[Savannah-register-public] [task #5612] Submission of OpenDos - An Open Source Dynamic Optimization System

[OpenDos Team]

URL:
  <http://savannah.gnu.org/task/?func=detailitem&item_id=5612>

                 Summary: Submission of OpenDos - An Open Source Dynamic
Optimization System
                 Project: Savannah Administration
            Submitted by: opendos
            Submitted on: Monday 05/29/2006 at 06:59
         Should Start On: Monday 05/29/2006 at 00:00
   Should be Finished on: Thursday 06/08/2006 at 00:00
                Category: Project Approval
                Priority: 5 - Normal
                  Status: None
                 Privacy: Public
             Assigned to: None
        Percent Complete: 0%
             Open/Closed: Open
                  Effort: 0.00

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######### REGISTRATION DETAILS ######### 

Full Name:
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  OpenDos - An Open Source Dynamic Optimization System

System Group Name:
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  opendos

Type:
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  non-GNU software & documentation

License:
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  GNU General Public License V2 or later

Description:
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  Project name : OpenDos – Dynamic Optimization System
College :Maharashtra Academy Of Engineering.

Project group

1.Poornima.P.Kamath . email-id: address@hidden
2.Divya Sasidharan email-id: address@hidden
3.Sumit Kumar email-id: address@hidden
4.Sandeep Kumar email-id: address@hidden

Project Guides:
Internal guide: Prof Pallavi Talegaonkar.
External guide: Mr Saurabh Verma (Codito technologies)
Sponsored by: Codito Technologies, Pune.

Dynamic optimization refers to the runtime optimization of a native program
binary. Dynamic binary translation is an important area for compiler
research, because additional information available at runtime can
substantially improve the effectiveness of optimizations. The challenge is to
monitor a process during its execution. We are building a system for
monitoring and modifying a program’s behavior while it is running. The
runtime environment exposes several execution paths that have not been
discovered during static optimization. This gives us several opportunities
for performing optimizations even though the binary is statically optimized.
As the 90-10 rule 90% of the program execution time is used for 10% of the
program region. The main aim of our system is to identify this 10% and
optimize it. The lightweight dynamic binary optimizer is a software that
optimizes the executables at run-time. This optimizer is aimed to optimize
i386 executables of ELF format. It is entirely user-level software, which
works on the native binaries.
As the binaries shipped by the vendors are not fully optimized there are
various opportunities for optimizing these binaries. Also as optimization is
done at runtime no extra code is added to the binary. Also our system
exploits the runtime information available to it. This includes information
about the taken branches, frequently executed path etc.
Using this information we can apply certain optimizations, which are termed
aggressive during static compilation. Also our system is an open source
effort towards dynamic optimization.



SYNOPSIS


1.1 Problem Statement:
Static optimization techniques do not perform optimization across shared
libraries. Also legacy code where code is unavailable cannot be optimized
using static techniques .
1.2 Soultion:
A solution to above problem is dynamic optimization. Dynamic optimizers apply
code to an executing application. Applying optimizations dynamically provides
several benefits over static optimization, particularly for control-intensive
programs. For example dynamic optimization span branches and calls including
calls to dynamically linked code, which typically hinder static
optimizations. In many cases, a dynamic optimizer is able to identify and
optimize longer hot execution paths than a static optimization. Also because
it naturally and transparently profiles during execution, a dynamic optimizer
can adapt to changing program behaviour.

1.3 Functional Description:
1.Region selection.
The optimizer observes the execution and generates a series of traces (code
which is executed frequently) that represent the common dynamic sequencing of
instructions.
2.Optimization.
It applies optimizations or transformations to the generated code traces.
3. Optimized region storage(fragment cache)
It stores the optimized code traces in a software based code cache.
4.Dispatch of optimized code.
It intercepts execution and directs it to code cache for all future
executions of the optimized code traces until program termination.

2.1 OUR SYSTEM DESIGN

The Image Cannot be Displayed.


MAIN COMPONENTS
1. Bootstrapper:
This module intercepts control from the running binary and gives control to
our interpreter.It loads and initializes all the modules of our system.

2.Interpreter.
This module does the job of profiling the executable.
It performs two tasks, a).It disassembles the binary till it gets a control
transfer instruction.
b).It simulates control transfer instructions and processes and records the
frequently executed hot regions.

3.Epilog-Prolog adder.
This module adds the epilog and prolog code along with exit stubs and
compensation code.As we execute hot code from fragment cache, there has to be
a change in context between executable and fragment code.
So the epilog and prolog code saves the register context

4.Optimizer.
The optimizer optimizes the hot code. The optimizer performs optimizations
like constant propagation. Copy propagation, etc.

5.Fragment cache manager.
The hot code that is frequently executed code is stored in fragment cache.
This code is in binary and is stored in a software code cache.
This is managed by fragment manager.
2.2 Software Process Life Cycle
The primary tasks involved in this project is to profile the executable as
well as optimize it at runtime . We can increase the optimizations in each
release Hence we use the Incremental model for the development of the
project.

2.3 Platforms
The dynamic optimizer we are developing is a user level software on linux
platform. It is for i386-Elf executables.


2.4 Area of work

Main category
Software
Subcategory:
System applications

2.5 Function point analysis

Measurement parameter Count Complex Count*average
Number of user input 1 6 6
Number of user output 1 7 7
Number of files 21 15 315
Count-total 328

FP= 328*(0.65+0.01*sum(Fi)) ,Fi=8
FP=239.44


2.6 Test Suites:

SPEC 2000 benchmarks
1.wc
2.bzip2
3.gzip

THE SOURCE CODE HAS NOT BEEN UPLOADED, BUT WILL BE UPLOADED IN A DAY OR TWO.


SOURCE URL : opendos.souceforge.net
BLOG       : opendos.blogspot.com
GROUP      : groups.google.co.in/group/opendos
             groups.yahoo.com/groups/opendos             
MAIL       : address@hidden



Other Comments:
---------------
  SIR WE HAVE NOT YET UPLOADED THE SOURCE BUT WE WILL DO IT AS EARLY AS
POSSIBLE. THE SOFTWARE IS IN TESTING PHASE NOW.








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