1. 1 Integrated Workload Management for Beowulf Clusters Bill DeSalvo – April 14, 2004 wdesalvo@platform.com

2. © Platform Computing Inc. 2003 2 What We’ll Cover Platform LSF Family of Products What is Platform LSF HPC Key Features & Benefits How it Works Q&A

3. © Platform Computing Inc. 2003 3 What is the Platform LSF Family of Products?

4. © Platform Computing Inc. 2003 4 What Problems Are We Solving? Solve large, grand challenge, complex problems by optimizing the placement of workload in High Performance Computing environments

5. © Platform Computing Inc. 2003 5 Platform LSF HPC Intelligent, policy-driven high performance computing (HPC) workload processing Parallel & sequential batch workload management for High Performance Computing (HPC) Includes patent-pending topology-based scheduling Intelligently schedules parallel batch jobs Virtualizes resources Prioritizes service levels based on policies Based on Platform LSF: Standards-based, OGSI-compliant, grid-enabled solution Commercial production quality product

6. © Platform Computing Inc. 2003 6 Platform Customers

7. © Platform Computing Inc. 2003 7 Platform Customers

8. © Platform Computing Inc. 2003 8 Platform Customers

9. © Platform Computing Inc. 2003 9 Platform LSF HPC Platform LSF HPC AlphaServer SC Platform LSF HPC for IBM Platform LSF HPC for Linux Platform LSF HPC for SGI Platform LSF HPC for Cray

10. © Platform Computing Inc. 2003 10 Extensive Hardware Support HP HP AlphaServer SC HP XC HP Superdome HP-UX 11i SGI SGI IRIX SGI TRIX SGI Altix, SGI Propack IBM IBM RS/6000 AIX IBM SP2/SP3 Linux IA-64 systens with RedHat Intel, AMD 32-bit systems with LINUX kernel Sun SUN Solaris High Performance Interconnects Myrinet with GM Quadrics QsNet SGI Numa Flex SGI NumaLink IBM SP Switch

11. © Platform Computing Inc. 2003 11 Platform LSF HPC – Linux Support HP HP XC Systems running Unlimited Linux HP Itanium 2 systems running LINUX 2.4.x kernel, glibc 2.2 with RMS on Quadrics QsNet/Elan3 HP Alpha/AXP systems running LINUX 2.4.x kernel, glibc 2.2.x with RMS on Quadrics QsNet/Elan3 Linux IA-64 systems, Kernel 2.4.x, compiled with glibc 2.2.x, tested on RedHat 7.3 x86 systems: Kernel 2.2.x, compiled with glibc 2.1.x, tested on Debian 2.2, OpenLinux 2.4, RedHat 6.2 and 7.0, SuSE 6.4 and 7.0, TurboLinux 6.1 Kernel 2.4.x, compiled with glibc 2.1.x, tested on RedHat 7.x and 8.0, and SuSE 7.0, and RedHat Linux Advanced Server 2.1 Clustermatic Linux 3.0 Kernel 2.4.x, compiled with glibc 2.2.x, tested on RedHat 8.0 Scyld Linux, Kernel 2.4.x, compiled with glibc 2.2.x. SGI SGI Altix systems running Linux Kernel 2.4.x compiled with glibc 2.2.x and SGI Propack 2.2 and higher

12. Key Features and Benefits Platform LSF HPC

13. © Platform Computing Inc. 2003 13 Key Features Optimized Application, System and Hardware Performance Enhanced Accounting, Auditing & Control Commercial Grade System Scalability & Reliability Extensive Hardware Support Comprehensive, Extensible and Standards-based Security

14. © Platform Computing Inc. 2003 14 Key Features – Platform LSF HPC Optimized Application, System and Hardware Performance Enhanced Accounting, Auditing & Control Commercial Grade System Scalability & Reliability Comprehensive, Extensible and Standards-based Security

15. © Platform Computing Inc. 2003 15 Adaptive Interconnect Performance Optimization Scheduling that takes advantage of unique interconnect properties IBM SP Switch at the POE software level RMS on AlphaServer SC (Quadrics) SGI topology hardware graph Out-of-the-box functionality without any customization required

16. © Platform Computing Inc. 2003 16 Generic Parallel Job Launcher Generic support for all different types of Parallel Job Launchers LAMMPI, MPICH-GM, MPICH-P4, POE, SCALI, CHAMPION PRO, etc Customizable for any vendor or publicly available parallel solution Control - ensuring no jobs can escape the workload management system

17. © Platform Computing Inc. 2003 17 Integrated out-of-the-box Parallel Launcher Support Full integration with IRIX MPI and array session daemon Full integration with SGI MPI for Linux Full integration with Sun HPC Clustertools providing full MPI control, accounting and integration with SUNs PRISM debugger Vendor MPI libraries provide better performance than open source libraries Vendor MPI library full support Vendor integration supported by Platform Seamless control and accounting

18. © Platform Computing Inc. 2003 18 HPC Workload Scheduling Dynamic load balancing supporting heterogeneous workloads IBM SP switch aware scheduling Scheduling of parallel jobs Number of CPUs, min/max, node span Backfill on processor & memory Processor & memory reservation Topology aware scheduling Exclusive scheduling Advance Reservation Fairshare, Preemption Accounting

19. © Platform Computing Inc. 2003 19 High Performing, Open, Scalable Architecture Scalable scheduler architecture Modularized, support for over 500,000 active jobs per cluster More than 2,000 multi-processor host per cluster - with multiple processors in each host Process 5x more work & achieve 100% utilization Scale with business growth External executable support Collect information from multiple external resources to track site specific local and global resources Extends out-of-the-box capabilities to manage additional resources and customer application execution Differentiation Multiple vs single external resource collector Job Groups Organize jobs into higher level work units - hierarchical tree Easy to manage and control work to increase user productivity by reducing complexity OGSI compliance Future-proof & protect grid investment using standards-based solutions, interoperate with third-party systems

20. © Platform Computing Inc. 2003 20 Intelligent Scheduling Policies Fairshare (User & Project-based) Ensure job resources are used for the right work Guarantees resource allocation among users and projects are met Co-ordinate access to the right number of resources for different users and projects according to pre-defined shares Differentiation Hierarchal & guaranteed Policy-based Preemption Maximizes throughput of high priority critical work based on priority and load conditions Prevents starvation of lower priority work Differentiation Platform LSF supports multiple preemption policies Goal-oriented SLA driven policies Based on customer SLA driven goals: Deadline, Velocity, Throughput Guarantees projects are completed on time Reduces projects and administration costs Provides visibility into the progress of projects Allows the admin focus on “What work and When” needs to be done, not “how” the resources are to be allocated Intelligent Scheduler Fairshare Preemption Resource Reservation Advance Reservation SLA Scheduling Service Level Agreement MultiCluster Other Scheduling Modules Plugin Schedulers License Scheduling

21. © Platform Computing Inc. 2003 21 Advanced Self-Management Flexible, Comprehensive Resource Definitions Resources defined on a node basis across an entire cluster or subset of the nodes in a cluster Auto-detectable or user defined resources Adaptive membership – nodes join and leave Platform LSF clusters dynamically and automatically without administration effort Dynamic or static resources Job Level Exception Management Exception-based error detection to take automatic, configurable, corrective actions Increased job reliability & predictability Improved visibility on job and system errors & reduced administration overhead and costs Automatic Job Migration and Requeue Automatically migrate and requeue jobs based on policies in the event of host or network failures Reduce user and administrator overhead in managing failures & reduce risk of running critical workloads Master Scheduler Failover Automatically fail over to another host if the master host is unavailable Continuous scheduling service and execution of jobs & eliminate manual intervention

22. © Platform Computing Inc. 2003 22 Backfill Policy configured at the queue level and applies to all jobs in a queue Smaller sequential jobs are ‘backfilled’ behind larger parallel jobs Improves hardware utilization Users provided with an accurate time when their job will start

23. Key New Feature & Benefits Platform LSF V6.0

24. © Platform Computing Inc. 2003 24 Feature Overview OGSI Compliance Goal-Oriented SLA-Driven Scheduling License-Aware Scheduling Job-Level Exception Management (Self Management Enhancement) Job Group Support Other Scheduling Enhancements Queue-Based Fairshare User Fairshare by Queue Priority Job Starvation Prevention plug-in

25. © Platform Computing Inc. 2003 25 Feature Overview (Cont.) HPC Enhancements Dynamic ptile Enforcement Resource Requirement Specification for Advance Reservation Thread Limit Enforcement General Parallel Support Parallel Job Size Scheduling Job Limit Enhancements Non-normalized Job Run Limit Resource Allocation Limit Display Administration and Diagnostics Scheduler Dynamic Debug Administrator Action Messages

26. © Platform Computing Inc. 2003 26 Goal-Oriented SLA-Driven Scheduling What is it? A new scheduling policy. Unlike current scheduling policies based on configured shares or limits, SLA-driven scheduling is based on customer provided goals: Deadline based goal: Specify the deadline for a group of jobs. Velocity based goal: Specify the number of jobs running at any one time. Throughput based goal: Specify the number of finished jobs per hour. This scheduling policy works on top of queues and host partitions. Benefits Guarantees projects are completed on time according to explicit SLA definitions. Provides visibility into the progress of projects to see how well projects are tracking to SLAs Allows the admin focus on “What work and When” needs to be done, not “how” the resources are to be allocated. Guarantees service level deliveries to the user community, reduces the risks of projects and administration cost.

27. © Platform Computing Inc. 2003 27 User case Problem: we need to finish all simulation jobs before 15:00pm. Solution: Configure a deadline service class in lsb.serviceclasses file. Begin ServiceClass NAME=simulation PRIORITY=100 GOALS = [deadline timeWindow (13:00 – 15:00)] DESCRIPTION = A simple deadline demo End ServiceClass Submitting and monitoring jobs $bsub –sla simulation –W 10 –J A[1-50] mySimulation $date;bsla Wed Aug 20 14:00:16 EDT 2003 SERVICE_CLASS_NAME: simulation GOAL: DEADLINE ACTIVE_WINDOW: (13:00 – 15:00) STATUS: Active:Ontime DEAD_LINE: (Wed Aug 20 15:00) ESTIMATED_FINISH_TIME: (Wed Aug 20 14:30) Optimum Number of Running Jobs: 5 NJOBS PEND RUN SSUSP USUSP FINISH 50 25 5 20

28. © Platform Computing Inc. 2003 28 Job-Level Exception Management (Self Management Enhancement) What is it? Platform LSF can monitor the exception behavior and take action accordingly. Benefits Increased reliability of job execution Improved visibility on job and system errors Reduced administration overhead and costs How it works Platform LSF V6 handles following exceptions: “Job eating” machine (or “black-hole” machine): for some reason, jobs keep exiting abnormally on a machine (e.g. no processes, mount daemon dies, etc.) Job underrun (job run time less than configured minimum time) Job overrun (job run time more than configured maximum time) Job run idle (job run without cpu usage increasing).

29. © Platform Computing Inc. 2003 29 Job-Level Exception Management (Self Management Enhancement) (Cont.) Use Case 1: Requirement: If the host has more than 30 jobs exited in past 5 minutes, I want LSF to close that machine, then notify me and tell me the machine name. Solution: Configure host exceptions (EXIT_RATE in lsb.hosts). Begin Host HOST_NAME MXJ EXIT_RATE # Keywords Default ! 6 End Host Configure the JOB_EXIT_RATE_DURATION = 5 in lsb.params (default value is 10 minutes)

30. © Platform Computing Inc. 2003 30 Job-Level Exception Management (Self Management Enhancement) (Cont.) Use Case 2: Requirement: If any job runs more than 3 hours, I want LSF to notify me and tell me the jobID. Solution: Configure job exceptions (lsb.queues) Begin Queue … JOB_OVERRUN = 3*60 # run time in minutes End Queue

31. © Platform Computing Inc. 2003 31 Job Starvation Prevention Plug-in What is it? External scheduler plug-in allows users to define their own equation for job priority Benefits Low priority work is guaranteed to run after ‘waiting’ for a specified time ensuring that the job does not wait forever (i.e. starvation). How it works By default, the scheduler provides the following calculation Job priority =A * (q_priority) *MIN(1, int(wait_time/T0)) * (B*requested_processors+MAX(C*wait_time*(1+1/run_time),D) +E*requested_memory) Where A, B, C, D, E are coefficients. T0 is the grace period. Default run_time= INFINIT Admin can define different coefficients for each queue with the following format: MANDATORY_EXTSCHED=JOBWEIGHT[A=val1; B=val2; …]

32. © Platform Computing Inc. 2003 32 Job Starvation Prevention Plug-in Use Case: Requirement: Lowest priority queue can wait no more than 10 hours. Solution: If highest priority queue PRIORITY = 100, lowest priority queue PRIORITY = 20. Configure the following in Lowest queue: MANDATORY_EXTSCHED=JOBWEIGHT[A=1;B=0;C=10;D=1;E=0;T0= 0.1] After waiting 10 hours, the job in Lowest queue will have higher priority than jobs in highest priority queue. Note: The formula for calculating job weight is open source and customers can customize it.

33. © Platform Computing Inc. 2003 33 Resource Requirement Specification For Advance Reservation What is it? Enable users to select the hosts for advance reservation based on the resource requirement. Benefit More flexible to reserve the host slots for the mission critical job. How it works brsvadd command supports select string: brsvadd –R “select[type==LINUX]” –n 4 –u xwei –b 10:00 –e 12:00

34. © Platform Computing Inc. 2003 34 Key Features – Platform LSF HPC Enhanced Accounting, Auditing & Control Optimized Application, System and Hardware Performance Commercial Grade System Scalability & Reliability Comprehensive, Extensible and Standards-based Security

35. © Platform Computing Inc. 2003 35 Job Termination Reasons Accounting log with detailed audit & error information for every job in the system Indicates why a job was terminated Difference between an abnormal termination or caused by Platform LSF HPC

36. © Platform Computing Inc. 2003 36 Key Features – Platform LSF HPC Optimized Application, System and Hardware Performance Enhanced Accounting, Auditing & Control Comprehensive, Extensible and Standards-based Security Commercial Grade System Scalability & Reliability

37. © Platform Computing Inc. 2003 37 Enterprise Proven Running on several of the top 10 supercomputers in the world on the “TOP500” (#2,4,5,6) More than 250,000 licenses in use spanning 1,500 customer sites Scales to over 100 clusters, 200,000 CPUs and 500,000 active jobs per cluster 11+ years experience in distributed & grid computing Risk free investment – proven solution Commercial production quality

38. © Platform Computing Inc. 2003 38 Key Features – Platform LSF HPC Optimized Application, System and Hardware Performance Enhanced Accounting, Auditing & Control Commercial Grade System Scalability & Reliability Comprehensive, Extensible and Standards-based Security

39. © Platform Computing Inc. 2003 39 Comprehensive, Extensible, Standards-based Security Scalable scheduler architecture Multiple scheduler plug-in API support External executable support Web GUI Open source components Risk free investment – proven solution Commercial grade Scalability and flexibility as a business grows

40. How It Works Platform LSF HPC

41. © Platform Computing Inc. 2003 41 Fault Tolerance via Master Election slave LIM sbd Host i slave LIM sbd Host N Master LIM sbd Host 1 mbd Am I master ? master announcement exchange load info mbsched

42. © Platform Computing Inc. 2003 42 Virtual Server Technology LIM: Collects & centralizes status of all resources in cluster RES: Transparent remote task execution ELIM Master LIM Load Information Free memory Idle Time Disk I/O Rate Free swap space Number of CPUs Host Status Custom Status RES Cluster APIs RES Slave LIM Slave LIM Slave LIM Slave LIM RES System Monitor Workload Management Admin Tools

43. © Platform Computing Inc. 2003 43 Executing Work SBD Master LIM Slave LIM Slave LIM MBD ELIM Chooses best, available resource to process the job Gaussian Distribution Job Computational Chemistry Job Protein Modeling Job BLAST Sequence Job Jobs Clients Slave LIM Slave LIM SBD

44. © Platform Computing Inc. 2003 44 Grid-enabled, Scalable Architecture Open, modular plug-in schedulers scale with the growth of your business

45. © Platform Computing Inc. 2003 45 How it Works - Platform LSF HPC Host Workload Manager 6 Accounting, auditing and control information 2 Task Execution Host 1 PAM Task Execution Host 2 Interconnect Manager 5 Cluster Information Manager 3 4 Intelligence Scheduler Topology Backfill MAUI Serial/Parallel Control Job Starvation Fairshare Preemption Advance Reservation Other Scheduler Modules Master Host Cluster Workload Manager Cluster Workload Manager 1 Web Application Job Submission API

46. © Platform Computing Inc. 2003 46 Scheduler Framework The framework hides the complexity of interacting with core services. Resource Broker responsible for resource information collection from other core services. Minimize the inter-dependencies between scheduling policies Maximize extensibility through the plug-in scheduler module stack Scheduler Framework Scheduler Modules Resource Broker

47. © Platform Computing Inc. 2003 47 The Four Scheduling Phases 1. Pre-Processing 2. Matching / Limits 3. Order / Allocation 4. Post-Processing Pre-Selected Jobs Scheduling Decisions/ Job Control Decisions Scheduling Decisions/ Job Control Decisions Localized setup Prioritize jobs and allocate resources Match eligible resources to nodes Allocation adjustments

48. © Platform Computing Inc. 2003 48 Multiple Scheduling Modules Pre- Processing Matching / Limits Order / Allocation Post- Processing Internal Module Pre- Processing Matching / Limits Order / Allocation Post- Processing... Add-on Module 1 Pre- Processing Matching / Limits Order / Allocation Post- Processing Add-on Module N Vendor specific matching policies (without changing the existing scheduler Support for external scheduler

49. © Platform Computing Inc. 2003 49 Maui Integration MBD SCH_FM RMGetInfo Post-Processing Pre-processing Order jobs UIProcessClients QueueScheduleSJobs QueueScheduleRJobs QueueScheduleIJobs QueueBackFill Job, Host, Res Info Decisions and ack Sync MAUI Plugin Event Handle (wait until GO event) MAUI Scheduler

50. Linux-specific Solutions

51. © Platform Computing Inc. 2003 51 Controlling an MPI job On a distributed system (Linux cluster) there are many problems to address: 1. Job launch across multiple nodes 2. Gather resource usage while job executes 3. Propagate signals 4. Job “clean-up” to eliminate “dangling” MPI processes 5. Comprehensive job accounting

52. © Platform Computing Inc. 2003 52 Resource manager Resource manager submit mpirun a.out Jobscript “traditional” MPI sequence Job launcher Job launcher

53. © Platform Computing Inc. 2003 53 Platform LSF HPC for Linux - MPICH-GM mbatchd sbatchd Job script mpirun TS res gmmpirun_wrapper a.out TS res PIM bsub a.out pam res PIM

54. © Platform Computing Inc. 2003 54 Execution Host H1 PIMLIM master LIM Master Host lsblib LIMPIM bsub SBD MBDSBD SBD child pam high med hpc_queue Queues MBSCHD Submission host H2 PJL TaskStarter a.out: process 1 TaskStarter a.out: process 2 PJL wrapperRoot res LIM Signals and rusage collection Hostname & pid Platform LSF HPC for Linux/Myrinet - Generic PJL

55. © Platform Computing Inc. 2003 55 Execution Host H1 PIMLIM master LIM Master Host lsblib LIMPIM bsub SBD MBDSBD SBD child pam high med hpc_queue Queues MBSCHD Submission host H2 esub elim Mpirun.ch_g m TaskStarter a.out: process 1 TaskStarter a.out: process 2 Gmmpirun_w rapper Root res LIM elim Set LSF_PJL_TYPE To mpich_gm Report resource availability Signals and rusage collection Report resource availability Hostname & pid rsh Platform LSF HPC for Linux/Myrinet - MPICH_GM Mpirun.lsf

56. © Platform Computing Inc. 2003 56 Platform LSF HPC for Linux/Myrinet - LAM/MPI Execution Host H1 PIMLIM master LIM Master Host lsblib LIMPIM bsub SBD MBDSBD SBD child pam high med hpc_linux Queues MBSCHD Submission host H2 esub elim mpirun TaskStarter a.out: process 1 TaskStarter a.out: process 2 Lammpirun_ wrapper Root res LIM elim Set LSF_PJL_TYPE To lammpi Report resource availability Signals and rusage collection Report resource availability Hostname & pid lamd Mpirun.lsf

57. © Platform Computing Inc. 2003 57 Execution Host H1 PIMLIM master LIM Master Host lsblib LIMPIM bsub SBD MBD SBD SBD child pam high med low Queues MBSCHD Submission host H2 mpimon TaskStarter a.out: process 1 TaskStarter a.out: process 2 Scali mpi wrapper Root res LIM Signals and rusage collection Hostname & pid Platform LSF HPC for Linux/Myrinet - Scali MPI mpid mpisubmon

58. © Platform Computing Inc. 2003 58 Platform LSF HPC for Linux/QsNet LSF Execution host / RMS node n0 PIMLIM master LIM Master Host lsblib LIMPIM bsub SBD MBD SBD SBD child – exec() res Res – rms_run() high med low Queues MBSCHD Submission host RLA Job’s Allocation User Job Node n1 Node n2 RMS plugin

59. © Platform Computing Inc. 2003 59 Scyld Beowulf Integration Scyld Beowulf handles the systems management challenge effectively No OS to distribute / synchnronize Central point of control from master Single process space makes it appear as large SMP Platform integrates with Scyld treating cluster as SMP and allocating resources Integrate with mpirun, mpprun or bpsh to start tasks Collect resource usage from BPROC Collect load information via BPROC APIs Singe user interface across Sycld & non-Scyld env.

60. © Platform Computing Inc. 2003 60 Platform LSF HPC for Linux/BProc Bproc Front-end Node PIMLIM master LIM Master Host lsblib LIMPIM bsub SBD MBD SBD high med low Queues 1A 1B 1C 2 3 4 6B 6C MBSCHD 5 Submission host Job file H3 Res SBD child –exec() res allocated nodes Computing Nodes Bpsh/mpirun User Job Processes esub Modify submission options

61. © Platform Computing Inc. 2003 61 More info at: www.platform.com/customers www.platform.com/barriers

62. Q & A