Transcript Message Passing Framework for Globally Interconnected Clusters

A-JUMP Message Passing
Framework for Globally
Interconnected Clusters
Mr. Sajjad Asghar
Advance Scientific Computing Group,
National Centre for Physics,
Islamabad, Pakistan.
Research Papers
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Mehnaz Hafeez, Sajjad Asghar, Usman A. Malik, Adeel-ur-Rehman,
and Naveed Riaz, “Message Passing Framework for Globally
Interconnected Clusters”, CHEP 2010, Taipei, Taiwan (Accepted).
Sajjad Asghar, Mehnaz Hafeez, Usman A. Malik, Adeel-ur-Rehman,
and Naveed Riaz, “A Framework for Parallel Code Execution using
Java”, IEEE International Conference IEEE International Conference
TENCON2010, Fukuoka, Japan (Accepted).
Mehnaz Hafeez, Sajjad Asghar, Usman A. Malik, Adeel-ur-Rehman,
and Naveed Riaz, “Survey of MPI Implementations delimited by
Java”, IEEE International Conference TENCON2010, Fukuoka, Japan
(Accepted).
Adeel-ur-Rehman, Sajjad Asghar, Usman A. Malik, Mehnaz Hafeez and
Naveed Riaz , “Multi-lingual Binding of MPI Code on A-JUMP”,
IEEE International Conference on Frontiers of Information Technology,
Islamabad Pakistan (Submitted).
Sajjad Asghar, Mehnaz Hafeez, Usman A. Malik, Adeel-ur-Rehman,
and Naveed Riaz, “A-JUMP, Architecture for Java Universal
Message Passing”, IEEE International Conference on Frontiers of
Information Technology, Islamabad Pakistan (Submitted).
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Layout
Introduction
 Related Work
 A-JUMP Frame work
 Message Passing for Interconnected
Clusters
 Performance Analysis
 Future work & Conclusion
 References
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Message Passing Interface
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Defacto Standard and defines interfaces
for C/C++ and Fortran
Programmer defines
 the work and data distribution
 How and when communication has to be
done via communication according to the
underlying algorithm.
Synchronization is implicit (can also be
user-defined)
Support distributed memory architectures
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Message Passing Interface
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Features
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5.
6.
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Standardization
Portability
Performance
Efficient implementations
Availability
Functionality
Scalability
The MPI Forum identified some critical
shortcomings of existing message passing
systems in areas such as complex data
layouts or support for modularity and safe
communication.
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Java and MPI
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Java is an excellent basis for implementing message
passing framework.
 Java supports multi-paradigm communications
environment.
 Java’s bytecode can be executed securely on many
platforms.
It allows integrating many technologies that are used
for existing software development.
Java provides many desired features for building wide
range of applications like; standalone, client-server,
semantic web, enterprise, mobile, graphical or
distributed.
Thus, it makes Java an excellent basis for achieving
productivity of parallel applications.
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Layout
Introduction
 Related Work
 A-JUMP Frame work
 Message Passing for Interconnected
Clusters
 Performance Analysis
 Future work & Conclusion
 References
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Architecture for Java Universal
Message Passing (A-JUMP)
Framework
A-JUMP is an HPC framework built for
distributed memory architectures in
order to facilitate explicit parallelism.
 A-JUMP is purely written in Java.
 A-JUMP is based on mpijava1.2
specifications.
 A-JUMP backbone is called High
Performance Computing Bus (HPC
Bus).
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HPC Bus of A-JUMP
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Communication backbone of the A-JUMP
 Based on Apache ActiveMQ
Includes inter-process communication, monitoring and
propagation of Registry information.
Provides interoperability between hardware resources
and communication protocols.
Ensures that any changes in communication protocols
and network topologies will remain transparent to end
users.
Ensures loosely coupled services and components.
Segregate the application and communication layers.
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HPC Bus of A-JUMP
C++ Client
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Architecture for Java Universal
Message Passing (A-JUMP)
Framework
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A-JUMP is designed to provide the following features
to write parallel application;
 Message Passing for Interconnected Clusters
 Multiple Languages
 Interoperability
 Portability
 Heterogeneity for resource environment
 Network Topology Independence
 Multiple Network Protocol Support
 Communication Mode Autonomy (i.e. asynchronous
communication)
 Different Communication Libraries
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A-JUMP Component
Diagram
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Layout
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Introduction
Related Work
Architecture for Java Universal Message
Passing (A-JUMP) Framework
Message Passing for Interconnected
Clusters
Performance Analysis
Future work & Conclusion
References
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Grid Computing and MPI
GRID
MPI
Dynamic
Resources
Static
can add/delete
dynamically
Static
Configuration Host
File
Voluminous data exchange
over Internet
Data exchange over cluster
Design for internet computing Design for cluster computing
Heterogeneous resource
environment
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Homogenous resource
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Grid Computing and MPI
GRID
MPI
Specific to certain scientific
applications
Generic and not specific to
certain scientific applications
Independent from base
Operating System
Code execution is Operating
System dependent
Support for different
communication protocols
paradigm
No support for different
communication protocols
paradigm
High network latencies due
to complex layout
Low network latencies for
message passing
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A-JUMP, Message Passing
for Interconnected Clusters
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It supports the dynamic behaviour of interconnected
clusters with MPI functionality.
It is written in pure Java and does not incorporate
any native code/libraries.
It provides asynchronous mode of communication
for both message passing and code distribution
over the clusters.
It provides sub-clustering of resources for different
jobs to utilize free resources efficiently.
It is designed for both internet and cluster
computing.
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A-JUMP, Message Passing
for Interconnected Clusters
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HPC Bus (interconnected clusters)
C++ Client
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A-JUMP, Message Passing
for Interconnected Clusters
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It segregates the communication layer from
the application code.
It is easy to adopt new communication
technologies without changing the
application code.
It offers support for both homogeneous and
heterogeneous clusters for parallel code
execution.
A set of easy to use APIs are part of the
framework.
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Layered Architecture
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A-JUMP framework
Components
Machine Registry
 Dynamic Resource Discovery
 Dynamic Resource Allocation
 Message Security
 Job Scheduler
 Monitoring
 Code Migrator/Execution
 API Classes
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Machine Registry
Machine Registry provides a list of machines that are
dynamically added or removed from the framework.
To become the part of the framework, every worker
machine has to run Code Migrator/Execution service.
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Code Migrator/Execution service sends the request to the
Machine Registry for a unique rank.
Machine Registry assigns unique ranks to the newly
added machines.
Machine Registry is also responsible to inform Monitoring
module about the newly added resources.
In future It will records the static information about each
machine which has been registered i.e. number of CPUs
and number of cores per CPU.
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Dynamic Resource
Discovery (DRD)
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It keeps track of the resources that are part of the AJUMP clusters (system size).
It gets the information from Machine Registry to
index the available machines that are registered with
the Machine Registry.
DRD fetches the information about the state of the
machines from Monitoring.
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The states are defined as free and busy.
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Dynamic Resource
Allocation (DRA)
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DRA finds the availability of free
resources on A-JUMP clusters.
Client sends the request for the required
numbers of free processors that are
needed to run the job.
DRA searches the free available
resources from the index maintained by
DRD and monitoring.
It creates a list of machine that could be
used to define a sub cluster from available
machines and return this list to client
APIs.
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Message Security
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It provides the facility to encrypt the
outgoing messages.
Current implementation is based on
simple symmetric encryption
technique.
Requires more performance analysis
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Job Scheduler(JS)
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JS distributes incoming jobs to the cluster.
The jobs are sent to the JS by client APIs through
ActiveMQ.
It works on queuing mechanism which keeps
incoming jobs queued until free resources are
available for execution.
If the number of available resources is less than the
required resources then job will not be submitted.
Otherwise, a sub-cluster is created by JS according
to the requirement.
Free machines will remain available for new job
request.
P2P-MPI is the only other implementation which
provides sub- clustering.
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Monitoring
Job Scheduler gets the information from the Monitoring
component.
Monitoring records the dynamic information about the
computational resources that are part of the
framework.
It records number of busy and free CPUs.
It helps the Job Scheduler to find the best match for
task in hand.
Monitoring maintains two distinct states of the
machines available in the cluster; these are free and
busy.
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As soon as a machine starts job execution, it informs
Monitoring to change its state from free to busy.
Monitoring is also responsible to set the state of the
machine back to free as soon as the job gets finished.
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Code Migrator/Execution
Code Migrator/Execution distributes and executes a task over
the network.
A built-in communication API is a part of this component.
Enables the tasks to do collective and point to point
communication.
Both communications between the tasks as well as distribution of
code are done in an asynchronous way through ActiveMQ.
As soon as a resource gets free, the job is dispatched by Job
Scheduler to the designated machine.
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The Code Migrator/Execution on the destination machine
accepts the codes and starts its execution.
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The underlying code distribution takes place through Code
Migrator/Execution.
The distribution is done through ActiveMQ.
The streamed output is redirected to the user machine.
The basic send() and receive() are also incorporated with the
help of communication libraries written purely in Java.
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Code Migrator/Execution
Code Adaptor
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Communication APIs
The proposed framework offers easy to use set of
communication APIs for writing parallel code.
These APIs are close to MPI specifications for Java
(mpijava1.2).
API Classes
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Sub cluster Grouping (MPI_COMM_WORLD )
MPI.Init
MPI.Finalize
MPI.COMM_WORLD.Rank
MPI.COMM_WORLD.Size
Send
Receive
Broadcast
Gather
Scatter
Allgather
Reduce
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Workflow of A-JUMP for
Interconnected Clusters
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Figure illustrates A-JUMP relationship and the information
shared between the different components.
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It describes the step by step the flow of program running parallel
on different clusters.
There are three main entities;
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A client is a process looking for computing resources.
A code adaptor is a process offering computing resources
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Each machine in cluster must run Code Adaptor to receive the
incoming program files. The role of a Code Adaptor or a client is
not fixed. A machine may serve as a Code Adaptor as well as
client.
DRD/DRA is a process that allocates the free resources to the
client for job submission.
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Clients
Code Adaptors
Dynamic Resource Discovery/Dynamic Resource Allocation
(DRD/DRA)
DRD/DRA maintains the index of resources and creates subclusters based on free
computing
resources.
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2. Resource
3.
4.
5.
6.
7.
8.
Request
Get
Create
Return
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Number
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Monitoring. As soon as the submitted job finishes, a request of change in status
from busy to free is sent back to machine Registry. Code Adaptors are also
responsible to sends results back to the client.
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Layout
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36
Introduction
Related Work
Architecture for Java Universal Message
Passing (A-JUMP) Framework
Message Passing for Interconnected
Clusters
Performance Analysis
Future work & Conclusion
References
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Performance Analysis
Communication Performance
Measurement
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Code Speed-up Performance
Analysis
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Ping Pong Latency Test
Network Throughput Measurement
Embarrassingly Parallel (EP) Benchmark
JGF Crypt Benchmark
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P2P-MPI
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S. Genaud and C. Rattanapoka, “P2P-MPI: A Peer-toPeer Framework for Robust Execution of Message
Passing Parallel Programs,” Journal of Grid
Computing, 5(1):27-42, 2007.
Strength
 Pure Java
 Supports distributed memory models
 Supports heterogeneous environment
 Supports high speed networks
Weakness
 No support for high speed networks
 Slow Performance
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Test Environment
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Results are collected on an environment that simulates
globally interconnected clusters.
The hardware resources involved in conducting the
tests include; 9 single core machines divided into two
clusters.
The clusters are connected with 1 Gbps bandwidth.
The machines are running Windows Server 2003 (with
SP2) and Windows XP (with SP3).
The TCP window size is default on all the machines in
clusters.
No optimization is done at the level of OS as well as at
the level of hardware.
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Time (ms)
Ping Pong Latency Test
Data Size (bytes)
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Network Throughput
Measurement
Mbps
Chart Title
45
40
35
30
25
20
15
10
5
0
A-JUMP (inter connected Clusters)
P2P-MPI
1
100
1K
4K
8K
16K
32K
64K
128K
256K
512K
Data Size (bytes)
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Code Speed UP Performance
Analysis (NAS EP)
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A-JUMP (Interconnected Clusters)
P2P-MPI
100
Tinme(sec)
80
60
40
20
0
2
4
6
8
Number of CPUs
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Code Speed UP Performance
Analysis (NAS EP)
Performance Gain of A-JUMP
30
25
25.24%
22.28%
Gain(%)
20
15
10
5
8.33%
6.44%
0
2
4
6
8
Number of CPUs
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Code Speed UP Performance
Analysis (JGF Crypt Class A)
2.5
A-JUMP interconnected clusters
P2P-MPI
Time(sec)
2
1.5
1
0.5
0
2
4
6
8
Number of CPUs
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Code Speed UP Performance
Analysis (JGF Crypt Class B)
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A-JUMP interconnected clusters
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P2P-MPI2
Time (sec)
12
10
8
6
4
2
0
2
4
6
8
Number of CPUs
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Layout
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47
Introduction
Related Work
Architecture for Java Universal Message
Passing (A-JUMP) Framework
Message Passing for Interconnected
Clusters
Performance Analysis
Conclusion and Future work
References
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Conclusion & Future Work
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A-JUMP for interconnected clusters is loosely coupled
with its communication layer
It supports sub clustering
It provides dynamic resource management
It carries multiple communication protocols
It supports asynchronous message passing
It supports heterogeneous environment
Performance analysis results of A-JUMP
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For small message sizes are better than P2P-MPI
For large message sizes are promising and comparable
with P2P-MPI
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Conclusion & Future Work
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The communication Library will be
improved for message sizes >= 256k
Support for different security techniques
The other area of focus will be to
improve network latencies and lessen
the communication overheads
Multilingual Support for Interconnected
Clusters
More NAS and JGF benchmarks
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Layout
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50
Introduction
Related Work
Architecture for Java Universal Message
Passing (A-JUMP) Framework
Message Passing for Interconnected
Clusters
Performance Analysis
Conclusion and Future work
References
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References
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