CXperf is a parallel application analysis tool that helps developers improve the performance of applications on Exemplar parallel servers. It analyzes applications, supports multiple parallel programming models, and interprets results visually. CXperf gathers performance measurements during application execution and then provides graphical analysis to help identify optimization opportunities. This helps developers fine-tune applications to more efficiently utilize complex HPC architectures.
CS266 Software Reverse Engineering (SRE)
Introduction to Software Reverse Engineering
Teodoro (Ted) Cipresso, teodoro.cipresso@sjsu.edu
Department of Computer Science
San José State University
Spring 2015
This calculator has been developed by me. It gives high precision results which
Normal calculator can not give. It is helpful in calculations for Space technology,
Supercomputers, Nano technology etc. I can give this calculator to interested people.
Highlighted notes of article while studying Concurrent Data Structures, CSE:
The Concurrency Challenge
Wen-mei W. Hwu, Kurt Keutzer, Tim Mattson
IEEE Design and Test
The Concurrency Challenge
July-August 2008, pp. 312-320, vol. 25
DOI Bookmark: 10.1109/MDT.2008.110
Wen-mei Hwu is a professor and
the Sanders-AMD Endowed Chair of
Electrical and Computer Engineering
at the University of Illinois at Urbana-
Champaign. His research interests
include architecture and compilation for parallel-
computing systems. He has a BS in electrical
engineering from National Taiwan University, and
a PhD in computer science from the University of
California, Berkeley. He is a Fellow of both the IEEE
and the ACM.
Kurt Keutzer is a professor of
electrical engineering and computer
science at the University of California,
Berkeley and a principal investigator
in UC Berkeley’s Universal Parallel
Computing Research Center. His research focuses
on the design and programming of ICs. He has a BS
in mathematics from Maharishi International University, and an MS a PhD in computer science from
Indiana University, Bloomington. He is a Fellow of the
IEEE and a member of the ACM.
Timothy G. Mattson is a principal
engineer in the Applications Research
Laboratory at Intel. He research inter-
ests focus on performance modeling
for future multicore microprocessors
and how different programming models map onto
these systems. He has a BS in chemistry from the
University of California, Riverside; an MS in chemistry
from the university of California, Santa Cruz; and a PhD in theoretical chemistry from the University of
California, Santa Cruz. He is a member of the
American Association for the Advancement of Sci-
ence (AAAS).
https://ieeexplore.ieee.org/document/4584454
STATISTICAL ANALYSIS FOR PERFORMANCE COMPARISONijseajournal
Performance responsiveness and scalability is a make-or-break quality for software. Nearly everyone runs into performance problems at one time or another. This paper discusses about performance issues faced during Pre Examination Process Automation System (PEPAS) implemented in java technology. The challenges faced during the life cycle of the project and the mitigation actions performed. It compares 3 java technologies and shows how improvements are made through statistical analysis in response time of the application. The paper concludes with result analysis.
CS266 Software Reverse Engineering (SRE)
Introduction to Software Reverse Engineering
Teodoro (Ted) Cipresso, teodoro.cipresso@sjsu.edu
Department of Computer Science
San José State University
Spring 2015
This calculator has been developed by me. It gives high precision results which
Normal calculator can not give. It is helpful in calculations for Space technology,
Supercomputers, Nano technology etc. I can give this calculator to interested people.
Highlighted notes of article while studying Concurrent Data Structures, CSE:
The Concurrency Challenge
Wen-mei W. Hwu, Kurt Keutzer, Tim Mattson
IEEE Design and Test
The Concurrency Challenge
July-August 2008, pp. 312-320, vol. 25
DOI Bookmark: 10.1109/MDT.2008.110
Wen-mei Hwu is a professor and
the Sanders-AMD Endowed Chair of
Electrical and Computer Engineering
at the University of Illinois at Urbana-
Champaign. His research interests
include architecture and compilation for parallel-
computing systems. He has a BS in electrical
engineering from National Taiwan University, and
a PhD in computer science from the University of
California, Berkeley. He is a Fellow of both the IEEE
and the ACM.
Kurt Keutzer is a professor of
electrical engineering and computer
science at the University of California,
Berkeley and a principal investigator
in UC Berkeley’s Universal Parallel
Computing Research Center. His research focuses
on the design and programming of ICs. He has a BS
in mathematics from Maharishi International University, and an MS a PhD in computer science from
Indiana University, Bloomington. He is a Fellow of the
IEEE and a member of the ACM.
Timothy G. Mattson is a principal
engineer in the Applications Research
Laboratory at Intel. He research inter-
ests focus on performance modeling
for future multicore microprocessors
and how different programming models map onto
these systems. He has a BS in chemistry from the
University of California, Riverside; an MS in chemistry
from the university of California, Santa Cruz; and a PhD in theoretical chemistry from the University of
California, Santa Cruz. He is a member of the
American Association for the Advancement of Sci-
ence (AAAS).
https://ieeexplore.ieee.org/document/4584454
STATISTICAL ANALYSIS FOR PERFORMANCE COMPARISONijseajournal
Performance responsiveness and scalability is a make-or-break quality for software. Nearly everyone runs into performance problems at one time or another. This paper discusses about performance issues faced during Pre Examination Process Automation System (PEPAS) implemented in java technology. The challenges faced during the life cycle of the project and the mitigation actions performed. It compares 3 java technologies and shows how improvements are made through statistical analysis in response time of the application. The paper concludes with result analysis.
Evaluation of morden computer & system attributes in ACAPankaj Kumar Jain
Elements of Modern Computers, Architectural
Evolution in computer architecture ,System Attributes to Performance,Clock Rate and CPI,MIPS Rate,Throughput Rate,Implicit Parallelism,Explicit Parallelism, State of computing,
Improved Strategy for Distributed Processing and Network Application Developm...Editor IJCATR
The complexity of software development abstraction and the new development in multi-core computers have shifted the burden of distributed software performance from network and chip designers to software architectures and developers. We need to look at software development strategies that will integrate parallelization of code, concurrency factors, multithreading, distributed resources allocation and distributed processing. In this paper, a new software development strategy that integrates these factors is further experimented on parallelism. The strategy is multidimensional aligns distributed conceptualization along a path. This development strategy mandates application developers to reason along usability, simplicity, resource distribution, parallelization of code where necessary, processing time and cost factors realignment as well as security and concurrency issues in a balanced path from the originating point of the network application to its retirement.
Improved Strategy for Distributed Processing and Network Application DevelopmentEditor IJCATR
The complexity of software development abstraction and the new development in multi-core computers have shifted the
burden of distributed software performance from network and chip designers to software architectures and developers. We need to
look at software development strategies that will integrate parallelization of code, concurrency factors, multithreading, distributed
resources allocation and distributed processing. In this paper, a new software development strategy that integrates these factors is
further experimented on parallelism. The strategy is multidimensional aligns distributed conceptualization along a path. This
development strategy mandates application developers to reason along usability, simplicity, resource distribution, parallelization of
code where necessary, processing time and cost factors realignment as well as security and concurrency issues in a balanced path from
the originating point of the network application to its retirement.
CIS 512 discussion post responses.CPUs and Programming Pleas.docxmccormicknadine86
CIS 512 discussion post responses.
"CPUs and Programming" Please respond to the following:
· From the first e-Activity, identify the following CPUs: 1) the CPU that resides on a computer that you own or a computer that you would consider purchasing, and 2) the CPU of one (1) other computer. Compare the instruction sets and clock rates of each CPU. Determine which CPU of the two is faster and why. Conclude whether or not the clock rate by itself makes the CPU faster. Provide a rationale for your response.
· From the second e-Activity, examine two (2) benefits of using planning techniques—such as writing program flowcharts, pseudocode, or other available programming planning technique—to devise and design computer programs. Evaluate the effectiveness of your preferred program planning technique, based on its success in the real world. Provide one (1) example of a real-life application of your preferred program planning technique to support your response.
MB’s post states the following:Top of Form
"CPUs and Programming" Please respond to the following:
· From the first e-Activity, identify the following CPUs: 1) the CPU that resides on a computer that you own or a computer that you would consider purchasing, and 2) the CPU of one (1) other computer. Compare the instruction sets and clock rates of each CPU. Determine which CPU of the two is faster and why. Conclude whether or not the clock rate by itself makes the CPU faster. Provide a rationale for your response.
The current CPU that resides in my computer is an Intel(R) Core(TM) i5-2540M CPU @ 2.60GHz, 2MB cache, 4 cores, and 8 threads
In comparison with my CPU to an Intel® Core™ i9-10980XE Extreme Edition Processor (24.75MB Cache, Up to 4.60 GHz), 24.75 MB Cache, 18 Cores, 36 Threads, 4.60GHz Max Turbo Frequency, XE – Extreme performance and mega-tasking, unlocked, I found the Intel i9 CPU clock speed is almost twice the speed of the CPU in my computer with a speed of 4.60GHz and cache up to 24.75 MB. This means the Intel core i9 stores more accessible data up to 24.75 MB of data on the CPU for processing and availability which is a huge amount of space for storing data directly on a CPU. The 18 cores also allows for multiple simultaneous parallel data processing through (Fetch, Decode and Execute) which increase the speed of processing data.
· From the second e-Activity, examine two (2) benefits of using planning techniques—such as writing program flowcharts, pseudocode, or other available programming planning technique—to devise and design computer programs. Evaluate the effectiveness of your preferred program planning technique, based on its success in the real world. Provide one (1) example of a real-life application of your preferred program planning technique to support your response.
Two benefits of using planning techniques to design a computer program are, to establish a frame work Architecture to provide a road map for implementation. Another benefit for planning is to provide c ...
A Comparative Study of Forward and Reverse Engineeringijsrd.com
With the software development at its boom compared to 20 years in the past, software developed in the past may or may not have a well-supported documentation during the software evolution. This may increase the specification gap between the document and the legacy code to make further evolutions and updates. Understanding the legacy code of the underlying decisions made during development is the prime motto, which is very well supported by Reverse Engineering. In this paper, we compare the Transformational Forward engineering, where a stepwise abstraction is obtained with the Transformational Reverse Methodology. While the forward transformation process produces overlap of the decisions, performance is affected. Hence, the use of transformational method of Reverse Engineering which is a backwards Forward Engineering process is suitable. Besides the design recognition obtained is a domain knowledge which can be used in future by the forward engineers.
Evaluation of morden computer & system attributes in ACAPankaj Kumar Jain
Elements of Modern Computers, Architectural
Evolution in computer architecture ,System Attributes to Performance,Clock Rate and CPI,MIPS Rate,Throughput Rate,Implicit Parallelism,Explicit Parallelism, State of computing,
Improved Strategy for Distributed Processing and Network Application Developm...Editor IJCATR
The complexity of software development abstraction and the new development in multi-core computers have shifted the burden of distributed software performance from network and chip designers to software architectures and developers. We need to look at software development strategies that will integrate parallelization of code, concurrency factors, multithreading, distributed resources allocation and distributed processing. In this paper, a new software development strategy that integrates these factors is further experimented on parallelism. The strategy is multidimensional aligns distributed conceptualization along a path. This development strategy mandates application developers to reason along usability, simplicity, resource distribution, parallelization of code where necessary, processing time and cost factors realignment as well as security and concurrency issues in a balanced path from the originating point of the network application to its retirement.
Improved Strategy for Distributed Processing and Network Application DevelopmentEditor IJCATR
The complexity of software development abstraction and the new development in multi-core computers have shifted the
burden of distributed software performance from network and chip designers to software architectures and developers. We need to
look at software development strategies that will integrate parallelization of code, concurrency factors, multithreading, distributed
resources allocation and distributed processing. In this paper, a new software development strategy that integrates these factors is
further experimented on parallelism. The strategy is multidimensional aligns distributed conceptualization along a path. This
development strategy mandates application developers to reason along usability, simplicity, resource distribution, parallelization of
code where necessary, processing time and cost factors realignment as well as security and concurrency issues in a balanced path from
the originating point of the network application to its retirement.
CIS 512 discussion post responses.CPUs and Programming Pleas.docxmccormicknadine86
CIS 512 discussion post responses.
"CPUs and Programming" Please respond to the following:
· From the first e-Activity, identify the following CPUs: 1) the CPU that resides on a computer that you own or a computer that you would consider purchasing, and 2) the CPU of one (1) other computer. Compare the instruction sets and clock rates of each CPU. Determine which CPU of the two is faster and why. Conclude whether or not the clock rate by itself makes the CPU faster. Provide a rationale for your response.
· From the second e-Activity, examine two (2) benefits of using planning techniques—such as writing program flowcharts, pseudocode, or other available programming planning technique—to devise and design computer programs. Evaluate the effectiveness of your preferred program planning technique, based on its success in the real world. Provide one (1) example of a real-life application of your preferred program planning technique to support your response.
MB’s post states the following:Top of Form
"CPUs and Programming" Please respond to the following:
· From the first e-Activity, identify the following CPUs: 1) the CPU that resides on a computer that you own or a computer that you would consider purchasing, and 2) the CPU of one (1) other computer. Compare the instruction sets and clock rates of each CPU. Determine which CPU of the two is faster and why. Conclude whether or not the clock rate by itself makes the CPU faster. Provide a rationale for your response.
The current CPU that resides in my computer is an Intel(R) Core(TM) i5-2540M CPU @ 2.60GHz, 2MB cache, 4 cores, and 8 threads
In comparison with my CPU to an Intel® Core™ i9-10980XE Extreme Edition Processor (24.75MB Cache, Up to 4.60 GHz), 24.75 MB Cache, 18 Cores, 36 Threads, 4.60GHz Max Turbo Frequency, XE – Extreme performance and mega-tasking, unlocked, I found the Intel i9 CPU clock speed is almost twice the speed of the CPU in my computer with a speed of 4.60GHz and cache up to 24.75 MB. This means the Intel core i9 stores more accessible data up to 24.75 MB of data on the CPU for processing and availability which is a huge amount of space for storing data directly on a CPU. The 18 cores also allows for multiple simultaneous parallel data processing through (Fetch, Decode and Execute) which increase the speed of processing data.
· From the second e-Activity, examine two (2) benefits of using planning techniques—such as writing program flowcharts, pseudocode, or other available programming planning technique—to devise and design computer programs. Evaluate the effectiveness of your preferred program planning technique, based on its success in the real world. Provide one (1) example of a real-life application of your preferred program planning technique to support your response.
Two benefits of using planning techniques to design a computer program are, to establish a frame work Architecture to provide a road map for implementation. Another benefit for planning is to provide c ...
A Comparative Study of Forward and Reverse Engineeringijsrd.com
With the software development at its boom compared to 20 years in the past, software developed in the past may or may not have a well-supported documentation during the software evolution. This may increase the specification gap between the document and the legacy code to make further evolutions and updates. Understanding the legacy code of the underlying decisions made during development is the prime motto, which is very well supported by Reverse Engineering. In this paper, we compare the Transformational Forward engineering, where a stepwise abstraction is obtained with the Transformational Reverse Methodology. While the forward transformation process produces overlap of the decisions, performance is affected. Hence, the use of transformational method of Reverse Engineering which is a backwards Forward Engineering process is suitable. Besides the design recognition obtained is a domain knowledge which can be used in future by the forward engineers.
Is Multicore Hardware For General-Purpose Parallel Processing Broken? : NotesSubhajit Sahu
Highlighted notes of article while studying Concurrent Data Structures, CSE:
Is Multicore Hardware For General-Purpose Parallel Processing Broken?
By Uzi Vishkin
Communications of the ACM, April 2014, Vol. 57 No. 4, Pages 35-39
10.1145/2580945
There are many ways to ruin a performance testing project, there is just a handful of ways to do it right. This publication analyses the most widespread performance testing blunders. It is impossible in one article to expose all the varieties of testing wrongdoings; as such, this publication is definitely an open-ended.
A Generic Open Source Framework for Auto Generation of Data Manipulation Comm...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Dairy management system project report..pdfKamal Acharya
ASP.NET is the next version of Active Server Pages (ASP); it is a unified Web development platform that provides the services necessary for developers to build enterprise-class Web applications. While ASP.NET is largely syntax compatible, it also provides a new programming model and infrastructure for more secure, scalable, and stable applications. ASP.NET is a compiled, NET-based environment, we can author applications in any .NET compatible language, including Visual Basic .NET, C#, and JScript .NET. Additionally, the entire .NET Framework is available to any ASP.NET application. Developers can easily access the benefits of these technologies, which include the managed common language runtime environment (CLR), type safety, inheritance, and so on. ASP.NET has been designed to work seamlessly with WYSIWYG HTML editors and other programming tools, including Microsoft Visual Studio .NET. Not only does this make Web development easier, but it also provides all the benefits that these tools have to offer, including a GUI that developers can use to drop server controls onto a Web page and fully integrated debugging support.
DhkGive Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given Give Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given retGive Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given Give Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given Give Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given Give Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given Give Me the proper retort for Use full
It can be very essential for all students
Give Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given Give Me the proper retort for Use full
It can be very essential for all students
Give Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given Give Me the proper retort for Use full
It can be very essential for all students
Give Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given Give Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given Give Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given retGive Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given Give Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given Give Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given Give Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given Give Me the proper retort for Use full
It can be very essential for all students
Give Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given Give Me the proper retort for Use full
It can be very essential for all students
Give Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given Give Me the proper retort for Use full
It can be very essential for all students
Give Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given Give Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given Give Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given retGive Me the proper retort for Use full
It can be very essential for all students
Its honorable request for given Give Me the proper retort for Use full
It can be very essential for all st
1. H
H P C X p e r f A p p l i c a t i o n A n a l y z e r
Pr o d u c t Brie f
E x e m p l a r
P r o g r a m m i n g
E n v i r o n m e n t
Analyzes parallel applications
Supports multiple parallel models
Interprets results visually
•
•
•
High-performance computer architectures are becoming more and more
sophisticated. Parallel processors, multiple levels of memory and complex I/O
configurations offer enormous potential for performance increases.
Effectively tapping into this potential power with your application software
offers tremendous benefits. CXperf, a parallel application analysis tool, helps application developers
deliver the power of the Exemplar family of parallel servers. CXperf clearly and dramatically helps improve the perfor-
mance of your complex real-world applications.
2. Why Application Performance
Analysis?
There are several types of perfor-
mance analyses, including hardware
simulation, system monitoring, appli-
cation monitoring and application
performance analysis. Application
performance analysis focuses on
improving the efficiency of your code
and reducing its total time to solution.
Application performance analysis
involves nearly every facet of a
system, including underlying hard-
ware architecture, operating system
and development tools. Analyzing the
behavior of applications therefore
requires well designed professionally
implemented tools.
Need for Speed
To compete in the global marketplace,
a product’s time-to-market and its
time-to-solution are paramount to
success. In scientific and engineering
computing, today’s users require the
ability to complete complex engineer-
ing and scientific development tasks
as quickly as possible.
processor speeds increase, and as the
complexity of memory architectures
increases, memory latency relative to
processor speeds also increases.
Managing the relative increased
memory latency continues to be a
significant challenge. These powerful
advanced systems promise dramatical-
ly improved performance. The chal-
lenge is to gain access to this new
power through applications software.
Larger Applications
As applications increase in size, they
require more memory and more
processors to complete in a timely
fashion. Mapping applications onto
multiprocessor systems with multiple
levels of memory is difficult, even with
the support of parallelizing compilers.
Complex Architectures
Computing architectures evolve to
meet customer demands for increased
performance and capability. As
Source
Program
Module
Parallel
Application
Editor
F90, F77,
C++, C
Compilers
Linker
Debugger
CXperf
Performance
Analysis
HP MPI
HP MLIB
Pthreads
Exemplar Programming Environment
Configure
Instrumentation
Execute
Analyze
CXperf Profiling Methodology
Compile application
for analysis
3. Performance tuning often involves
optimizing the use of this memory by
spreading the load across processors.
What is CXperf?
CXperf is an application analyzer,
designed to help developers identify
ways to improve the time to solution
of applications. CXperf gathers a large
variety of measurements of the perfor-
mance of an application. To reduce the
amount of data generated, CXperf uses
the reductionist method of analysis.
The reductionist method summarizes
statistics for each region of the appli-
cation you want to measure while your
program runs.
CXperf is integrated with HP compil-
ers, including Fortran 90, Fortran 77,
ANSI C++ and ANSI C. CXperf sup-
ports profiling of routines and loops,
including tracking compiler optimiza-
tions. CXperf is integrated with hard-
ware and the operating system to
support wall clock timing, CPU timing,
memory access counts and memory
latency timing. CXperf also supports
profiling of shared memory applica-
tions, including compiler generated
parallel code, Pthreads and user-speci-
fied parallel directives. CXperf can
profile multi-process applications and
message-passing parallel programming
models, such as HP MPI Message
Passing Interface software.
Description
Profiling an application is an iterative
process. CXperf allows a user to pro-
file an application, make changes and
re-profile the same application. CXperf
supports this process with an intuitive,
easy to use graphical user interface as
well as a command line interface to
easily modify and rerun tests.
To begin the process, the user com-
piles the application to profile, selects
the parts of the application to profile,
and then selects the metrics to collect
regarding those parts of the applica-
tion. CXperf then instruments the
application.
After the instrumentation step, the
user runs the application. CXperf
generates a program data file during
execution of the application.
In the analysis step, the developer
uses CXperf tools to graphically dis-
play the behavior of the application as
it occurred during the execution step.
Call graphs, summary profiles and
detailed parallel performance profiles
are all readily displayed. CXperf also
includes a number of textual reports
to describe the overall behavior of the
application.