Outline
• Midterm results summary
• Distributed file systems – continued
• Distributed shared memory
Midterm Results Summary
• The distribution
 70
0
 75
4
 80
6
 85
1
 90
3
1
 100
1
 95
> 100
2
• The average is 83.20
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Distributed Shared Memory
• Distributed computing is mainly based on the
message passing model
– Client/server model
– Remote procedure calls
• Distributed shared memory
– is a resource management component that
implements the shared memory model in
distributed systems, where there is no physically
shared memory
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Memory Hierarchies
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Virtual memory
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Page Table Mapping
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Distributed Shared Memory – cont.
• This is a further extension of the virtual
memory management on a single computer
– When a process accesses data in the shared
address space, a mapping manager maps the
shared memory address to the physical memory,
which can be local or remote
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Distributed Shared Memory – cont.
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Distributed Shared Memory – cont.
A mapping manager is a layer of software to map addresses in user
space into the physical memory addresses
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Distributed Shared Memory – cont.
• With DSM, application programs can access
data in the shared space as they access data in
traditional virtual memory
– Mapping manager can move data among the
local main memory, local disk, and another nodes
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Distributed Shared Memory – cont.
• Advantages of DSM
– It is easier to design and develop algorithms with
DSM than message passing models
– DSM allows complex structures to be passed by
reference, simplifying the distributed application
development
– DSM can cut down the overhead of communication
by exploiting locality in programs
– DSM can overcome some the architectural
limitations of shared memory machines
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Distributed Shared Memory – cont.
• Central implementation issues in DSM
– How to keep track of the location of remote data
– How to overcome the communication delays and
high overhead associated with communication
protocols
– How to improve the system performance
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The Central-Server Algorithm
• A central server maintains all the shared data
– It serves the read requests from other nodes or
clients by returning the data items to them
– It updates the data on write requests by clients
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The Central-Server Algorithm – cont.
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The Migration Algorithm
• In contrast to the central-server algorithm,
data in the migration algorithm is shipped to
the location of data access request
– Subsequent accesses can then be performed
locally
• Thrashing can be a problem
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The Migration Algorithm – cont.
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The Read-Replication Algorithm
• The read-replication algorithm allows
multiple node to have read access or one
node to have read-write access
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The Read-Replication Algorithm
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– cont.
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The Full-Replication Algorithm
• This is a further extension of the readreplication algorithm
– It allows multiple nodes to have both read and
write access to shared data blocks
• Data consistency issue
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The Full-Replication Algorithm
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– cont.
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Memory Coherence
• Memory consistency models
–
–
–
–
–
Sequential consistency
General consistency
Processor consistency
Weak consistency
Release consistency
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Memory Coherence – cont.
• Coherence protocols
– A protocol to keep replicas coherent
• Write-invalidate protocol
– A write to a shared data causes the invalidation of
all copies except the one where the write occurs
• Write-update protocol
– A write to a shared data causes all copies of that
data to be updated
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Design Issues
• Granularity
– The size of the shared memory unit
– Advantages of large sizes
• A page size that is a multiple of the size provided by
the underlying memory management system allows
for the integration of DSM and the memory
management system
• Better utilization of locality of reference
– Disadvantages
• The greater the chance for contention
• False sharing
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False Sharing
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Design Issues – cont.
• Page replacement
– Traditional methods such as LRU can not be used
directly
– Page access modes must be taken into
consideration
• For example, private pages may be replaced before
shared pages
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Case Studies
• IVY
– Integrated Shared Virtual Memory at Yale
– The granularity is a page
– The address space is divided into shared virtual
memory address space and private space
• The coherence protocol
– Write fault handling
– Read fault handing
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IVY – cont.
• Coherence protocol
– The centralized manager scheme
– Fixed distributed manager scheme
– Dynamic distributed manager scheme
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IVY – cont.
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IVY – cont.
• Double fault
• Memory allocation
• Process synchronization
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Case Studies – cont.
• Mirage
– Thrashing control
• Clouds
– The RA kernel
– Distributed shared memory controller
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Summary
• Distributed shared memory tries to provide an
easy-to-use interface for distributed applications
– Distributed programs access data in the shared
address space as they access data in local memory
• However, the performance is a critical issue
– Replication is used to reduce the high cost of
communications
– Memory coherence needs to be taken of
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