1. OpenMosix, Open SSI, and LinuxPMI

2. 64 Raspberry Pi’s in a Lego enclosure
Clusters
Constructed from standard computers (nodes) without any shared physical memory
Single System Image (SSI)
Distributed computing method
SSI Cluster
A collection of machines that make up the cluster and it appears as a single machine
Linux Cluster Technologies
High-availability (HA)
High-performance (HP)
Load-Leveling
Web-Service
Storage
Database
64 Raspberry Pi’s in a Lego enclosure

3. Open SSI Project Brings open source cluster technologies together
Addresses all cluster environments with 3 key goals in mind
Availability
Scalability
Manageability
Best of each cluster solution
Modularity in mind

4. Open SSI Components NSC (NonStop Clusters for Unixware)
CI (Cluster Infrastructure)
GFS (Global File System)
DLM (Distributed Lock Manager)
LVS (Linux Virtual Server)
Lustre
Mosix
Scyld / Beowulf
HA (High Availability)
UML (User Mode Linux)

5. OpenMosix A tool for a Unix-like kernel, such as Linux Goals
Kernel extension for single-system image clustering (SSI)
Goals
To improve cluster-wide performance
Create a convenient multiuser, time-sharing environment
Run-time environment is a computing cluster
Capable of utilizing both UP & SMP nodes

6. OpenMosix Implementation
A Preemptive Process Migration (PPM) mechanism
A set of algorithms for adaptive resource sharing
Kernel level via a loaded module
Kernel remains un-modified
Transparent to application level
No Master-Slave relationship between nodes
Nodes make decisions independently
Dynamic configuration

7. Preemptive Process Migration (PPM)
Any process, anytime
Migration is based on algorithms
User is able to manually override
Unique Home-Node (UHN)
Migrating process is divided into two contexts:
User context
System context

8. PPM Implementation User Context (the remote)
Process can migrate many times
Contains: code, stack, data, memory-maps, and registers of the process
System Context (the deputy)
UHN dependent, doesn’t migrate
Contains description of the resources and a kernel-stack for the execution of system code on behalf of the process
The interface is well-defined
Easily forward information regarding interactions
Implemented at the Link Layer

9. Digging Deeper… Migrated process characteristics
Location transparency
System calls are executed synchronously
Intercepted by remote site’s link layer
Site Dependent / Independent
Drawback of deputy approach
Extra overhead in execution of system calls
File & network access operations

10. Resource Sharing Algorithms
Dynamic Load Balancing
Memory Ushering
Scheduling

11. Dynamic Load Balancing
Continuously attempting to reduce load difference between nodes
Algorithm is decentralized
Key Algorithmic Data
# of processors / speed
Dynamically responses to changes in node loads
Runtime characteristics of processes

12. Memory Ushering
Place the maximum # of processes in the cluster-wide RAM
Avoid thrashing and the swapping out of processes
Triggered by excessive paging
Shortage of free memory
Overrides load-balancing algorithm
Migrates a process to a node even if it creates uneven load distribution

13. Scheduling Algorithm
Algorithm to select which node a given program should run
Complication
Resources available on a cluster are heterogenous
Units of measure are incomparable
Memory, CPU, process communication
Solution
Create a unified algorithm framework
Convert total usage of heterogenous resources into a universal “cost”
Jobs are assigned to a machine where the cost is lowest
Market oriented economy

14. LinuxPMI Extended from the now closed, OpenMosix 2.6 branch
Multi-System-Image software
Works in clusters with diverse Linux distro’s
CPU types & specific kernel features must remain the same
Linux kernel patches implementing process migration
Allows the movement of a program from one machine to another and return

15. The End Questions? Resources PDF provided by professor Fukuda
IntroductionToOpenMosix.pdf
LoadBalancingOpenMosix.pdf
ssi-intro.pdf