Inter-Application Control
Through Global States
Monitoring On a Grid
M. Tudruj, J. Borkowski, D. Kopanski
Polish-Japanese Institute
of Information Technology,
Koszykowa 86, 02-008 Warsaw, Poland
1
Monitoring global states
Processes can communicate with a number of Synchronizers. Synchronizers
learn state information from processes and send back control information.
Sa
synchronizers
processes
state
information
P1
P2
P3
q
P4
Arrows represent reliable,
asynchronous communication
channels
control
Sb
2
Monitoring consistent global states
•There is no global clock, no shared memory
•Synchronizer must be able to order properly incoming events to build
Strongly Consistent Global States (SCGS)
•SCGS is a combination of process local states, one state from each
process, such that the local states are pairwise concurrent. E.g. <s1,t1>
is a SCGS, <s1,t2> is not.
P1
e1
s1
e2
t1
P2
t2
f1
f2
m2
m1
sync
3
Strongly Consistent Global States
•Events must have timestamps to be able to order messages correctly.
Logical vector clocks or real time intervals based on roughly
synchronized local clocks can be used
•If process local clocks are synchronized with a known accuracy, then
real time interval timestamps can be used to identify SCGS
4
Computation activation and cancellation caused
by predicate evaluation
5
GRADE system
A complete graphical programming environment for developing message
passing applications designed at Parallel and Distributed Systems
Laboratory of the SZTAKI Institute of Hungarian Academy of Sciences
•Application level specifies processes
and their interconnections
•Process level defines control flow
diagram of a process
•Text level is used to enter sequential C
code into elements of a flow diagram
loop
begin
send through
port 1
receive
from port 0
sequential code in C
6
GRADE extension – PS-GRADE
State information monitoring
local state info transfer channels
signal transfer channels
standard message passing channels
7
PS-GRADE - synchronizer
Start
State
messages
Wait for a process/application
state information message
Is a new SCGS / OGS detected?
No
Yes
Update state records and
make them available for
control predicates
Condition 1
Predicate 1
satisfied?
Yes
Send sync
signals
Condition 2
No
Predicate 2
satisfied?
Yes
Send sync
signals
Condition k
...
No
Predicate k
satisfied?
No
Yes
Send sync
signals
8
PS-GRADE– synchronizer
reception of state
variables
condition
send signal
condition window
control flow window
9
PS-GRADE– Process - control flow window
Start signal -sensitive
region "watching signal"
Start signal insensitive region
Resume
interrupted
computations
Send state
End signal insensitive region
Cancel
computations
End signal -sensitive
region "endwatching signal"
10
PS-GRADE– synchronizer hierarchy
11
The principles of Grid application control
Control of Grid application by:
•Data control flow (similarly to P-GRADE Workflow
implemented by SZTAKI) , based on input and output files for
cluster application
•Grid Synchronizer :
•Collects information (vector of state) about application
state
•Detects SCGS or OGS
•Computes conditions
•Sends signals to the application
12
A Grid-level synchronizer inserted into
a workflow graph
A1
1
1
A2
4
3
4
2
1
Synch1
5
1
A4
5
2
3
3
2
2
6
4
3
1
A5
3
1
A3
5
2
4
1
A6
13
A Grid-level synchronizer and an application
Application A2
GRID Synchronizer
Application
A3
Application
A4
Application
A5
14
Grid PS-GRADE environment general structure
15
Organizing Grid-level program execution control
The following co-operation schemes included into the proposed
Grid environment will be discussed:
A1
1
Simple workflow.
A selected application starts executing after a set
of selected applications is completed. Example:
complicated scientific computations performed
layer by layer in different computer networks.
1
1
A2
2
A3
3
2
1
A4
2
1
2
A5
16
Alternative workflow.
One of several applications is selected for
execution depending on the results (state) of
former applications. Example: one of two
available program packages is run
depending on computation results
performed so far.
A1
2
1
1
Synch1
2
1
A2.1
2
…
1 2
A2.N
Partial canceling of workflow:
Applications that become superfluous from the point of view of the general purpose
of computation are stopped. Example: The exhaustive parallel search on a Grid for
the optimal solution in a solution space is stopped or restricted when the search
provides a satisfactory solution.
17
Supporting workflow:
A set of currently executed applications require activation of auxiliary applications,
which will provide useful results. Example: In a coarse grain simulation of a system
of moving objects a collision that appears, stimulates a change in the Grid
application configuration. An application which models the collision in a detailed way
(with a fine granularity of events) is activated. After detailed simulation of the
collision the coarse grain of the simulation process is restored.
A1.1
3
4
2
1
Synch1
3
3
2
2
A2.N
Workflow coupling:
A common (global) status of many
applications is monitored and control
directives are distributed to particular
applications of needed. Applications
compute parameters that are subject to
mutual exchange. Some parameters in
meta-level applications are updated with
the use of results of some auxiliary
computations
A1.1
…
A1.N
3
2
4
1
Synch1
3
2
3
2
3
3
2
2
A2.1
…
A2.N
18
Example – A Grid TSP application structure
PreProc
1
3
B&B1
3
3
2
1
B&B2
1
4
2
0
2
3
3
2
1
3
B&B3
Synch1
4
2
Heur1
1
2
Heur2
1
4
4
1
4
1
PostProc
19
The TSP application
Synch1 conditions:
DataRequest, MinDist, FinishCond (left to right)
20
The TSP application
B&B part: condition window
B&B part: communication diagram
Heuristic search
Application
structure
search process
application structure
21
Conclusions
•The paper has presented how the synchronization-based parallel application
control can be extended and ported onto the GRID level. With the use of the
proposed method we can create an advanced control of many applications
running in the GRID environment. Inter–application coordination between
programs, which are executed on different GRID sites, is supported.
•We identify five types of Grid-level program execution control
•The presented example shows that the new programming environment
provides convenient means for designing complicated Grid applications control.
Being on the Grid, we can extend the time consuming parts of the applications
and run it on any available clusters during the middle stage of the algorithm.
The best results from the heuristic part of the application obtained in a shorter
time than by the B&B computations can support faster finding of the exact
solution.
22