPC Cluster, such as the Linux application called Beowulf, and Microsoft has a server product for HPC using standard computers, called the Windows Compute Cluster that you can read more about here. The issue with HPC (from any vendor) that some organization have is the amount of compute nodes they need. Having too many results in excess infrastructure, including computers, buildings, storage, heat and so on. Having too few means that the work is slower, and takes longer to return a result to the calling application. Unless there is a consistent level of work requested, predicting the number of nodes is problematic. Implementation: Recently, Microsoft announced an internal partnership between the HPC group (Now called the Technical Computing Group) and Windows Azure. You now have two options for implementing an HPC environment using Windows. You can extend the current infrastructure you have for HPC by adding in Compute Nodes in Windows Azure, using a “Broker Node”.  You can then purchase time for adding machines, and then stop paying for them when the work is completed. This is a common pattern in groups that have a constant need for HPC, but need to “burst” that load count under certain conditions. The second option is to install only a Head Node and a Broker Node onsite, and host all Compute Nodes in Windows Azure. This is often the pattern for organizations that need HPC on a scheduled and periodic basis, such as financial analysis or actuarial table calculations. References: Blog entry on Hybrid HPC with Windows Azure: http://blogs.msdn.com/b/ignitionshowcase/archive/2010/12/13/high-performance-computing-on-premise-and-in-the-windows-azure-cloud.aspx  Links for further research on HPC, includes Windows Azure information: http://blogs.msdn.com/b/ncdevguy/archive/2011/02/16/handy-links-for-hpc-and-azure.aspx 

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  • Windows HPC Server 08 suitability for Matlabs

    - by blade
    I want to setup another Hyper-V VM for installing Matlabs/doing some compute-intensive programming using C. I keep thinking that Windows Server HPC 2008 is designed for this sort of work. Would I be on the right track to setup a single VM with this OS and install this software? Or is HPC more for grid/distributed computing? Thanks

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  • using i7 "gamer" cpu in a HPC cluster

    - by user1219721
    I'm running WRF weather model. That's a ram intensive, highly parallel application. I need to build a HPC cluster for that. I use 10GB infiniband interconnect. WRF doesn't depends of core count, but on memory bandwidth. That's why a core i7 3820 or 3930K performs better than high-grade xeons E5-2600 or E7 Seems like universities uses xeon E5-2670 for WRF. It costs about $1500. Spec2006 fp_rates WRF bench shows $580 i7 3930K performs the same with 1600MHz RAM. What's interesting is that i7 can handle up to 2400MHz ram, doing a great performance increase for WRF. Then it really outperforms the xeon. Power comsumption is a bit higher, but still less than 20€ a year. Even including additional part I'll need (PSU, infiniband, case), the i7 way is still 700 €/cpu cheaper than Xeon. So, is it ok to use "gamer" hardware in a HPC cluster ? or should I do it pro with xeon ? (This is not a critical application. I can handle downtime. I think I don't need ECC?)

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  • Is this a HPC or HA mySQL cluster?

    - by Louise Hoffman
    Can someone tell me if this is a High Performance Compute or High Available mySQL cluster? There is a picture of the setup. This is part of the config.ini they talk about [ndbd default] NoOfReplicas=2 # Number of replicas Is it correct understood that NoOfReplicas determines if I have a HPC or a HA cluster?

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  • low performance on HPC cluster (sge) when running multiple jobs

    - by Yotam
    O know this is a long-shot but I'm clueless here. I'm running several computer simulations on High Performance Computation cluster (HPC) of oracale grid engine (sge). A single job runs at a certain speed (roughly 80 steps per second) when I add jobs to the machine, at a certain treshhold, the speed is recuded by two. On one machine (I don't know the cpu kind) the treshold is 11 jobs for 16 cpu's. On another one with the same number and kind of cpu's , the treshold is 8. I thought at first that this is a memory issue but each job takes about 60MB - 100MB and I have 16GB of ram on each of those machine. Did any of you encountered such a problem? is there any way to analyz this? Thanks.

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  • How are you keeping abreast with latest HPC trends?

    - by Fanatic23
    For those of you primarily working on high performance computing for non-scientific purposes (as in no fortran) what are the ways by which you keep yourself abreast of the latest trends out there? Industry gossip? Random blogs from google? Search SO? I am into HPC recently and looking for the high level architectural landscape. Given that everyone from GPGPU coders to FPGA folks to Erlang developers claim they are into HPC, how are you keeping up with so much information?

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  • WEB based HPC cluster node management

    - by Skuja
    Hello, i am working on my school diploma thesis. The main goal is to create web based application where logged users could see free and busy nodes, turn them on and off, see what process they are running etc. Figured out that i could do something like this - write some cron daemon that would run every 30seconds or so, and it could run ping utility for each node to find out if it is on or off, then write results to some file. Then from my web app (i will write in PHP) i could read the info. Will it be a good solution? How would you suggest me to do it? And finally, is there any existing solutions (it may not be a definetly ewb based) for managment of cluster nodes?

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  • HPC Cluster planning workflow?

    - by Veronica
    After three days of intensive Google searching, I have not found any high-level workflow of how to build a low profile - cheap - computing cluster (we are not interested in HA yet). This is just a front-end plus a node for now. We want to start small with rockscluster, provide a web-based server for offering services, and then add nodes as our budget increases. We're small company, so we haven't enough human resources to implement it smoothly. Here are some facts about our environment: Our hardware is not constant (we will add nodes). Our workload will vary (in the order from 200Mb - 1Tb) Our software will change (scientific applications for data mining) Do you know any visual workflow, worksheet, chart, describing the general necessary steps to begin our cluster planning?

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  • HPC Server Dynamic Job Scheduling: when jobs spawn jobs

    - by JoshReuben
    HPC Job Types HPC has 3 types of jobs http://technet.microsoft.com/en-us/library/cc972750(v=ws.10).aspx · Task Flow – vanilla sequence · Parametric Sweep – concurrently run multiple instances of the same program, each with a different work unit input · MPI – message passing between master & slave tasks But when you try go outside the box – job tasks that spawn jobs, blocking the parent task – you run the risk of resource starvation, deadlocks, and recursive, non-converging or exponential blow-up. The solution to this is to write some performance monitoring and job scheduling code. You can do this in 2 ways: manually control scheduling - allocate/ de-allocate resources, change job priorities, pause & resume tasks , restrict long running tasks to specific compute clusters Semi-automatically - set threshold params for scheduling. How – Control Job Scheduling In order to manage the tasks and resources that are associated with a job, you will need to access the ISchedulerJob interface - http://msdn.microsoft.com/en-us/library/microsoft.hpc.scheduler.ischedulerjob_members(v=vs.85).aspx This really allows you to control how a job is run – you can access & tweak the following features: max / min resource values whether job resources can grow / shrink, and whether jobs can be pre-empted, whether the job is exclusive per node the creator process id & the job pool timestamp of job creation & completion job priority, hold time & run time limit Re-queue count Job progress Max/ min Number of cores, nodes, sockets, RAM Dynamic task list – can add / cancel jobs on the fly Job counters When – poll perf counters Tweaking the job scheduler should be done on the basis of resource utilization according to PerfMon counters – HPC exposes 2 Perf objects: Compute Clusters, Compute Nodes http://technet.microsoft.com/en-us/library/cc720058(v=ws.10).aspx You can monitor running jobs according to dynamic thresholds – use your own discretion: Percentage processor time Number of running jobs Number of running tasks Total number of processors Number of processors in use Number of processors idle Number of serial tasks Number of parallel tasks Design Your algorithms correctly Finally , don’t assume you have unlimited compute resources in your cluster – design your algorithms with the following factors in mind: · Branching factor - http://en.wikipedia.org/wiki/Branching_factor - dynamically optimize the number of children per node · cutoffs to prevent explosions - http://en.wikipedia.org/wiki/Limit_of_a_sequence - not all functions converge after n attempts. You also need a threshold of good enough, diminishing returns · heuristic shortcuts - http://en.wikipedia.org/wiki/Heuristic - sometimes an exhaustive search is impractical and short cuts are suitable · Pruning http://en.wikipedia.org/wiki/Pruning_(algorithm) – remove / de-prioritize unnecessary tree branches · avoid local minima / maxima - http://en.wikipedia.org/wiki/Local_minima - sometimes an algorithm cant converge because it gets stuck in a local saddle – try simulated annealing, hill climbing or genetic algorithms to get out of these ruts   watch out for rounding errors – http://en.wikipedia.org/wiki/Round-off_error - multiple iterations can in parallel can quickly amplify & blow up your algo ! Use an epsilon, avoid floating point errors,  truncations, approximations Happy Coding !

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  • HPC (mainly on Java)

    - by Insectatorious
    I'm looking for some way of using the number-crunching ability of a GPU (with Java perhaps?) in addition to using the multiple cores that the target machine has. I will be working on implementing (at present) the A* Algorithm but in the future I hope to replace it with a Genetic Algorithm of sorts. I've looked at Project Fortress but as I'm building my GUI in JavaFX, I'd prefer not to stray too far from a JVM. Of course, should no feasible solution be available, I will migrate to the easiest solution to implement.

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  • c++ programming for clusters and HPC

    - by Abruzzo Forte e Gentile
    HI All I need to write a scientific application in C++ doing a lot of computations and using a lot of memory. I have part of the job but due to high requirements in terms of resources I was thinking to start moving to OpenMPI. Before doing that I have a simple curiosity: If I understood the principle of OpenMPI is the developer that has the task of splitting the jobs over different nodes calling SEND and RECEIVE based on node available at that time. Do you know if it does exist some library or OS or whatever that has this capability letting my code reamain as it is now? Basically something that connects all computers and let share as one their memory and CPU? I am a bit confused because of the high material available on the topic. Should I look at cloud computing? or Distributed Shared Memory? Can you help me or address me a bit? Thanks

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  • Microsoft Windows HPC Server R2 Beta2

    Internally and unofficially we refer to this as "HPC Server v3" and its Beta2 became available last week. Read the full story on this blog post from Ryan and this one from Don. There has been a lot of excitement on the web for this release with coverage from last Wednesday here, here, here, here, here and here. Don't forget that Visual Studio 2010 makes it easy to develop for HPC Server including the MPI Cluster Debugger integration that I explained here and here. Comments about this...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • Windows Azure HPC Scheduler Architecture

    - by Churianov Roman
    So far I've found very little information on the scheduling policy, resource management policy of Azure HPC Scheduler. I would appreciate any kind of information regarding some of these questions: What scheduling policy does a Head Node use to scatter jobs to Compute Nodes? Does Azure Scheduler use prior information about the jobs (compute time, memory demands ...) ? If 'yes', how it gets this information? Does Azure Scheduler split a job into several parallel jobs on one Compute node? Does it have any protection from Compute Node failures? (what it does when a compute node stops responding) Does it support addition/subtraction of Compute nodes? Is it possible to cancel a job? P.S. I'm aware of the MSDN resource Windows Azure HPC Scheduler. I found only information of how to use this Scheduler but almost nothing about how it works inside.

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  • MPI Project Template for VS2010

    If you are developing MS MPI applications with Visual Studio 2010, you are probably tired of following some tedious steps for every new C++ project that you create, similar to the following:1. In Solution Explorer, right-click YourProjectName, then click Properties to open the Property Pages dialog box.2. Expand Configuration Properties and then under VC++ Directories place the cursor at the beginning of the list that appears in the Include Directories text box and then specify the location of the MS MPI C header files, followed by a semicolon, e.g.C:\Program Files\Microsoft HPC Pack 2008 SDK\Include;3. Still under Configuration Properties and under VC++ Directories place the cursor at the beginning of the list that appears in the Library Directories text box and then specify the location of the Microsoft HPC Pack 2008 SDK library file, followed by a semicolon, e.g.if you want to build/debug 32bit application:C:\Program Files\Microsoft HPC Pack 2008 SDK\Lib\i386;if you want to build/debug 64bit application:C:\Program Files\Microsoft HPC Pack 2008 SDK\Lib\amd64;4. Under Configuration Properties and then under Linker, select Input and place the cursor at the beginning of the list that appears in the Additional Dependencies text box and then type the name of the MS MPI library, i.e.msmpi.lib;5. In the code file#include "mpi.h"6. To debug the MPI project you have just setup, under Configuration Properties select Debugging and then switch the Debugger to launch combo value from Local Windows Debugger to MPI Cluster Debugger.Wouldn't it be great if at C++ project creation time you could choose an MPI Project Template that included the steps/configurations above? If you answered "yes", I have good news for you courtesy of a developer on our team (Qing). Feel free to download from Visual Studio gallery the MPI Project Template. Comments about this post welcome at the original blog.

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  • Message Passing Interface (MPI)

    So you have installed your cluster and you are done with introductory material on Windows HPC. Now you want to develop an application with the most common programming model: Message Passing Interface.The MPI programming model is a standard with implementations from many vendors. For newbies (like myself!), I have aggregated below links for getting started.Non-Microsoft MPI resources (useful even if you are not on the Windows platform)1. Message Passing Interface on wikipedia. 2. The MPI standard.3. MPICH2 - an MPI implementation.4. Tutorial on MPI by William Gropp.5. MPI patterns presented as a tutorial with sample code. 6. THE official MPI Forum (maintains the standard) including the wiki discussing the MPI future.7. Great MPI tutorial including at the end the MPI Exercise.8. C++ MPI Exercises by John Burkardt.9. Book online: MPI The Complete Reference.MS-MPI10. Windows HPC Server 2008 - Using MS-MPI whitepaper (15 page doc).11. Tracing MPI applications (27 page doc).12. Using Microsoft MPI (TechNet section).13. Windows HPC Server MPI forum (for posting questions). MPI.NET14. MPI.NET Home Page (not owned by Microsoft).15. MPI.NET Tutorial.16. HPC Development using F# using MPI.NET (38 page doc).Next time I'll post resources for the Microsoft Cluster SOA programming model - happy coding... Comments about this post welcome at the original blog.

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  • Penguin's HPC Waddle

    Server Snapshot: Penguin Computing has always, as its name implies, focused on developing best practices for Linux-based systems, software and services, particularly in the HPC space.

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  • Penguin's HPC Waddle

    Server Snapshot: Penguin Computing has always, as its name implies, focused on developing best practices for Linux-based systems, software and services, particularly in the HPC space.

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  • Dryad and DryadLINQ from MSR

    - by Daniel Moth
    Microsoft Research (MSR) researches technologies, incubates projects which many times result in technology that looks like a ready-to-use product (but it is important to understand that these are not the same as products built by the various… actual product teams here at Microsoft). A very popular MSR project has been DryadLINQ, which itself builds on Dryad. To learn more follow the project pages I just linked to and I also recommend this 1-hour channel 9 video. If you only have 3 minutes, watch this great elevator pitch instead. You can also stay tuned on the official blog, which includes a post that refers to internal adoption e.g by Bing, a quick DryadLINQ code example, and some history on how DryadLINQ generalizes the MapReduce pattern and makes it accessible to regular programmers (see this post and that post). Essentially, the DryadLINQ framework (building on the Dryad runtime) allows developers to re-use their LINQ skills for creating/generating programs that process large multi-gigabyte/terabyte datasets across 100s-1000s of machines. One way to think about it is that just as Parallel LINQ allows LINQ developers to seamlessly use multiple cores from a single process on a single machine, DryadLINQ allows LINQ developers to seamlessly use multiple machines for their data parallel algorithms. In the former scenario the motivation was speed of execution, in the latter it is speed of execution AND processing large datasets that simply don't fit on a single machine. Whenever I hear about execution of parallel code on multiple machines on the Microsoft platform, I immediately think of Windows HPC Server. Indeed Dryad and DryadLINQ were made available for Windows HPC Server and I encourage you to watch the PDC session on this topic: Data-Intensive Computing on Windows HPC Server with the DryadLINQ Framework. Watch this space… Comments about this post welcome at the original blog.

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  • A Real-Time HPC Approach for Optimizing Multicore Architectures

    Complex math is at the heart of many of the biggest technical challenges. With multicore processors, the type of calculations that would have required a supercomputer can now be performed in real-time, embedded environments. High-performance computing - Supercomputer - Real-time computing - Operating system - Companies

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  • Check which nodes of Beowulf HPC cluster system are free from PHP app?

    - by Skuja
    I am working on my diploma thesis project. I have access to 32Node Dell poweredge HPC cluster system with Linux(Debian i think) installed on it. My first goal is to create web (PHP) app where logged users could see free and busy nodes, turn them on and off. I am planning to do something like this - write some cron daemon that would run every 30seconds or other interval, and it could run ping utility for each node to find out if it is on or off, then write results to some file. Then from my web app i could read the info. Will it be a good solution? What existing for node management solutions are there?

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