This document describes a course on superscalar processor design taught at Carnegie Mellon University since 1995. The course objectives are to teach modern processor design skills at the microarchitecture level, cover techniques for exploiting instruction-level parallelism to achieve high performance, and impart insights and experience in designing contemporary high-performance microprocessors. The course also includes a project to design a future-generation superscalar microprocessor. The document then provides a link to solution manuals for exercises in the textbook "Modern Processor Design" by John Paul Shen and Mikko H. Lipasti.
Microarchitecture of a coarse grain out-of-order superscalar processorecway
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Hybrid Model Based Testing Tool Architecture for Exascale Computing SystemCSCJournals
Exascale computing refers to a computing system which is capable to at least one exaflop in next couple of years. Many new programming models, architectures and algorithms have been introduced to attain the objective for exascale computing system. The primary objective is to enhance the system performance. In modern/super computers, GPU is being used to attain the high computing performance. However, it’s the objective of proposed technologies and programming models is almost same to make the GPU more powerful. But these technologies are still facing the number of challenges including parallelism, scale and complexity and also many more that must be fixed to achieve make computing system more powerful and efficient. In this paper, we have present a testing tool architecture for a parallel programming approach using two programming models as CUDA and OpenMP. Both CUDA and OpenMP could be used to program shared memory and GPU cores. The object of this architecture is to identify the static errors in the program that occurred during writing the code and cause absence of parallelism. Our architecture enforces the developers to write the feasible code through we can avoid from the essential errors in the program and run successfully.
Microarchitecture of a coarse grain out-of-order superscalar processorecway
Final Year IEEE Projects, Final Year Projects, Academic Final Year Projects, Academic Final Year IEEE Projects, Academic Final Year IEEE Projects 2013, Academic Final Year IEEE Projects 2014, IEEE JAVA, .NET Projects, 2013 IEEE JAVA, .NET Projects, 2013 IEEE JAVA, .NET Projects in Chennai, 2013 IEEE JAVA, .NET Projects in Trichy, 2013 IEEE JAVA, .NET Projects in Karur, 2013 IEEE JAVA, .NET Projects in Erode, 2013 IEEE JAVA, .NET Projects in Madurai, 2013 IEEE JAVA, .NET Projects in Salem, 2013 IEEE JAVA, .NET Projects in Coimbatore, 2013 IEEE JAVA, .NET Projects in Tirupur, 2013 IEEE JAVA, .NET Projects in Bangalore, 2013 IEEE JAVA, .NET Projects in Hydrabad, 2013 IEEE JAVA, .NET Projects in Kerala, 2013 IEEE JAVA, .NET Projects in Namakkal, IEEE JAVA, .NET Image Processing, IEEE JAVA, .NET Face Recognition, IEEE JAVA, .NET Face Detection, IEEE JAVA, .NET Brain Tumour, IEEE JAVA, .NET Iris Recognition, IEEE JAVA, .NET Image Segmentation, Final Year JAVA, .NET Projects in Pondichery, Final Year JAVA, .NET Projects in Tamilnadu, Final Year JAVA, .NET Projects in Chennai, Final Year JAVA, .NET Projects in Trichy, Final Year JAVA, .NET Projects in Erode, Final Year JAVA, .NET Projects in Karur, Final Year JAVA, .NET Projects in Coimbatore, Final Year JAVA, .NET Projects in Tirunelveli, Final Year JAVA, .NET Projects in Madurai, Final Year JAVA, .NET Projects in Salem, Final Year JAVA, .NET Projects in Tirupur, Final Year JAVA, .NET Projects in Namakkal, Final Year JAVA, .NET Projects in Tanjore, Final Year JAVA, .NET Projects in Coimbatore, Final Year JAVA, .NET Projects in Bangalore, Final Year JAVA, .NET Projects in Hydrabad, Final Year JAVA, .NET Projects in Kerala, Final Year JAVA, .NET IEEE Projects in Pondichery, Final Year JAVA, .NET IEEE Projects in Tamilnadu, Final Year JAVA, .NET IEEE Projects in Chennai, Final Year JAVA, .NET IEEE Projects in Trichy, Final Year JAVA, .NET IEEE Projects in Erode, Final Year JAVA, .NET IEEE Projects in Karur, Final Year JAVA, .NET IEEE Projects in Coimbatore, Final Year JAVA, .NET IEEE Projects in Tirunelveli, Final Year JAVA, .NET IEEE Projects in Madurai, Final Year JAVA, .NET IEEE Projects in Salem, Final Year JAVA, .NET IEEE Projects in Tirupur, Final Year JAVA, .NET IEEE Projects in Namakkal, Final Year JAVA, .NET IEEE Projects in Tanjore, Final Year JAVA, .NET IEEE Projects in Coimbatore, Final Year JAVA, .NET IEEE Projects in Bangalore, Final Year JAVA, .NET IEEE Projects in Hydrabad, Final Year JAVA, .NET IEEE Projects in Kerala, Final Year IEEE MATLAB Projects, Final Year Projects, Academic Final Year Projects, Academic Final Year IEEE MATLAB Projects, Academic Final Year IEEE MATLAB Projects 2013, Academic Final Year IEEE MATLAB Projects 2014, IEEE MATLAB Projects, 2013 IEEE MATLAB Projects, 2013 IEEE MATLAB Projects in Chennai, 2013 IEEE MATLAB Projects in Trichy, 2013 IEEE MATLAB Projects in Karur, 2013 IEEE MATLAB Projects in Erode, 2013 IEEE MATLAB Projects in Madurai, 2013 IEEE MATLAB
Hybrid Model Based Testing Tool Architecture for Exascale Computing SystemCSCJournals
Exascale computing refers to a computing system which is capable to at least one exaflop in next couple of years. Many new programming models, architectures and algorithms have been introduced to attain the objective for exascale computing system. The primary objective is to enhance the system performance. In modern/super computers, GPU is being used to attain the high computing performance. However, it’s the objective of proposed technologies and programming models is almost same to make the GPU more powerful. But these technologies are still facing the number of challenges including parallelism, scale and complexity and also many more that must be fixed to achieve make computing system more powerful and efficient. In this paper, we have present a testing tool architecture for a parallel programming approach using two programming models as CUDA and OpenMP. Both CUDA and OpenMP could be used to program shared memory and GPU cores. The object of this architecture is to identify the static errors in the program that occurred during writing the code and cause absence of parallelism. Our architecture enforces the developers to write the feasible code through we can avoid from the essential errors in the program and run successfully.
Concurrent Matrix Multiplication on Multi-core ProcessorsCSCJournals
With the advent of multi-cores every processor has built-in parallel computational power and that can only be fully utilized only if the program in execution is written accordingly. This study is a part of an on-going research for designing of a new parallel programming model for multi-core architectures. In this paper we have presented a simple, highly efficient and scalable implementation of a common matrix multiplication algorithm using a newly developed parallel programming model SPC3 PM for general purpose multi-core processors. From our study it is found that matrix multiplication done concurrently on multi-cores using SPC3 PM requires much less execution time than that required using the present standard parallel programming environments like OpenMP. Our approach also shows scalability, better and uniform speedup and better utilization of available cores than that the algorithm written using standard OpenMP or similar parallel programming tools. We have tested our approach for up to 24 cores with different matrices size varying from 100 x 100 to 10000 x 10000 elements. And for all these tests our proposed approach has shown much improved performance and scalability
The following resources come from the 2009/10 BEng in Electrical Engineering (course number 2ELE0066) from the University of Hertfordshire. All the mini projects are designed as level two modules of the undergraduate programmes.
The objectives of this module are to demonstrate within an industrial environment:
• To use Matlab® (Simulink®)
• To implement an appropriate analogue computer for modelling dynamic systems.
A DC motor model, in specific prototyping stages, is more appropriate to use than the actual DC motor. This project aimed to design and implement a DC motor model by using a simulation package (CAD) such as Matlab and implement the equivalent electronic hardware platform.
Bt0068 computer organization and architecturesmumbahelp
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
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or
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How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...inside-BigData.com
In this deck from the Stanford HPC Conference, DK Panda from Ohio State University presents: How to Achieve High-Performance, Scalable and Distributed DNN Training on Modern HPC Systems?
"This talk will start with an overview of challenges being faced by the AI community to achieve high-performance, scalable and distributed DNN training on Modern HPC systems with both scale-up and scale-out strategies. After that, the talk will focus on a range of solutions being carried out in my group to address these challenges. The solutions will include: 1) MPI-driven Deep Learning, 2) Co-designing Deep Learning Stacks with High-Performance MPI, 3) Out-of- core DNN training, and 4) Hybrid (Data and Model) parallelism. Case studies to accelerate DNN training with popular frameworks like TensorFlow, PyTorch, MXNet and Caffe on modern HPC systems will be presented."
Watch the video: https://youtu.be/LeUNoKZVuwQ
Learn more: http://web.cse.ohio-state.edu/~panda.2/
and
http://www.hpcadvisorycouncil.com/events/2020/stanford-workshop/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Hardback solution to accelerate multimedia computation through mgp in cmpeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Concurrent Matrix Multiplication on Multi-core ProcessorsCSCJournals
With the advent of multi-cores every processor has built-in parallel computational power and that can only be fully utilized only if the program in execution is written accordingly. This study is a part of an on-going research for designing of a new parallel programming model for multi-core architectures. In this paper we have presented a simple, highly efficient and scalable implementation of a common matrix multiplication algorithm using a newly developed parallel programming model SPC3 PM for general purpose multi-core processors. From our study it is found that matrix multiplication done concurrently on multi-cores using SPC3 PM requires much less execution time than that required using the present standard parallel programming environments like OpenMP. Our approach also shows scalability, better and uniform speedup and better utilization of available cores than that the algorithm written using standard OpenMP or similar parallel programming tools. We have tested our approach for up to 24 cores with different matrices size varying from 100 x 100 to 10000 x 10000 elements. And for all these tests our proposed approach has shown much improved performance and scalability
The following resources come from the 2009/10 BEng in Electrical Engineering (course number 2ELE0066) from the University of Hertfordshire. All the mini projects are designed as level two modules of the undergraduate programmes.
The objectives of this module are to demonstrate within an industrial environment:
• To use Matlab® (Simulink®)
• To implement an appropriate analogue computer for modelling dynamic systems.
A DC motor model, in specific prototyping stages, is more appropriate to use than the actual DC motor. This project aimed to design and implement a DC motor model by using a simulation package (CAD) such as Matlab and implement the equivalent electronic hardware platform.
Bt0068 computer organization and architecturesmumbahelp
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
or
Call us at : 08263069601
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...inside-BigData.com
In this deck from the Stanford HPC Conference, DK Panda from Ohio State University presents: How to Achieve High-Performance, Scalable and Distributed DNN Training on Modern HPC Systems?
"This talk will start with an overview of challenges being faced by the AI community to achieve high-performance, scalable and distributed DNN training on Modern HPC systems with both scale-up and scale-out strategies. After that, the talk will focus on a range of solutions being carried out in my group to address these challenges. The solutions will include: 1) MPI-driven Deep Learning, 2) Co-designing Deep Learning Stacks with High-Performance MPI, 3) Out-of- core DNN training, and 4) Hybrid (Data and Model) parallelism. Case studies to accelerate DNN training with popular frameworks like TensorFlow, PyTorch, MXNet and Caffe on modern HPC systems will be presented."
Watch the video: https://youtu.be/LeUNoKZVuwQ
Learn more: http://web.cse.ohio-state.edu/~panda.2/
and
http://www.hpcadvisorycouncil.com/events/2020/stanford-workshop/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Hardback solution to accelerate multimedia computation through mgp in cmpeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Solution manual for modern processor design by john paul shen and mikko h. lipasti
1. Solution Manual for Modern Processor Design by John Paul
Shen and Mikko H. Lipasti
This book emerged from the course Superscalar Processor Design, which has been taught at
Carnegie Mellon University since 1995. Superscalar Processor Design is a mezzanine course targeting
seniors and first-year graduate students. Quite a few of the more aggressive juniors have taken the
course in the spring semester of their junior year. The prerequisite to this course is the
Introduction to Computer Architecture course. The objectives for the Superscalar Processor Design
course include: (1) to teach modem processor design skills at the microarchitecture level of
abstraction; (2) to cover current microarchitecture techniques for achieving high performance
via the exploitation of instruction-level parallelism (ILP); and (3) to impart insights and hands-on
experience for the effective design of contemporary high-performance microprocessors for mobile,
desktop, and server markets. In addition to covering the contents of this book, the course contains
a project component that involves the microarchitectural design of a future-generation superscalar
microprocessor.
Here, in next successive posts, I am going to post solutions for the same Text-book (Modern
Processor Design by John Paul Shen and Mikko H. Lipasti). If you find any difficulty or wants to
suggest anything, feel free to comment...:)
Link:
http://targetiesnow.blogspot.in/p/solution-manual-for-modern-
processor.html
Modern Processor Design by John Paul Shen and Mikko H.
Lipasti : Exercise 1.6 and 1.7 Solution
2. Q.1.6: A program's run time is determined by the product of instructions per program, cycles
per instruction, and clock frequency. Assume the following instruction mix for aMlPS-like RISC
instruction set: 15% stores, 25% loads, 15% branches, and 35% integer arithmetic, 5% integer shift,
and 5% integer multiply. Given that load instructions require two cycles, branches require four
cycles, integer ALU instructions require one cycle, and integer multiplies require ten cycles,
compute the overall CPI.
Q.1.7: Given the parameters of Problem 6, consider a strength-reducing optimization that
converts multiplies by a compile-time constant into a sequence of shifts and adds. For this
instruction mix, 50% of the multiplies can be converted to shift-add sequences with an average
length of three instructions. Assuming a fixed frequency, compute the change in instructions per
program, cycles per instruction, and overall program speedup.
Solution:http://targetiesnow.blogspot.in/2013/11/modern-processor-design-byjohn-paul_9765.html#links