This document discusses scheduling for tightly coupled multiprocessor systems. It describes two types of multiprocessor systems: loosely coupled systems where each processor has its own memory and I/O, and tightly coupled systems where processors share main memory. It also defines levels of granularity in parallel applications from independent to fine-grained parallelism. The key issues in multiprocessor scheduling are process assignment, multiprogramming, and dispatching. Different strategies like load sharing, gang scheduling, and dedicated assignment are used to address these issues.

1. Multiprocessor scheduling

2. Introduction
 When a computer system contains more than a single processor, several
new issues are introduced into the design of scheduling functions. We will
examine these issues and the details of scheduling algorithms for tightly
coupled multi-processor systems.

3. Classifications of Multiprocessor
Systems
 Loosely coupled or distributed multiprocessor, or cluster
 Each processor has its own memory and I/O channels
 Functionally specialized processors
 Such as I/O processor
 Controlled by a master processor
 Tightly coupled multiprocessing
 Processors share main memory
 Controlled by operating system

4. Interconnection Network
P P P
Memory
disk
Memory Memory
disk disk
Shared Nothing
(Loosely Coupled)
P P P
Interconnection Network
Global Shared Memory
disk disk disk
Shared Memory
(Tightly Coupled)
Memory Memory Memory
P P P
Interconnection Network
disk disk disk
Shared Disk

5. Granularity
 A good metric for characterizing multiprocessors and placing then in
context with other architectures is to consider the synchronization
granularity, or frequency of synchronization, between processes in a
system.
 Five categories of parallelism that differ in the degree of granularity
can be defined:
1. Independent parallelism
2. Very coarse granularity
3. Coarse granularity
4. Medium granularity
5. Fine granularity

6. Independent Parallelism
 With independent parallelism there is no explicit synchronization among
processes.
 Each process represents a separate, independent application or job.
 This type of parallelism is typical of a time-sharing system.
 The multiprocessor provides the same service as a multiprogrammed
uniprocessor, however, because more than one processor is available,
average response times to the user tend to be less.

7. Coarse and Very Coarse-Grained
Parallelism
 With coarse and very coarse grained parallelism, there is synchronization
among processes, but at a very gross level.
 This type of situation is easily handled as a set of concurrent processes running
on a multi-programmed uni-processor and can be supported on a
multiprocessor with little or no change to user software.
 Good for concurrent processes that need to communicate or synchronize can
benefit from the use of a multiprocessor architecture.
 In the case of very infrequent interaction among the processes, a distributed
system can provide good support. However, if the interaction is somewhat
more frequent, then the overhead of communication across the network may
negate some of the potential speedup. In that case, the multiprocessor
organization provides the most effective support.

8. Medium-Grained Parallelism
 Single application is a collection of threads
 Threads usually interact frequently
Fine-Grained Parallelism
 Highly parallel applications
 Specialized and fragmented area

9. Design Issues For Multiprocessor
Scheduling
 Scheduling on a multiprocessor involves three interrelated
issues:
1. The assignment of processes to processors
2. The use of multiprogramming on individual processors
3. The actual dispatching of a process
 Looking at these three issues, it is important to keep in mind
that the approach taken will depend, in general, on the
degree of granularity of the applications and on the
number of processors available.

10. 1: Assignment of Processes to Processors
 Treat processors as a pooled resource and assign process to processors on
demand
 Permanently assign process to a processor
 Known as group or gang scheduling
 Dedicate short-term queue for each processor
 Less overhead
 Processor could be idle while another processor has a backlog
 Global queue
 Schedule to any available processor

11. Assignment of Processes to Processors
 Master/slave architecture
 Key kernel functions always run on a particular processor
 Master is responsible for scheduling
 Slave sends service request to the master
 Disadvantages
 Failure of master brings down whole system
 Master can become a performance bottleneck
 Peer architecture
 Kernel can execute on any processor
 Each processor does self-scheduling
 Complicates the operating system
 Make sure two processors do not choose the same process

12. Process Scheduling
 Single queue for all processes
 Multiple queues are used for priorities
 All queues feed to the common pool of processors

13. Multiprocessor Thread Scheduling
 Executes separate from the rest of the process
 An application can be a set of threads that cooperate and execute concurrently in the
same address space
 Load sharing
 Processes are not assigned to a particular processor
 Gang scheduling
 A set of related threads is scheduled to run on a set of processors at the same time
 Dedicated processor assignment
 Threads are assigned to a specific processor
 Dynamic scheduling
 Number of threads can be altered during course of execution

14. Load Sharing
 Load is distributed evenly across the processors
 No centralized scheduler required
 Use global queues
Disadvantages of Load Sharing
 Central queue needs mutual exclusion
 Preemptive threads are unlikely to resume execution on the same
processor
 If all threads are in the global queue, all threads of a program will not gain
access to the processors at the same time

15. Gang Scheduling
 Simultaneous scheduling of threads that make up a single process
 Useful for applications where performance severely degrades when any
part of the application is not running
 Threads often need to synchronize with each other

16. Dedicated Processor Assignment
 When application is scheduled, its threads are assigned to a processor
 Some processors may be idle
 No multiprogramming of processors

17. Dynamic Scheduling
 Number of threads in a process are altered dynamically by the application
 Operating system adjust the load to improve utilization
 Assign idle processors
 New arrivals may be assigned to a processor that is used by a job currently using
more than one processor
 Hold request until processor is available
 Assign processor a job in the list that currently has no processors (i.e., to all
waiting new arrivals)