SlideShare a Scribd company logo
๏ƒ˜ Here we present methods in teaching advanced
computer architecture courses. These methods
include presenting fundamental computer
architecture issues using e-learning; employing
visual aids to teach fundamentals concepts like
Caches, pipelining and scheduling.
2
๏ƒ˜ Advance Computer Architecture usually combines software and
hardware approaches that increase the performance of
microprocessor design.
๏ƒ˜ Main concepts in this courses includes measuring performance,
Instruction Set Design, Memory Hierarchy and Caches, Pipelining
and its Hazards, Instruction Level Parallelism, I/O storage, and
latest contemporary computer architecture issues.
๏ƒ˜ By using these concepts this course also presents the quantitative
approaches to measure the feasibility.
3
๏ƒ˜ These approaches also measure the performance emphasizing on
the differences between hardware and software approaches.
๏ƒ˜ There are several books available on Computer Architecture
concepts.
๏ƒ˜ Hennessy and Pattersonโ€™s are the one who gives a comprehensive
documentation on most of computer architecture topics.
4
Concepts for e-learning are
๏‚ž Cache Associativity
๏‚ž Superscalar microprocessors.
๏‚ž Dynamic scheduling algorithms.
5
๏‚ž Definition
๏ƒ˜ It is the easy control of direct mapping cache and a fully associative
cache.
๏ƒ˜ Each cache location can have more than one pair of tag and data
item that resides at same location in cache memory.
๏ƒ˜ If one cache location is holding two pair of tag and data item that is
called two-way set associative cache.
6
๏ƒ˜ A 2-way set associative cache
having 8 lines will have 4 sets
and each set has two lines.
๏ƒ˜ Figures show the set
associativity explain
๏ƒ˜ This approach presents the
cache to be split into number of
sets and each set has equal
number of lines.
7
Visual aid made the concepts easy to understand and we
can easily explained our point by adding visual aids and
graphics
๏‚ž Pipelining and its hazards
๏‚ž Superscalar design
๏‚ž Instruction Level Parallelism
๏‚ž Dynamic Scheduling.
8
๏‚ž Pipelining
๏ƒ˜ A Pipelining is a series of stages, where some work is done at each
stage in parallel.
๏ƒ˜ The stages are connected one to the next to form a pipe
instructions enter at one end, progress through the stages, and exit
at the other end.
๏‚ž pipelining hazards
๏ƒ˜ Prevent the next instruction in the instruction stream from
being executing during its designated clock cycle.
๏ƒ˜ Hazards reduce the performance from the ideal speedup
gained by pipelining
9
๏ƒ˜ DLX is simple pipelining
architecture for CPU.
๏ƒ˜ This is the seven clock cycle
that is required to execute the
instruction
K+(n-1) cycle
๏ƒ˜ The pipeline could be also
shown in terms of cycles,
meaning display the events at
each clock cycle
DLX pipeline Starting stage
DLX pipeline 2nd instruction
10
Pipelining hazards
๏ƒ˜ For pipeline hazards, the visual aid could show bubbles
inserted in the pipeline figure show bubbles and data
forwarded using arrows.
11
๏ƒ˜ The concept of superscalars can also be explained with the
visual aids.
๏ƒ˜ This figure show a 2-way issues for a DLX superscalar
machine
๏ƒ˜ where one pipeline is assigned for integer and the other for
floating-point operations. Note that floating-point operation
takes 3 cycles to execute.
12
๏‚ž Definition
๏ƒ˜ Instruction level parallelism (ILP) is a measure of how
many of the instructions in a computer program can
be executed simultaneously.
๏ƒ˜ In Dynamic scheduling hardware determines which
instructions to execute,
๏ƒ˜ ILP and Dynamic Scheduling is made easy by using
visual aid.
13
Tomasulaโ€™s algorithm
๏ƒ˜ It is a computer architecture hardware algorithm for
dynamic scheduling of instructions.
๏ƒ˜ It allows out-of-order execution and enables more efficient
use of multiple execution units.
๏ƒ˜ At cycle =0 five instructions
scheduled
๏ƒ˜ Student re-write each cycle
result.
๏ƒ˜ This idea involve the
student in the process of
learning and solving the
problem.
14
๏ƒ˜ Advanced Computer Architecture is
rich with new topics that are in the
research stage.
๏ƒ˜ The student must be aware of these
topics before completing any advanced
computer architecture course.
15
๏ƒ˜ Advanced Computer Architecture is rich with
advanced topics. The most advanced way of
learning is through visual aids and e-learning.
Future trends in teaching Computer Architecture
may lead to e-learning at a distance.
16
๏ƒ˜ http://web.cs.iastate.edu/~prabhu/Tutorial/PIPELINE/ha
zards.html
๏ƒ˜ https://en.wikipedia.org/wiki/Tomasulo_algorithm
๏ƒ˜ https://kb.iu.edu/d/aett
๏ƒ˜ http://www.pcguide.com/ref/mbsys/cache/funcMapping-
c.html
17

More Related Content

What's hot

Lecture 3
Lecture 3Lecture 3
Lecture 3
Mr SMAK
ย 
AI On the Edge: Model Compression
AI On the Edge: Model CompressionAI On the Edge: Model Compression
AI On the Edge: Model Compression
Apache MXNet
ย 
Detailed Simulation of Large-Scale Wireless Networks
Detailed Simulation of Large-Scale Wireless NetworksDetailed Simulation of Large-Scale Wireless Networks
Detailed Simulation of Large-Scale Wireless Networks
Gabriele D'Angelo
ย 
Using Multi-layered Feed-forward Neural Network (MLFNN) Architecture as Bidir...
Using Multi-layered Feed-forward Neural Network (MLFNN) Architecture as Bidir...Using Multi-layered Feed-forward Neural Network (MLFNN) Architecture as Bidir...
Using Multi-layered Feed-forward Neural Network (MLFNN) Architecture as Bidir...
IOSR Journals
ย 
Introduction to neural networks and Keras
Introduction to neural networks and KerasIntroduction to neural networks and Keras
Introduction to neural networks and Keras
Jie He
ย 
Bt0068 computer organization and architecture
Bt0068   computer organization and architectureBt0068   computer organization and architecture
Bt0068 computer organization and architecture
smumbahelp
ย 
3D-DRESD DReAMS
3D-DRESD DReAMS3D-DRESD DReAMS
3D-DRESD DReAMS
Marco Santambrogio
ย 
Lecture 4 principles of parallel algorithm design updated
Lecture 4   principles of parallel algorithm design updatedLecture 4   principles of parallel algorithm design updated
Lecture 4 principles of parallel algorithm design updated
Vajira Thambawita
ย 
Transfer learning with LTANN-MEM & NSA for solving multi-objective symbolic r...
Transfer learning with LTANN-MEM & NSA for solving multi-objective symbolic r...Transfer learning with LTANN-MEM & NSA for solving multi-objective symbolic r...
Transfer learning with LTANN-MEM & NSA for solving multi-objective symbolic r...
Amr Kamel Deklel
ย 
UIC Panella Thesis
UIC Panella ThesisUIC Panella Thesis
UIC Panella Thesis
Marco Santambrogio
ย 
Keras on tensorflow in R & Python
Keras on tensorflow in R & PythonKeras on tensorflow in R & Python
Keras on tensorflow in R & Python
Longhow Lam
ย 
A tutorial on CGAL polyhedron for subdivision algorithms
A tutorial on CGAL polyhedron for subdivision algorithmsA tutorial on CGAL polyhedron for subdivision algorithms
A tutorial on CGAL polyhedron for subdivision algorithms
Radu Ursu
ย 
2017 (albawi-alkabi)image-net classification with deep convolutional neural n...
2017 (albawi-alkabi)image-net classification with deep convolutional neural n...2017 (albawi-alkabi)image-net classification with deep convolutional neural n...
2017 (albawi-alkabi)image-net classification with deep convolutional neural n...
ali hassan
ย 
Convolutional neural network from VGG to DenseNet
Convolutional neural network from VGG to DenseNetConvolutional neural network from VGG to DenseNet
Convolutional neural network from VGG to DenseNet
SungminYou
ย 
Enhancing the matrix transpose operation using intel avx instruction set exte...
Enhancing the matrix transpose operation using intel avx instruction set exte...Enhancing the matrix transpose operation using intel avx instruction set exte...
Enhancing the matrix transpose operation using intel avx instruction set exte...
ijcsit
ย 
Patterns For Parallel Computing
Patterns For Parallel ComputingPatterns For Parallel Computing
Patterns For Parallel Computing
David Chou
ย 
Keras: Deep Learning Library for Python
Keras: Deep Learning Library for PythonKeras: Deep Learning Library for Python
Keras: Deep Learning Library for Python
Rafi Khan
ย 
Lecture 2 more about parallel computing
Lecture 2   more about parallel computingLecture 2   more about parallel computing
Lecture 2 more about parallel computing
Vajira Thambawita
ย 
Aca2 08 new
Aca2 08 newAca2 08 new
Aca2 08 new
Sumit Mittu
ย 
Introduction to Segmentation in Computer vision
Introduction to Segmentation in Computer vision Introduction to Segmentation in Computer vision
Introduction to Segmentation in Computer vision
ParrotAI
ย 

What's hot (20)

Lecture 3
Lecture 3Lecture 3
Lecture 3
ย 
AI On the Edge: Model Compression
AI On the Edge: Model CompressionAI On the Edge: Model Compression
AI On the Edge: Model Compression
ย 
Detailed Simulation of Large-Scale Wireless Networks
Detailed Simulation of Large-Scale Wireless NetworksDetailed Simulation of Large-Scale Wireless Networks
Detailed Simulation of Large-Scale Wireless Networks
ย 
Using Multi-layered Feed-forward Neural Network (MLFNN) Architecture as Bidir...
Using Multi-layered Feed-forward Neural Network (MLFNN) Architecture as Bidir...Using Multi-layered Feed-forward Neural Network (MLFNN) Architecture as Bidir...
Using Multi-layered Feed-forward Neural Network (MLFNN) Architecture as Bidir...
ย 
Introduction to neural networks and Keras
Introduction to neural networks and KerasIntroduction to neural networks and Keras
Introduction to neural networks and Keras
ย 
Bt0068 computer organization and architecture
Bt0068   computer organization and architectureBt0068   computer organization and architecture
Bt0068 computer organization and architecture
ย 
3D-DRESD DReAMS
3D-DRESD DReAMS3D-DRESD DReAMS
3D-DRESD DReAMS
ย 
Lecture 4 principles of parallel algorithm design updated
Lecture 4   principles of parallel algorithm design updatedLecture 4   principles of parallel algorithm design updated
Lecture 4 principles of parallel algorithm design updated
ย 
Transfer learning with LTANN-MEM & NSA for solving multi-objective symbolic r...
Transfer learning with LTANN-MEM & NSA for solving multi-objective symbolic r...Transfer learning with LTANN-MEM & NSA for solving multi-objective symbolic r...
Transfer learning with LTANN-MEM & NSA for solving multi-objective symbolic r...
ย 
UIC Panella Thesis
UIC Panella ThesisUIC Panella Thesis
UIC Panella Thesis
ย 
Keras on tensorflow in R & Python
Keras on tensorflow in R & PythonKeras on tensorflow in R & Python
Keras on tensorflow in R & Python
ย 
A tutorial on CGAL polyhedron for subdivision algorithms
A tutorial on CGAL polyhedron for subdivision algorithmsA tutorial on CGAL polyhedron for subdivision algorithms
A tutorial on CGAL polyhedron for subdivision algorithms
ย 
2017 (albawi-alkabi)image-net classification with deep convolutional neural n...
2017 (albawi-alkabi)image-net classification with deep convolutional neural n...2017 (albawi-alkabi)image-net classification with deep convolutional neural n...
2017 (albawi-alkabi)image-net classification with deep convolutional neural n...
ย 
Convolutional neural network from VGG to DenseNet
Convolutional neural network from VGG to DenseNetConvolutional neural network from VGG to DenseNet
Convolutional neural network from VGG to DenseNet
ย 
Enhancing the matrix transpose operation using intel avx instruction set exte...
Enhancing the matrix transpose operation using intel avx instruction set exte...Enhancing the matrix transpose operation using intel avx instruction set exte...
Enhancing the matrix transpose operation using intel avx instruction set exte...
ย 
Patterns For Parallel Computing
Patterns For Parallel ComputingPatterns For Parallel Computing
Patterns For Parallel Computing
ย 
Keras: Deep Learning Library for Python
Keras: Deep Learning Library for PythonKeras: Deep Learning Library for Python
Keras: Deep Learning Library for Python
ย 
Lecture 2 more about parallel computing
Lecture 2   more about parallel computingLecture 2   more about parallel computing
Lecture 2 more about parallel computing
ย 
Aca2 08 new
Aca2 08 newAca2 08 new
Aca2 08 new
ย 
Introduction to Segmentation in Computer vision
Introduction to Segmentation in Computer vision Introduction to Segmentation in Computer vision
Introduction to Segmentation in Computer vision
ย 

Similar to Integrating research and e learning in advance computer architecture

1.My Presentation.pptx
1.My Presentation.pptx1.My Presentation.pptx
1.My Presentation.pptx
ArslanAliArslanAli
ย 
PID2143641
PID2143641PID2143641
PID2143641
Gustavo Pabon
ย 
Implementing True Zero Cycle Branching in Scalar and Superscalar Pipelined Pr...
Implementing True Zero Cycle Branching in Scalar and Superscalar Pipelined Pr...Implementing True Zero Cycle Branching in Scalar and Superscalar Pipelined Pr...
Implementing True Zero Cycle Branching in Scalar and Superscalar Pipelined Pr...
IDES Editor
ย 
Modern processors
Modern processorsModern processors
Modern processors
gowrivageesan87
ย 
Parallel Processing Concepts
Parallel Processing Concepts Parallel Processing Concepts
Parallel Processing Concepts
Dr Shashikant Athawale
ย 
DESIGN AND ANALYSIS OF A 32-BIT PIPELINED MIPS RISC PROCESSOR
DESIGN AND ANALYSIS OF A 32-BIT PIPELINED MIPS RISC PROCESSORDESIGN AND ANALYSIS OF A 32-BIT PIPELINED MIPS RISC PROCESSOR
DESIGN AND ANALYSIS OF A 32-BIT PIPELINED MIPS RISC PROCESSOR
VLSICS Design
ย 
Design and Analysis of A 32-bit Pipelined MIPS Risc Processor
Design and Analysis of A 32-bit Pipelined MIPS Risc ProcessorDesign and Analysis of A 32-bit Pipelined MIPS Risc Processor
Design and Analysis of A 32-bit Pipelined MIPS Risc Processor
VLSICS Design
ย 
DESIGN AND ANALYSIS OF A 32-BIT PIPELINED MIPS RISC PROCESSOR
DESIGN AND ANALYSIS OF A 32-BIT PIPELINED MIPS RISC PROCESSORDESIGN AND ANALYSIS OF A 32-BIT PIPELINED MIPS RISC PROCESSOR
DESIGN AND ANALYSIS OF A 32-BIT PIPELINED MIPS RISC PROCESSOR
VLSICS Design
ย 
Resisting skew accumulation
Resisting skew accumulationResisting skew accumulation
Resisting skew accumulation
Md. Hasibur Rashid
ย 
A Survey of Machine Learning Methods Applied to Computer ...
A Survey of Machine Learning Methods Applied to Computer ...A Survey of Machine Learning Methods Applied to Computer ...
A Survey of Machine Learning Methods Applied to Computer ...
butest
ย 
ACA-Lect10.pptx
ACA-Lect10.pptxACA-Lect10.pptx
ACA-Lect10.pptx
meghana092
ย 
Co question bank LAKSHMAIAH
Co question bank LAKSHMAIAH Co question bank LAKSHMAIAH
Co question bank LAKSHMAIAH
veena babu
ย 
1.prallelism
1.prallelism1.prallelism
1.prallelism
Mahesh Kumar Attri
ย 
1.prallelism
1.prallelism1.prallelism
1.prallelism
Mahesh Kumar Attri
ย 
Concurrent Matrix Multiplication on Multi-core Processors
Concurrent Matrix Multiplication on Multi-core ProcessorsConcurrent Matrix Multiplication on Multi-core Processors
Concurrent Matrix Multiplication on Multi-core Processors
CSCJournals
ย 
Pipelining in Computer System Achitecture
Pipelining in Computer System AchitecturePipelining in Computer System Achitecture
Pipelining in Computer System Achitecture
YashiUpadhyay3
ย 
Parallelization of Graceful Labeling Using Open MP
Parallelization of Graceful Labeling Using Open MPParallelization of Graceful Labeling Using Open MP
Parallelization of Graceful Labeling Using Open MP
IJSRED
ย 
Cloud Module 3 .pptx
Cloud Module 3 .pptxCloud Module 3 .pptx
Cloud Module 3 .pptx
ssuser41d319
ย 
CS 301 Computer ArchitectureStudent # 1 EID 09Kingdom of .docx
CS 301 Computer ArchitectureStudent # 1 EID 09Kingdom of .docxCS 301 Computer ArchitectureStudent # 1 EID 09Kingdom of .docx
CS 301 Computer ArchitectureStudent # 1 EID 09Kingdom of .docx
faithxdunce63732
ย 
Parallex - The Supercomputer
Parallex - The SupercomputerParallex - The Supercomputer
Parallex - The Supercomputer
Ankit Singh
ย 

Similar to Integrating research and e learning in advance computer architecture (20)

1.My Presentation.pptx
1.My Presentation.pptx1.My Presentation.pptx
1.My Presentation.pptx
ย 
PID2143641
PID2143641PID2143641
PID2143641
ย 
Implementing True Zero Cycle Branching in Scalar and Superscalar Pipelined Pr...
Implementing True Zero Cycle Branching in Scalar and Superscalar Pipelined Pr...Implementing True Zero Cycle Branching in Scalar and Superscalar Pipelined Pr...
Implementing True Zero Cycle Branching in Scalar and Superscalar Pipelined Pr...
ย 
Modern processors
Modern processorsModern processors
Modern processors
ย 
Parallel Processing Concepts
Parallel Processing Concepts Parallel Processing Concepts
Parallel Processing Concepts
ย 
DESIGN AND ANALYSIS OF A 32-BIT PIPELINED MIPS RISC PROCESSOR
DESIGN AND ANALYSIS OF A 32-BIT PIPELINED MIPS RISC PROCESSORDESIGN AND ANALYSIS OF A 32-BIT PIPELINED MIPS RISC PROCESSOR
DESIGN AND ANALYSIS OF A 32-BIT PIPELINED MIPS RISC PROCESSOR
ย 
Design and Analysis of A 32-bit Pipelined MIPS Risc Processor
Design and Analysis of A 32-bit Pipelined MIPS Risc ProcessorDesign and Analysis of A 32-bit Pipelined MIPS Risc Processor
Design and Analysis of A 32-bit Pipelined MIPS Risc Processor
ย 
DESIGN AND ANALYSIS OF A 32-BIT PIPELINED MIPS RISC PROCESSOR
DESIGN AND ANALYSIS OF A 32-BIT PIPELINED MIPS RISC PROCESSORDESIGN AND ANALYSIS OF A 32-BIT PIPELINED MIPS RISC PROCESSOR
DESIGN AND ANALYSIS OF A 32-BIT PIPELINED MIPS RISC PROCESSOR
ย 
Resisting skew accumulation
Resisting skew accumulationResisting skew accumulation
Resisting skew accumulation
ย 
A Survey of Machine Learning Methods Applied to Computer ...
A Survey of Machine Learning Methods Applied to Computer ...A Survey of Machine Learning Methods Applied to Computer ...
A Survey of Machine Learning Methods Applied to Computer ...
ย 
ACA-Lect10.pptx
ACA-Lect10.pptxACA-Lect10.pptx
ACA-Lect10.pptx
ย 
Co question bank LAKSHMAIAH
Co question bank LAKSHMAIAH Co question bank LAKSHMAIAH
Co question bank LAKSHMAIAH
ย 
1.prallelism
1.prallelism1.prallelism
1.prallelism
ย 
1.prallelism
1.prallelism1.prallelism
1.prallelism
ย 
Concurrent Matrix Multiplication on Multi-core Processors
Concurrent Matrix Multiplication on Multi-core ProcessorsConcurrent Matrix Multiplication on Multi-core Processors
Concurrent Matrix Multiplication on Multi-core Processors
ย 
Pipelining in Computer System Achitecture
Pipelining in Computer System AchitecturePipelining in Computer System Achitecture
Pipelining in Computer System Achitecture
ย 
Parallelization of Graceful Labeling Using Open MP
Parallelization of Graceful Labeling Using Open MPParallelization of Graceful Labeling Using Open MP
Parallelization of Graceful Labeling Using Open MP
ย 
Cloud Module 3 .pptx
Cloud Module 3 .pptxCloud Module 3 .pptx
Cloud Module 3 .pptx
ย 
CS 301 Computer ArchitectureStudent # 1 EID 09Kingdom of .docx
CS 301 Computer ArchitectureStudent # 1 EID 09Kingdom of .docxCS 301 Computer ArchitectureStudent # 1 EID 09Kingdom of .docx
CS 301 Computer ArchitectureStudent # 1 EID 09Kingdom of .docx
ย 
Parallex - The Supercomputer
Parallex - The SupercomputerParallex - The Supercomputer
Parallex - The Supercomputer
ย 

Recently uploaded

How to Predict Vendor Bill Product in Odoo 17
How to Predict Vendor Bill Product in Odoo 17How to Predict Vendor Bill Product in Odoo 17
How to Predict Vendor Bill Product in Odoo 17
Celine George
ย 
Nutrition Inc FY 2024, 4 - Hour Training
Nutrition Inc FY 2024, 4 - Hour TrainingNutrition Inc FY 2024, 4 - Hour Training
Nutrition Inc FY 2024, 4 - Hour Training
melliereed
ย 
How Barcodes Can Be Leveraged Within Odoo 17
How Barcodes Can Be Leveraged Within Odoo 17How Barcodes Can Be Leveraged Within Odoo 17
How Barcodes Can Be Leveraged Within Odoo 17
Celine George
ย 
spot a liar (Haiqa 146).pptx Technical writhing and presentation skills
spot a liar (Haiqa 146).pptx Technical writhing and presentation skillsspot a liar (Haiqa 146).pptx Technical writhing and presentation skills
spot a liar (Haiqa 146).pptx Technical writhing and presentation skills
haiqairshad
ย 
The basics of sentences session 7pptx.pptx
The basics of sentences session 7pptx.pptxThe basics of sentences session 7pptx.pptx
The basics of sentences session 7pptx.pptx
heathfieldcps1
ย 
NEWSPAPERS - QUESTION 1 - REVISION POWERPOINT.pptx
NEWSPAPERS - QUESTION 1 - REVISION POWERPOINT.pptxNEWSPAPERS - QUESTION 1 - REVISION POWERPOINT.pptx
NEWSPAPERS - QUESTION 1 - REVISION POWERPOINT.pptx
iammrhaywood
ย 
Bonku-Babus-Friend by Sathyajith Ray (9)
Bonku-Babus-Friend by Sathyajith Ray  (9)Bonku-Babus-Friend by Sathyajith Ray  (9)
Bonku-Babus-Friend by Sathyajith Ray (9)
nitinpv4ai
ย 
THE SACRIFICE HOW PRO-PALESTINE PROTESTS STUDENTS ARE SACRIFICING TO CHANGE T...
THE SACRIFICE HOW PRO-PALESTINE PROTESTS STUDENTS ARE SACRIFICING TO CHANGE T...THE SACRIFICE HOW PRO-PALESTINE PROTESTS STUDENTS ARE SACRIFICING TO CHANGE T...
THE SACRIFICE HOW PRO-PALESTINE PROTESTS STUDENTS ARE SACRIFICING TO CHANGE T...
indexPub
ย 
BIOLOGY NATIONAL EXAMINATION COUNCIL (NECO) 2024 PRACTICAL MANUAL.pptx
BIOLOGY NATIONAL EXAMINATION COUNCIL (NECO) 2024 PRACTICAL MANUAL.pptxBIOLOGY NATIONAL EXAMINATION COUNCIL (NECO) 2024 PRACTICAL MANUAL.pptx
BIOLOGY NATIONAL EXAMINATION COUNCIL (NECO) 2024 PRACTICAL MANUAL.pptx
RidwanHassanYusuf
ย 
Oliver Asks for More by Charles Dickens (9)
Oliver Asks for More by Charles Dickens (9)Oliver Asks for More by Charles Dickens (9)
Oliver Asks for More by Charles Dickens (9)
nitinpv4ai
ย 
Mule event processing models | MuleSoft Mysore Meetup #47
Mule event processing models | MuleSoft Mysore Meetup #47Mule event processing models | MuleSoft Mysore Meetup #47
Mule event processing models | MuleSoft Mysore Meetup #47
MysoreMuleSoftMeetup
ย 
Jemison, MacLaughlin, and Majumder "Broadening Pathways for Editors and Authors"
Jemison, MacLaughlin, and Majumder "Broadening Pathways for Editors and Authors"Jemison, MacLaughlin, and Majumder "Broadening Pathways for Editors and Authors"
Jemison, MacLaughlin, and Majumder "Broadening Pathways for Editors and Authors"
National Information Standards Organization (NISO)
ย 
Skimbleshanks-The-Railway-Cat by T S Eliot
Skimbleshanks-The-Railway-Cat by T S EliotSkimbleshanks-The-Railway-Cat by T S Eliot
Skimbleshanks-The-Railway-Cat by T S Eliot
nitinpv4ai
ย 
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) Curriculum
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) CurriculumPhilippine Edukasyong Pantahanan at Pangkabuhayan (EPP) Curriculum
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) Curriculum
MJDuyan
ย 
Prรฉsentationvvvvvvvvvvvvvvvvvvvvvvvvvvvv2.pptx
Prรฉsentationvvvvvvvvvvvvvvvvvvvvvvvvvvvv2.pptxPrรฉsentationvvvvvvvvvvvvvvvvvvvvvvvvvvvv2.pptx
Prรฉsentationvvvvvvvvvvvvvvvvvvvvvvvvvvvv2.pptx
siemaillard
ย 
Gender and Mental Health - Counselling and Family Therapy Applications and In...
Gender and Mental Health - Counselling and Family Therapy Applications and In...Gender and Mental Health - Counselling and Family Therapy Applications and In...
Gender and Mental Health - Counselling and Family Therapy Applications and In...
PsychoTech Services
ย 
RHEOLOGY Physical pharmaceutics-II notes for B.pharm 4th sem students
RHEOLOGY Physical pharmaceutics-II notes for B.pharm 4th sem studentsRHEOLOGY Physical pharmaceutics-II notes for B.pharm 4th sem students
RHEOLOGY Physical pharmaceutics-II notes for B.pharm 4th sem students
Himanshu Rai
ย 
HYPERTENSION - SLIDE SHARE PRESENTATION.
HYPERTENSION - SLIDE SHARE PRESENTATION.HYPERTENSION - SLIDE SHARE PRESENTATION.
HYPERTENSION - SLIDE SHARE PRESENTATION.
deepaannamalai16
ย 
Haunted Houses by H W Longfellow for class 10
Haunted Houses by H W Longfellow for class 10Haunted Houses by H W Longfellow for class 10
Haunted Houses by H W Longfellow for class 10
nitinpv4ai
ย 
Leveraging Generative AI to Drive Nonprofit Innovation
Leveraging Generative AI to Drive Nonprofit InnovationLeveraging Generative AI to Drive Nonprofit Innovation
Leveraging Generative AI to Drive Nonprofit Innovation
TechSoup
ย 

Recently uploaded (20)

How to Predict Vendor Bill Product in Odoo 17
How to Predict Vendor Bill Product in Odoo 17How to Predict Vendor Bill Product in Odoo 17
How to Predict Vendor Bill Product in Odoo 17
ย 
Nutrition Inc FY 2024, 4 - Hour Training
Nutrition Inc FY 2024, 4 - Hour TrainingNutrition Inc FY 2024, 4 - Hour Training
Nutrition Inc FY 2024, 4 - Hour Training
ย 
How Barcodes Can Be Leveraged Within Odoo 17
How Barcodes Can Be Leveraged Within Odoo 17How Barcodes Can Be Leveraged Within Odoo 17
How Barcodes Can Be Leveraged Within Odoo 17
ย 
spot a liar (Haiqa 146).pptx Technical writhing and presentation skills
spot a liar (Haiqa 146).pptx Technical writhing and presentation skillsspot a liar (Haiqa 146).pptx Technical writhing and presentation skills
spot a liar (Haiqa 146).pptx Technical writhing and presentation skills
ย 
The basics of sentences session 7pptx.pptx
The basics of sentences session 7pptx.pptxThe basics of sentences session 7pptx.pptx
The basics of sentences session 7pptx.pptx
ย 
NEWSPAPERS - QUESTION 1 - REVISION POWERPOINT.pptx
NEWSPAPERS - QUESTION 1 - REVISION POWERPOINT.pptxNEWSPAPERS - QUESTION 1 - REVISION POWERPOINT.pptx
NEWSPAPERS - QUESTION 1 - REVISION POWERPOINT.pptx
ย 
Bonku-Babus-Friend by Sathyajith Ray (9)
Bonku-Babus-Friend by Sathyajith Ray  (9)Bonku-Babus-Friend by Sathyajith Ray  (9)
Bonku-Babus-Friend by Sathyajith Ray (9)
ย 
THE SACRIFICE HOW PRO-PALESTINE PROTESTS STUDENTS ARE SACRIFICING TO CHANGE T...
THE SACRIFICE HOW PRO-PALESTINE PROTESTS STUDENTS ARE SACRIFICING TO CHANGE T...THE SACRIFICE HOW PRO-PALESTINE PROTESTS STUDENTS ARE SACRIFICING TO CHANGE T...
THE SACRIFICE HOW PRO-PALESTINE PROTESTS STUDENTS ARE SACRIFICING TO CHANGE T...
ย 
BIOLOGY NATIONAL EXAMINATION COUNCIL (NECO) 2024 PRACTICAL MANUAL.pptx
BIOLOGY NATIONAL EXAMINATION COUNCIL (NECO) 2024 PRACTICAL MANUAL.pptxBIOLOGY NATIONAL EXAMINATION COUNCIL (NECO) 2024 PRACTICAL MANUAL.pptx
BIOLOGY NATIONAL EXAMINATION COUNCIL (NECO) 2024 PRACTICAL MANUAL.pptx
ย 
Oliver Asks for More by Charles Dickens (9)
Oliver Asks for More by Charles Dickens (9)Oliver Asks for More by Charles Dickens (9)
Oliver Asks for More by Charles Dickens (9)
ย 
Mule event processing models | MuleSoft Mysore Meetup #47
Mule event processing models | MuleSoft Mysore Meetup #47Mule event processing models | MuleSoft Mysore Meetup #47
Mule event processing models | MuleSoft Mysore Meetup #47
ย 
Jemison, MacLaughlin, and Majumder "Broadening Pathways for Editors and Authors"
Jemison, MacLaughlin, and Majumder "Broadening Pathways for Editors and Authors"Jemison, MacLaughlin, and Majumder "Broadening Pathways for Editors and Authors"
Jemison, MacLaughlin, and Majumder "Broadening Pathways for Editors and Authors"
ย 
Skimbleshanks-The-Railway-Cat by T S Eliot
Skimbleshanks-The-Railway-Cat by T S EliotSkimbleshanks-The-Railway-Cat by T S Eliot
Skimbleshanks-The-Railway-Cat by T S Eliot
ย 
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) Curriculum
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) CurriculumPhilippine Edukasyong Pantahanan at Pangkabuhayan (EPP) Curriculum
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) Curriculum
ย 
Prรฉsentationvvvvvvvvvvvvvvvvvvvvvvvvvvvv2.pptx
Prรฉsentationvvvvvvvvvvvvvvvvvvvvvvvvvvvv2.pptxPrรฉsentationvvvvvvvvvvvvvvvvvvvvvvvvvvvv2.pptx
Prรฉsentationvvvvvvvvvvvvvvvvvvvvvvvvvvvv2.pptx
ย 
Gender and Mental Health - Counselling and Family Therapy Applications and In...
Gender and Mental Health - Counselling and Family Therapy Applications and In...Gender and Mental Health - Counselling and Family Therapy Applications and In...
Gender and Mental Health - Counselling and Family Therapy Applications and In...
ย 
RHEOLOGY Physical pharmaceutics-II notes for B.pharm 4th sem students
RHEOLOGY Physical pharmaceutics-II notes for B.pharm 4th sem studentsRHEOLOGY Physical pharmaceutics-II notes for B.pharm 4th sem students
RHEOLOGY Physical pharmaceutics-II notes for B.pharm 4th sem students
ย 
HYPERTENSION - SLIDE SHARE PRESENTATION.
HYPERTENSION - SLIDE SHARE PRESENTATION.HYPERTENSION - SLIDE SHARE PRESENTATION.
HYPERTENSION - SLIDE SHARE PRESENTATION.
ย 
Haunted Houses by H W Longfellow for class 10
Haunted Houses by H W Longfellow for class 10Haunted Houses by H W Longfellow for class 10
Haunted Houses by H W Longfellow for class 10
ย 
Leveraging Generative AI to Drive Nonprofit Innovation
Leveraging Generative AI to Drive Nonprofit InnovationLeveraging Generative AI to Drive Nonprofit Innovation
Leveraging Generative AI to Drive Nonprofit Innovation
ย 

Integrating research and e learning in advance computer architecture

  • 1.
  • 2. ๏ƒ˜ Here we present methods in teaching advanced computer architecture courses. These methods include presenting fundamental computer architecture issues using e-learning; employing visual aids to teach fundamentals concepts like Caches, pipelining and scheduling. 2
  • 3. ๏ƒ˜ Advance Computer Architecture usually combines software and hardware approaches that increase the performance of microprocessor design. ๏ƒ˜ Main concepts in this courses includes measuring performance, Instruction Set Design, Memory Hierarchy and Caches, Pipelining and its Hazards, Instruction Level Parallelism, I/O storage, and latest contemporary computer architecture issues. ๏ƒ˜ By using these concepts this course also presents the quantitative approaches to measure the feasibility. 3
  • 4. ๏ƒ˜ These approaches also measure the performance emphasizing on the differences between hardware and software approaches. ๏ƒ˜ There are several books available on Computer Architecture concepts. ๏ƒ˜ Hennessy and Pattersonโ€™s are the one who gives a comprehensive documentation on most of computer architecture topics. 4
  • 5. Concepts for e-learning are ๏‚ž Cache Associativity ๏‚ž Superscalar microprocessors. ๏‚ž Dynamic scheduling algorithms. 5
  • 6. ๏‚ž Definition ๏ƒ˜ It is the easy control of direct mapping cache and a fully associative cache. ๏ƒ˜ Each cache location can have more than one pair of tag and data item that resides at same location in cache memory. ๏ƒ˜ If one cache location is holding two pair of tag and data item that is called two-way set associative cache. 6
  • 7. ๏ƒ˜ A 2-way set associative cache having 8 lines will have 4 sets and each set has two lines. ๏ƒ˜ Figures show the set associativity explain ๏ƒ˜ This approach presents the cache to be split into number of sets and each set has equal number of lines. 7
  • 8. Visual aid made the concepts easy to understand and we can easily explained our point by adding visual aids and graphics ๏‚ž Pipelining and its hazards ๏‚ž Superscalar design ๏‚ž Instruction Level Parallelism ๏‚ž Dynamic Scheduling. 8
  • 9. ๏‚ž Pipelining ๏ƒ˜ A Pipelining is a series of stages, where some work is done at each stage in parallel. ๏ƒ˜ The stages are connected one to the next to form a pipe instructions enter at one end, progress through the stages, and exit at the other end. ๏‚ž pipelining hazards ๏ƒ˜ Prevent the next instruction in the instruction stream from being executing during its designated clock cycle. ๏ƒ˜ Hazards reduce the performance from the ideal speedup gained by pipelining 9
  • 10. ๏ƒ˜ DLX is simple pipelining architecture for CPU. ๏ƒ˜ This is the seven clock cycle that is required to execute the instruction K+(n-1) cycle ๏ƒ˜ The pipeline could be also shown in terms of cycles, meaning display the events at each clock cycle DLX pipeline Starting stage DLX pipeline 2nd instruction 10
  • 11. Pipelining hazards ๏ƒ˜ For pipeline hazards, the visual aid could show bubbles inserted in the pipeline figure show bubbles and data forwarded using arrows. 11
  • 12. ๏ƒ˜ The concept of superscalars can also be explained with the visual aids. ๏ƒ˜ This figure show a 2-way issues for a DLX superscalar machine ๏ƒ˜ where one pipeline is assigned for integer and the other for floating-point operations. Note that floating-point operation takes 3 cycles to execute. 12
  • 13. ๏‚ž Definition ๏ƒ˜ Instruction level parallelism (ILP) is a measure of how many of the instructions in a computer program can be executed simultaneously. ๏ƒ˜ In Dynamic scheduling hardware determines which instructions to execute, ๏ƒ˜ ILP and Dynamic Scheduling is made easy by using visual aid. 13
  • 14. Tomasulaโ€™s algorithm ๏ƒ˜ It is a computer architecture hardware algorithm for dynamic scheduling of instructions. ๏ƒ˜ It allows out-of-order execution and enables more efficient use of multiple execution units. ๏ƒ˜ At cycle =0 five instructions scheduled ๏ƒ˜ Student re-write each cycle result. ๏ƒ˜ This idea involve the student in the process of learning and solving the problem. 14
  • 15. ๏ƒ˜ Advanced Computer Architecture is rich with new topics that are in the research stage. ๏ƒ˜ The student must be aware of these topics before completing any advanced computer architecture course. 15
  • 16. ๏ƒ˜ Advanced Computer Architecture is rich with advanced topics. The most advanced way of learning is through visual aids and e-learning. Future trends in teaching Computer Architecture may lead to e-learning at a distance. 16
  • 17. ๏ƒ˜ http://web.cs.iastate.edu/~prabhu/Tutorial/PIPELINE/ha zards.html ๏ƒ˜ https://en.wikipedia.org/wiki/Tomasulo_algorithm ๏ƒ˜ https://kb.iu.edu/d/aett ๏ƒ˜ http://www.pcguide.com/ref/mbsys/cache/funcMapping- c.html 17