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Introduction to LAVA workload scheduler High Performance Computing and Networking Center (HPCNC) Kasetsart University   In collaboration with Innovative Extremist (INOX) Co.,Ltd. and Platform Computing Inc.
Outline ,[object Object]
LAVA workload scheduler
Installing and configuring LAVA Cluster
Workshop : Using LAVA
Introduction to HPC, Cluster and  Workload Scheduler
Cluster Computing ,[object Object]
Why now? ,[object Object]
Parallel Programming Systems which is portable and efficient
MPI (LAM, MPICH)
Software library that ease the application development e.g. Scalapack, Plapack, PetSc
PC also rule the world ,[object Object]
PC mass market nature drive the price down while performance increase rapidly
Cluster nature make it easy to capitalize on PC new technology right away
Why? Price Performance!
Goal of Clustering ,[object Object]
Goal of Clustering ,[object Object]
Applications ,[object Object]
Bioinformatics
Large scale financial analysis
Simulation
Drug Design
Automobile Design ( Crash Simulation) ,[object Object],[object Object]
(Google use more than 10000 node servers)  ,[object Object],[object Object]
Molecular  Dynamic Simulation ,[object Object]
HIV ,[object Object]
Graphics Rendering and Special Effect ,[object Object]
Massive number of rendering job needed to be done to create a movie
Cluster Software Architecture HTC HPC HPTC
High Throughput Computing ,[object Object]
High Throughput Computing (con) ,[object Object]
Excellence for many type of applications such as ,[object Object]
Distributed application such as massive rendering in animation industry ,[object Object],[object Object]
High Performance Computing ,[object Object]
Use of specialised codes, libraries ,[object Object]
Parallel Maths Libraries (ScaLapack) ,[object Object]
Pros and Cons ,[object Object]
Good when ,[object Object]
Speedup for a single instance of problem  is needed
Advantages and Challenges ,[object Object]
Plenty of free software ,[object Object],[object Object]
No powerful software development environment
Low compatibility with many enterprise computing environment
Parallel Application Development ,[object Object]
Message passing ā€“ data is exchanged by sending/receiving messages between processors
Workload Scheduler ,[object Object]
Main role of distributed computing
Allow users to share computing resources and time sharing ,[object Object]
Control shared resource usage for multiple users ,[object Object]
Scheduling Policies  ,[object Object]
Hide the complexity of using cluster's computing resources by submitting job to the scheduler
Key Features ,[object Object]
How many we can use?

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