Cluster Computer and its Architecture

• A cluster is a type of parallel or distributed processing system, which consists of a collection of interconnected stand-alone computers cooperatively working together as a single, integrated computing resource

• A node

– a single or multiprocessor system with memory, I/O facilities, & OS.

– generally 2 or more computers (nodes) connected together.

– in a single cabinet or physically separated & connected via a LAN cabinet, – appear as a single system to users and applications.

– provide a cost-effective way to gain features and benefits.

Windows of Opportunities

• Parallel Processing

– Use multiple processors p p to build MPP/DSM-like systems for parallel computing

• Network RAM

– Use memory associated with each workstation as aggregate DRAM cache.

• Software RAID (Redundant array of inexpensive disks)

– Possible to provide parallel I/O support to applications.

– Use arrays of workstation disks to provide cheap, highly available, and scalable file storage.

• Multipath Communication

– Use multiple networks for parallel data transfer between nodes.

Prominent Components of Cluster Computers

• High Performance Networks/Switches

– Ethernet (10Mbps),

– Fast Ethernet (100Mbps),

– Gigabit Ethernet (1Gbps)

– SCI (Dolphin - MPI- 12micro-sec latency)

– ATM

– Myrinet (1.2Gbps)

- InfiniBand

– Digital Memory Channel

– FDDI

– Advanced Switching

– Quadrics…

• Cluster Middleware

– Single System Image (SSI)

– System Availability (SA) Infrastructure

• Hardware

– DEC Memory Channel, DSM (Alewife, DASH), SMP Techniques

• Operating System Kernel/Gluing Layers

– Solaris MC, Unixware, GLUnix

• Applications and Subsystems

– Applications (system management and electronic forms)

– Runtime systems (software DSM, PFS etc.)

– Resource management and scheduling software (RMS)

• CODINE, LSF, PBS, NQS, etc.

• Parallel Programming Environments and Tools

– Threads (PCs, SMPs, NOW..)

• POSIX Threads

• Java Threads

– MPI

• Linux, NT, on many Supercomputers

– PVM

– Software DSMs (Shmem)

– Compilers

• C/C++/Java

• Parallel programming with C++ (MIT Press book)

– RAD (rapid application development tools)

• GUI based tools for PP modeling

– Debuggers

– Performance Analysis Tools

– Visualization Tools

• Applications

– Sequential

– Parallel / Distributed (Cluster-aware app.)

• Grand Challenging applications

– Weather Forecasting

– Quantum Chemistry

– Molecular Biology Modeling

– Engineering Analysis (CAD/CAM)

– ……………….

• PDBs, web servers,data-mining

Clusters Classification

• Application Target

– High Performance (HP) Clusters

• Grand Challenging Applications

– High Availability (HA) Clusters

• Mission Critical applications

• Node Ownership

– Dedicated Clusters

– Non-dedicated clusters

• Adaptive parallel computing GRID

• Communal multiprocessing

• Node Hardware

– Clusters of PCs (CoPs)

• Piles of PCs (PoPs)

– Clusters of Workstations (COWs)

– Clusters of SMPs CLUMPs) Constellations)

• Node Operating System

– Linux Clusters (e.g., Beowulf)

– Solaris Clusters (e.g., Berkeley NOW)

– NT Clusters (e.g., HPVM)

– AIX Clusters (e.g., IBM SP2)

– SCO/Compaq Clusters (Unixware)

– Digital VMS Clusters

– HP-UX clusters

– Microsoft Wolfpack clusters

• Node Configuration

– Homogeneous Clusters

• All nodes will have similar architectures and run the same OSs

– Heterogeneous Clusters

• All nodes will have different architectures and run different OSs

• Levels of Clustering

– Group Clusters (#nodes: 2-99)

• Nodes are connected by SAN like Myrinet

– Departmental Clusters (#nodes: 10s to 100s)

– Organizational Clusters (#nodes: many 100s)

– National Metacomputers (WAN/Internet-based)

– International Metacomputers (Internet-based, #nodes: 1000s to many millions)

• Metacomputing

• Web-based Computing

• Agent Based Computing

– Java plays a major in web and agent based computing